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Cultural Studies: Unraveling the Influence of Culture on Society

• Al Istiqlal University (Palestinian Academy for Security Sciences)

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Explore Our Top Cultural Research Paper Topics

Updated 20 Jun 2024

Culture is a broad term that covers an endless number of possibilities for crafting research topics. You can view it as a global aspect and write a research paper about culture inherent in all of humanity.

On the other hand, you may focus on answering some particular research questions about culture for a specific state or region, e.g., the local community you live in. Another possibility is to compare two cultures and learn about beautiful ethnic differences.

Whichever the case, writing a cultural research paper will open a unique world for us where we can view humanity on a more in-depth level and decipher what is inherent in each culture. Since the options for cultural research paper topics are numerous, it’s essential to choose the one that will catch the reader’s attention.

If the topic is too broad or too narrow, the reader will either get lost in the process of reading or end up lacking crucial information regarding your topic. If you're overwhelmed with assignments, you might consider the option to pay someone to write my paper , ensuring your research is thorough and well-presented. Therefore, to be sure that we satisfy our readers, we must pay close attention to choosing the right topic. Let’s see how.

How to Choose Interesting Cultural Research Paper Topics

Here are a couple of tips from our  research paper writing services on how to choose an interesting topic. Before the writing process, you should consider the following:

• Consult people from your surrounding.  Is there someone native from the culture you want to write about you can reach out to? Bear in mind that the most accurate information comes from culture bearers.
• Make a profound research about the topic you’re intended to write about.  Nothing is random in culture - each tradition, habit, style, and background have a specific goal and a purpose.
• Try to place yourself in the shoes of a culture’s representative.
• Always be accepting and tolerant.  Try not to involve emotions in the choice of topics and write accurately about them.

List of Culture Research Topics

Here’s a list of 20 interesting and somewhat general topics about culture everyone can find something suitable from:

• The Impact of Globalization on Indigenous Cultures
• Cultural Identity in the Digital Age: A New Form of Nationalism?
• The Role of Language in Preserving Cultural Heritage
• Cross-Cultural Comparisons of Marriage and Family Structures
• Cultural Implications of Climate Change on Traditional Societies
• The Evolution of Gender Roles within Different Cultures
• Food as a Cultural Ambassador: Exploring Culinary Diplomacy
• Cultural Responses to Pandemics: A Historical Perspective
• The Influence of Religion on Art and Architecture across Cultures
• Cultural Appropriation vs. Cultural Exchange: Drawing the Line
• The Role of Festivals in Promoting and Preserving Cultural Identity
• Impact of Colonialism on the Cultural Practices of Indigenous Peoples
• Cultural Assimilation and Resistance: Case Studies from Around the World
• The Psychology of Superstitions and Their Cultural Significance
• Cultural Perspectives on Aging and Elder Care
• The Intersection of Technology and Culture: A Double-Edged Sword
• Cultural Traditions in Conservation and Environmental Stewardship
• Music as a Reflection of Social and Cultural Change
• Cultural and Ethical Considerations in Genetic Research
• The Dynamics of Cultural Conflict and Cooperation in Multicultural Societies

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Cultural Diversity Research Paper Topics

The more people, countries and religions are on the planet, the greater the diversity. When choosing a title from this list, make sure to look wider.

• The Impact of Cultural Diversity on Global Business Practices
• Multiculturalism in Education: Challenges and Opportunities
• Cultural Diversity and Its Influence on Global Marketing Strategies
• The Role of Language in Promoting Cultural Diversity
• Immigration and Cultural Integration: Success Stories and Challenges
• Cultural Diversity in the Workplace: Benefits and Challenges
• The Impact of Cultural Diversity on Team Dynamics and Performance
• Cultural Representation in Media and Entertainment
• The Effects of Globalization on Preserving Local Cultures
• Cultural Diversity and Public Policy: Case Studies from Around the World
• The Role of Cultural Festivals in Promoting Diversity and Unity
• Cultural Diversity in Healthcare: Understanding and Overcoming Barriers
• The Influence of Cultural Diversity on Artistic Expression
• Cultural Diversity and Conflict Resolution: Lessons Learned
• The Role of Technology in Bridging Cultural Gaps
• Cultural Diversity in Sports: Breaking Down Barriers
• The Impact of Migration on Cultural Identity
• Cultural Diversity and Innovation: How Diversity Fuels Creativity
• The Challenges of Cultural Relativism in a Globalized World
• Promoting Cultural Diversity and Tolerance through Education

Cultural Anthropology Research Paper Topics

Here, you’ll find a list of 10 ideas for research paper about culture that are concentrated on anthropological aspect:

• The Role of Rituals in Maintaining Social Order in Traditional Societies
• Kinship and Social Structure: A Comparative Analysis of Matrilineal and Patrilineal Societies
• Cultural Adaptations to Environmental Changes in Indigenous Communities
• The Impact of Westernization on Indigenous Cultural Practices
• Language Preservation and Revitalization in Minority Cultures
• Gender Roles and Their Evolution in Different Cultures
• The Anthropology of Food: Cultural Significance of Cuisine Across Societies
• Traditional Healing Practices and Their Place in Modern Medicine
• The Effects of Globalization on Language and Cultural Identity
• Cultural Perspectives on Death and Mourning Practices
• The Influence of Colonialism on the Cultural Landscape of Africa
• Urbanization and Its Impact on Traditional Social Structures
• Cultural Constructs of Beauty and Body Image Worldwide
• The Role of Folklore and Mythology in Shaping Cultural Values
• Cultural Anthropology of Digital Communities and Online Behavior
• Migration Patterns and Their Impact on Cultural Identity
• The Intersection of Culture and Mental Health Practices
• Economic Systems in Traditional Societies: From Barter to Digital Currency
• The Anthropology of Religion: Rituals, Beliefs, and the Supernatural
• Cross-Cultural Studies on Aging and Elderly Care

Subculture Research Ideas

• The Evolution of Punk Culture and Its Influence on Music and Fashion
• Cyber Subcultures: The Rise of Virtual Communities and Their Social Implications
• The Skateboarding Subculture: Lifestyle, Identity, and Urban Spaces
• Gothic Culture: Aesthetic, Literature, and Social Identity
• Hip-Hop and Rap: Cultural Expression, Social Issues, and Global Impact
• The Role of Zines in Subcultural Expression and Communication
• Cosplay Subculture: Identity, Performance, and Fandom
• The Vegan Movement: Ethical Consumption and Subcultural Identity
• Gamer Culture: Social Dynamics and Stereotypes in Gaming Communities
• Street Art and Graffiti: Artistic Expression or Vandalism?
• The Influence of Social Media on the Formation and Evolution of Subcultures
• Rave Culture and Electronic Dance Music: Community, Identity, and Experience
• The Mod Subculture: Fashion, Music, and Social Change in Post-War Britain
• Straight Edge Movement: Music, Lifestyle, and Ideology
• The Role of Subcultures in Shaping Youth Identity and Social Beliefs
• Kawaii Culture in Japan: Aesthetic, Consumerism, and Global Influence
• The Steampunk Aesthetic: Retrofuturism, Literature, and Community
• The Intersection of Subcultures and Political Movements
• Sneaker Culture: Collecting, Customization, and Community
• The Tiny House Movement: Minimalism, Sustainability, and Lifestyle Choice

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Pop Culture Research Topics

• The Evolution of Pop Music and Its Influence on Global Youth Culture
• Reality Television: Impact on Society's Perception of Reality
• Social Media Influencers: Shaping Trends and Consumer Behavior
• The Representation of Gender and Sexuality in Popular Films
• Memes and Internet Culture: Communication and Social Commentary
• The Globalization of Anime: Cultural Exchange and Adaptation
• Celebrity Culture and Its Impact on Self-Image and Aspirations
• The Rise of eSports: From Niche Hobby to Mainstream Entertainment
• Fashion Trends Originating from Pop Culture Icons
• The Role of Popular Literature in Shaping Contemporary Myths
• Superhero Movies: Cultural Significance and Box Office Dominance
• The Impact of Streaming Services on Television and Movie Consumption
• Fan Fiction and Fan Cultures: Participation and Creativity
• The Influence of Video Games on Popular Culture and Society
• Social Movements and Pop Culture: A Symbiotic Relationship
• The Commodification of Nostalgia in Film and Television
• The Role of Music Videos in Shaping Pop Music Perception
• The Impact of Pop Culture on Language and Slang
• Viral Marketing: How Pop Culture Facilitates Brand Engagement
• The Representation of Science and Technology in Pop Culture

Socio-Cultural Essay Topics

Here are ten exciting socio-cultural ideas. If you’re interested in comparing a community’s social and moral aspects, choose one title from this list as a basis.

• The Impact of Cultural Norms on Gender Roles and Expectations
• Social Media's Role in Shaping Modern Cultural Identities
• Cultural Dimensions of Globalization: Homogenization vs. Cultural Diversity
• Language as a Cultural Tool: Its Role in Shaping Social Reality
• The Influence of Religious Beliefs on Social Behavior and Norms
• Migration and Cultural Integration: Challenges and Opportunities
• Cultural Perspectives on Mental Health and Well-being
• The Role of Education in Transmitting Cultural Values
• Social Stratification and Cultural Capital: The Dynamics of Inequality
• Cultural Responses to Environmental Challenges and Sustainability
• The Evolution of Family Structures and Its Socio-Cultural Implications
• Youth Subcultures and Their Rebellion Against Societal Norms
• The Influence of Popular Culture on Political Engagement and Discourse
• Cultural Traditions and Their Impact on Modern Legal Systems
• The Role of Art and Culture in Social Activism and Change
• Cultural and Social Implications of Biotechnological Advances
• The Sociology of Food: Cultural Significance and Social Practices
• Cultural Identity in Multicultural Societies: Belonging and Conflict
• The Impact of Tourism on Local Cultures and Social Structures
• Cultural Stereotypes and Their Effects on Interpersonal and Intergroup Relations

Cultural Phenomena Topics

• The Global Spread of Fast Food Culture and Its Impact on Dietary Habits
• The Rise of Social Networking Sites and Their Influence on Social Relationships
• Eco-Conscious Living: From Niche Lifestyle to Mainstream Culture
• The Cultural Significance of Memes in Digital Communication
• The Impact of Reality TV on Perceptions of Reality and Fame
• The Phenomenon of Binge-Watching and Its Effects on Content Consumption
• The Influence of Hipster Culture on Fashion, Music, and Lifestyle
• The Role of Viral Challenges in Shaping Online Communities
• Minimalism: A Cultural Reaction to Consumerism
• The Resurgence of Vinyl Records in the Digital Age
• The Cultural and Social Implications of Body Modification
• The Rise of Digital Nomadism and Changing Work Cultures
• Fan Culture and Celebrity Worship: Psychological and Social Dimensions
• The Impact of Cancel Culture on Public Discourse and Accountability
• The Evolution of Language and Slang in the Internet Era
• The Growing Popularity of Esports and Its Recognition as a Legitimate Sport
• The Cultural Phenomenon of Selfie Culture and Its Impact on Self-Perception
• The Influence of Streaming Services on Music and Television Consumption
• The Role of Podcasts in Shaping Modern Media Consumption
• The Emergence of Autonomous Sensory Meridian Response (ASMR) as a Cultural Trend

Cultural Psychology Research Topics

• Cross-Cultural Variations in Emotional Expression and Recognition
• The Impact of Collectivism vs. Individualism on Self-Identity and Social Behavior
• Cultural Influences on Cognitive Development and Learning Styles
• The Role of Culture in Shaping Attitudes towards Mental Health and Therapy
• Acculturation Stress and Coping Mechanisms among Immigrants
• Cultural Dimensions of Parenting Styles and Child Outcomes
• Language and Thought: How Linguistic Diversity Shapes Cognitive Processes
• Cultural Adaptations of Psychological Interventions and Therapies
• The Psychology of Superstitions and Magical Thinking across Cultures
• Socialization Practices and Their Impact on Gender Roles and Identities
• Cultural Perspectives on Aging and the Elderly
• The Influence of Religious Beliefs on Psychological Well-being and Coping Strategies
• Cross-Cultural Differences in Perception and Visual Cognition
• Cultural Norms and Their Impact on Conflict Resolution Styles
• The Role of Cultural Heritage in Shaping Individual Values and Morals
• Intercultural Communication: Psychological Barriers and Bridges
• Cultural Factors Influencing Decision Making and Risk Taking
• The Impact of Cultural Diversity on Team Dynamics and Creativity
• Cultural Identity Development during Adolescence
• The Psychological Effects of Cultural Displacement and Identity Negotiation

Western Civilization Essay Topics

• The Influence of Ancient Greek Democracy on Modern Political Systems
• The Role of the Roman Empire in Shaping European Culture and Law
• Christianity and Its Impact on Western Ethical and Moral Values
• The Renaissance: Humanism and Its Contributions to Art and Science
• The Reformation and Its Effect on Religious and Political Landscapes in Europe
• The Enlightenment: Reason, Individualism, and the Birth of Modern Thought
• The Industrial Revolution and Its Social and Economic Consequences
• Colonialism and Its Legacy in Modern Western Societies
• The French Revolution: Liberty, Equality, Fraternity, and Its Global Impact
• The Development of Constitutional Monarchies in Europe
• The Impact of World War I on the Political Map of Europe
• The Rise and Fall of Fascism and Communism in 20th Century Europe
• The Cold War: Ideological Conflict and Its Influence on Global Politics
• The European Union: Integration, Expansion, and Challenges
• The Influence of American Culture on Western Society in the 20th Century
• The Digital Revolution and Its Impact on Western Societies
• The Role of Women in Western Civilization: From Antiquity to Feminism
• The Impact of Immigration on Cultural Diversity in Western Countries
• Environmentalism and Its Growing Influence in Western Policy and Culture
• The Future of Western Civilization: Challenges and Prospects in a Globalized World

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What are the biophysical and emotional thresholds of hunger and what does it take for people in vulnerable communities to navigate them? For low-income communities in Luzon Island (Philippines), pantawid-gutom offers a provisional and fleeting means to distract themselves from the bodily demands of hunger. Gideon Lasco and Jhaki Mendoza’s ethnography of such alimentary distractions—from drugs to water or staples—offers a unique vantage point into the dynamic and material semiotics of urban poverty.

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Using the Cultures Framework for Research

• Open Access
• First Online: 23 March 2023

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• Janet Stephenson 2  

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This chapter is designed to guide academics and students who wish to undertake research using the cultures framework. It offers a structured approach to cultural research that can be used by researchers from diverse disciplinary backgrounds. The variables and dynamics depicted by the framework are able to be discovered, described and analysed using a wide variety of qualitative and quantitative methodologies. The framework can also be used as a meta-theoretical framing. It invites interdisciplinary endeavours and multi-method research approaches, and operates well as an integrating framework. Further research on culture and sustainability is needed to build up a better understanding of, amongst other things, universal cultural processes, transforming unsustainable meta-cultures, and the multiple roles that culture can play in sustainability transitions. The chapter concludes with suggesting further potential contributions to sustainability research  from each of the nine perspectives of culture described in Chapter 2 .

You have full access to this open access chapter,  Download chapter PDF

• Sustainability
• Qualitative methodology
• Quantitative methodology
• Multi-method
• Meta-theoretical
• Interdisciplinary
• Integrative
• Cultural theory

Introduction

I cannot think of a single research topic relating to the human/sustainability nexus that does not have a cultural component. From globally influential paradigms and the practices of fossil fuel majors to the operations of small businesses and the daily lives of households, culture is involved. Yet as a research topic, culture is often remaindered—applied as a loose label for a collection of features of social existence that sit unexamined alongside other deeply analysed phenomena. Apart from the fraction of researchers trained in forms of cultural analysis, the slippery, qualitative features of culture can seem too hard to investigate by researchers interested in sustainability issues. The cultures framework addresses this difficulty by offering a structured way to approach cultural research that can be used by researchers from almost any disciplinary background. As described in earlier chapters, the framework has been sufficiently tested to have confidence that it can fruitfully guide research endeavours.

Over the 12 years since the framework was first introduced in the literature, it has been used with a broad range of research approaches. It has been used with qualitative methods, quantitative methods and mixed methods. It has been used to formulate research design, as an analytical frame for the interpretation of existing data sets, and as a conceptual framing for meta-reviews of data. It has been used by individual researchers from a single discipline as well as by interdisciplinary research teams. It has underpinned undergraduate studies, postgraduate dissertations and extensive research programmes. It has been used to design research-based interventions and as an evaluation framework. And as shown in earlier chapters, it has been applied to a wide variety of problems and fields of enquiry.

This chapter is designed to guide academics and students who wish to undertake research using the cultures framework. For most of the chapter, I discuss the use of the framework to explore the interplay between culture and sustainability. By providing a structure for research investigations, the framework can help reveal what cultural ensembles, consisting of what cultural features, have causal relationships with what outcomes, affected by what external influences. It can help determine who are the actors within the culture group under study, and which cultural ensembles are already more sustainable than others. By examining the internal dynamics of culture, we can see how this leads to the sustainability outcomes. By studying cultural ensembles in relation to external influences, we can gain insights into why cultures remain static or evolve. By investigating the scope of agency of cultural actors, we can better understand why it is difficult for them to change, and who comprise more powerful organisations or institutions. And by examining whether a culture is dynamically stable or has the potential to change, we can gain insights into whether transformation is possible. Of course, not all these questions will be relevant to a given study, and the choice of questions will be determined by the particular context of the research and the sustainability issues at stake, but this gives an indication of the types of questions for which the framework can be used.

Towards the end of the chapter, I discuss how the framework can also be used as a meta-theoretical framing. In this sense, it can be used as an overarching structuring device for multidisciplinary, multi-theoretical and multi-method research, as with the examples of the Energy Cultures research programmes discussed in Chapter 7 . As covered in Chapter 4 , it builds on mature social science and cultural theories, and the framework acts as a structuring device for reaching into these fields of knowledge to examine dynamics and causal mechanisms in greater depth. I finish by discussing how the diverse and currently fragmented cultural theories discussed in Chapter 2 can make a stronger contribution to sustainability research.

Core Concepts

On the assumption that some readers may skip directly to this chapter, I will first recap on some key concepts. First, what culture is not. Culture is not about how people operate as individuals, each with their unique personal history and psychology. It is not about demographics. It is not about features that all humans share as social beings. All of these may interplay with culture, but they are not its defining characteristics. Second, the cultures framework is not just about culture. Cultures do not exist in a vacuum, and the framework draws attention to important variables that shape culture and mediate its implications for sustainability outcomes.

Recapping on what I mean by culture in this context, I describe it in Chapter 4 as comprising distinctive patterns of motivators (norms, values, beliefs, knowledge and symbolism), activities (routines and actions) and materiality (products and acquisitions) that form dynamic ensembles which are shared by a group of people and learned through both cognitive and bodily processes . These cultural ensembles can be most simply described as similar ways of thinking, doing and having that are evident across a group of people. Depending on the focus of research, this could apply to the cultures of people in their everyday lives, or the cultures of organisations or businesses, or cultures at even broader scales of institutions and ideologies.

Rather than focusing on describing groups that we typically think of in cultural terms (e.g. ethnic cultures, youth cultures, American culture), the framework invites inquiries into actors and their cultural ensembles that have implications for sustainability. Relevant actors may be identified at any scale: individuals, households, communities, organisations and beyond. Culture can be investigated in relation to a sustainability problem in both a causal sense and in the way in which cultural dynamics can resist change. Culture can also be investigated as part of sustainability solutions in the sense that many existing cultures are exemplars of sustainability. Cultural change can be a creative and fast-moving force for sustainability transitions.

The range of concerns of sustainability is exemplified by the United Nations’ 17 Sustainable Development Goals (United Nations, 2015 ) but as discussed in Chapter 1 , the SDGs are only one perspective on sustainability. More critical perspectives suggest that sustainability will not be achieved without more radical change to established systems of production and expectations of consumption. The framework does not predetermine what is meant by sustainability outcomes—this is left to the researcher to determine for their particular context.

The cultures framework has evolved over time. All the research examples I included in previous chapters used earlier terminologies (‘energy cultures framework’ or ‘sustainability cultures framework’) but the core concepts have changed little over time apart from becoming more generic. Earlier versions have produced sound and fruitful findings, and there is no reason why researchers cannot continue to use it in its earlier and slightly simpler form, especially those wishing to take their first forays into this field, in which case the guidance in Stephenson ( 2018 , 2020 ) will be helpful. In this chapter, I continue to use examples from this prior research, but describe how researchers can undertake inquiries using the revised cultures framework which is presented in Chapter 4 . I encourage readers of this chapter to return to Chapter 4 for fuller descriptions of the language, elements and dynamics of the revised framework.

A Guide to Research with the Cultures Framework

The framework can be applied in many different ways to support research processes. One way is to simply use the diagram of the cultural ensemble (Fig.  8.2 ) as the basis for describing a culture—its distinctive elements and their dynamics. It can be surprisingly difficult to explain what culture is, and these concepts give a solid foundation for identifying cultural features in any given context. At my university, some lecturers ask students to undertake at-home research to describe their own cultural ensembles that relate to energy use or greenhouse gas emissions. The diagram showing the ensemble, agency barrier and external influences (Fig.  8.5 ) has been used as the basis for discussions about research culture in university departments, and by research organisations to analyse how their own culture may be holding them back from undertaking transformative research. In these instances, it can be a tool for self-reflection, enabling actors to understand and articulate elements of their culture and constraints on change.

But more commonly, the framework is used by researchers in its full form (Fig.  8.1 ) for sustainability-related investigations. Some studies primarily seek to describe the cultural characteristics of a particular population. Examples I have discussed in earlier chapters include cooking cultures in Zambia, energy cultures in rural households in Transylvania and mobility cultures in New Zealand. Studies have also used the framework to compare cultures within a population. These have generally sought to explore the contribution of cultural differences to sustainability outcomes. Examples discussed in previous chapters include identifying varied cultural ensembles across populations in relation to energy consumption, energy efficiency and water consumption. Others have explored aspects of culture as influences on people’s readiness to engage in new collective behaviours, their responses to efficiency retrofits and as a factor in nations’ willingness to decarbonise.

The cultures framework

The framework is also useful for exploring barriers to cultural change. Studies discussed in earlier chapters have identified cultural characteristics that help explain resistance to change in the US Navy, failures to achieve desired levels of change in social housing interventions and cultural barriers to change in academic air travel. Chapter 7 discusses at length how the framework can be used as a basis for policy development and to underpin the evaluation of interventions.

The following section describes how to use the revised cultures framework to underpin research. For easier reference, I repeat here (as Fig. 8.1) the complete cultures framework diagram (first appearing as Fig.  4.8 in Chapter 4 ). The section is ordered as a step-by-step process, although it should be noted that not all research will involve all stages, and some research may proceed in a different order or head in different directions. Following this, I describe the range of research methods that have so far been used with the framework, and its methodological inclusivity in general.

Research on culture is research with people. In exploring what is needed to achieve societal transitions towards sustainability, researchers might wish to learn from groups and organisations that have already grappled with what it takes to live sustainably. They may wish to explore unsustainable cultures that seem unlikely to change. They might seek to work with culture groups or organisations that wish to change but can’t, or with those that are already on change journeys. In any situation, the research process and its outcomes have the potential to destabilise established beliefs, ways of life and social processes. Social research is a serious business and must be undertaken ethically and with the consent of, and ideally in collaboration with, those with whose lives you may disrupt.

Determining the Sustainability Outcomes

The cultures framework theorises that cultural ensembles have a causal relationship with sustainability outcomes, a concept that is conveyed by the two-headed arrow in Fig.  8.1 . The starting point for research design could be at either end of the arrow. If the sustainability outcomes to be examined are predetermined (e.g. energy consumption, equity, waste reduction), the research might seek to characterise different cultural ensembles within the population that have a causal relationship with these outcomes. Alternatively, the outcomes may be uncertain at the outset, but will emerge from the study. For example, research on the cultural ensembles of elderly households may reveal multiple sustainability implications such as health outcomes, energy expenditure and carbon emissions.

As discussed earlier, the concept of sustainability outcomes can be as broad or as specific, and as conservative or as radical, as the researcher wishes to make it. To be useful for the purposes of the framework, outcomes ideally are measurable (i.e. empirical evidence is available as to whether that outcome is improving or degrading) or at least able to be qualitatively described and compared. Outcomes can be uni-dimensional (e.g. a measure of water quality) or might consist of multiple interconnected qualities (e.g. health, biodiversity, equity). Outcomes may be of widespread benefit (e.g. reducing greenhouse gas emissions) or directly beneficial to the households themselves (e.g. improved health).

The double-headed arrow between cultural ensembles and outcomes also reminds researchers that if outcomes change, this changed context can become a further external influence. For example, if a farmer introduces practices that result in cleaner rivers and streams, this may create positive reinforcement for further cultural change. The farmer may enjoy being able to catch fish again, or seeing their children swimming, or hear positive feedback from community members, and may be encouraged to do more. Research on this kind of feedback could help identify whether and how positive affirmation from more sustainable outcomes can lead to ongoing cultural transformation.

Determining the Cultural Elements and Their Interactions

At an early point in the research process, it will be necessary to determine both the scope of the cultural ensemble and the scope of the member actors. The cultural elements to be studied will ultimately be determined by the sustainability outcomes you are interested in and the actors you are focusing on. For example, if you are interested in carbon emissions from a business sector, the obvious cultural actors to focus on would be those businesses, and the elements to study would be the motivators, materiality and activities that have a direct relationship to carbon emissions. However, from identifying this first-order group of actors, it may become clear that other actors also play a role. It may prove more useful to focus on a sub-group within the business such as senior leadership, or shareholders, or alternatively it may prove important to examine cultural factors at broader scales, such as at the sector level, or within suppliers for these businesses. As a researcher, be open to which group/s of actors it might be most useful to focus on. Depending on the research aim, it might be more useful to gain a rich understanding of the cultural ensembles of a small number of actors, or alternatively to investigate a narrow range of cultural features across a much larger population.

You may find it is useful to examine cultures at multiple scales. Cultures are identifiable and discussable from a minute scale, such as the cultural ensemble of a particular actor or organisation, to massive scales, such as the distinctive and enduring features of Western civilisation. You may find it useful to study the ways in which culture can act as structure—a high-level ensemble of beliefs, symbolism, practices and institutions, which shape other cultures that have less power and reach. The framework is relevant to supporting research at any scale and scope.

The next step is to determine which cultural features are most relevant to your study. The core variables of the framework reflect concepts about culture that repeatedly appear in cultural theories (see Chapter 3 ). Materiality comprises items that are made, acquired, owned, accumulated, held or nurtured by cultural actors. Activities are frequent and infrequent actions undertaken by cultural actors. Motivators are shared aspects of cognition that include norms, values, beliefs, knowledge and meanings (Fig.  8.2 ). Which specific features comprise the ensemble for the purposes of your research will depend on the sustainability outcomes, the nature of the actors and of course your interests as a researcher.

I have described a cultural ensemble as a generally consistent pattern of materiality, motivators and activities displayed by an actor or group of actors, but all three may not have equal pertinence depending on the issue—for example, beliefs, meanings or understandings may be more relevant in a particular case than activities or materiality, and vice versa. Cultures will rarely be distinguishable by unique sets of cultural elements; there may be a great deal of overlap between the ensembles of culture groups. The ways in which they are differentiated will be determined by the research context.

When doing research with the cultures framework, how deeply to drill into each element will depend on the nature of the study. For example, in relation to ‘motivators’, many studies to date have focused on depicting norms, because this was the terminology of the original cultures framework. Other studies using the framework have explored morals, meanings, values, knowledge and beliefs, which is one of the reasons for replacing ‘norms’ with ‘motivators’ in the revised cultures framework. In terms of activities, some studies have focused on routines while others have been more interested in one-off or occasional actions. Some have centred on one type of material item, while others have been interested in material assemblages. The nature of the topic should shape the focus of the research, and the researcher should hold open the possibility that relevant but unsuspected cultural features may emerge in the course of the research.

The cultural ensemble—the core elements and their dynamics

Although the research process will likely identify specific cultural features that can be directly causally related to the outcomes (e.g. the presence of particular technologies or practices), it is the cultural ensemble and dynamics between cultural features that make it ‘cultural’. Research should therefore seek to go beyond simply listing cultural features that bear a relationship to the outcomes of interest, to considering how they interact. Motivators, activities and materiality form the interconnected ‘system’ of culture, as indicated by the curved arrows in Fig.  8.2 . How people think influences what they acquire and how they act; people’s activities partly determine what they have and how they think; and the things that people have influence what they do and how they think. Exploring these interactions is critical to understanding how culture operates.

When considering the scope of cultural features to study, some may emerge as more significant than others depending on the sustainability outcomes you are interested in. For example, although sustainability research often focuses on routines or habits, it could be that in some instances, irregular or rare actions have the biggest impacts (noting that these can be equally culturally driven, such as the choice of a new house or whether to buy a car). In fields that you are familiar with, you may have a better chance of an ‘educated guess’ about which cultural features to start investigating, but you may be surprised. In research on household energy efficiency, we started by assuming that people’s values would strongly shape how efficient they were, but we found no consistent relationship between values and actions (Mirosa et al., 2011 ). So keep an open mind and, of course, explore literature in the field beforehand.

There will always be variability in the extent to which actors adopt cultural ensembles. Cultural uniformity is a myth—in reality, actors will have greater or lesser adherences to the ‘signature’ ensemble that is identified in research. This is not a problem, and indeed can provide useful insights into variability and opportunities for change. For example, if you are interested in sustainable transport, you might find that almost all actors own fossil fuelled cars, but some will use more fuel than others. Car owners will all have driving skills, but some may be more efficient drivers than others. All might drive their cars regularly, but some may drive more frequently than others. From a high-level perspective, they all share a similar mobility culture—one that is dependent on cars and fossil fuels—but if you drilled down you could identify variations in that culture. Where you choose to place your inclusion–exclusion delineation around this group, and whether you choose to segment it into sub-groups, will depend on the purpose of your research.

Ultimately, it doesn’t pay to agonise too much about exactly where to draw a line around the actors and cultural ensembles to study. What we’re interested in as researchers is finding patterns that reflect general similarities in cultural features which relate to sustainability outcomes. It is about sense-making through identifying fuzzy patterns of similarity and difference, which is more fruitful than assuming that everyone is identical.

Determining Cultural Vectors

If you are interested in how culture is transmitted, learned and adopted, you may also wish to examine the role of cultural vectors (Fig.  8.3 ). As discussed in Chapters 4 and 6 , vectors include such things as sensory encounters, forms of communication, bodily learning and semantic knowledge that are absorbed from sources such as social interactions, media, bodily experiences and formal learning. Through cultural vectors, people come to adopt similar activities to others, and/or acquire or make similar material items, and/or develop similar norms, aspirations, understandings and other motivators. Vectors are how people learn culture, how it is socially reinforced, and how new cultural concepts are passed from actor to actor.

Cultural vectors—the means by which culture is learned and shared

Cultural vectors will not necessarily be important for all research, but they can help reveal processes of cultural continuity and cultural change. In New Zealand research, for example, we asked householders about alterations they had recently made to improve the heating in their homes, and found that family and friends were by far the biggest influence on their decision. Hearing others' stories of change and experiencing the warmth of others' homes were far more influential than information campaigns, online information or advisory services.

Determining the Agency Boundary

Culture is most often used to describe shared characteristics across a population, but the cultures framework asks researchers to identify a subset of cultural features: those that are both particular to their chosen actors and that could potentially be changed by those actors. This demarcation is indicated in the cultures framework by the agency boundary, shown as a dashed circle around the core elements of culture (Fig.  8.4 ). The boundary reflects the capacity of the actor to make choices regarding their cultural ensemble. It distinguishes between elements of culture that are particular to and/or controlled by the actor group under study and those that are particular to and/or controlled by others. The actors’ capacity may be constrained by many things, such as their financial circumstances, their age or gender, their education or their familiarity with bureaucratic systems.

Depicting the agency boundary

In Chapters 4 – 6 , I describe several examples of how this agency distinction is made and used in research. One example is of people on low incomes living within rental housing; the outcomes of interest are energy consumption and wellbeing. Here, the house and chattels owned by the landlord are not considered part of the tenants’ energy culture because tenants have no control over them. The tenants’ cultural ensemble comprises the dynamic package of motivators, activities and materiality that they enact within those constraints. As well as being shaped by the landlord, their energy culture will be shaped by additional influences beyond the agency barrier, such as the cost of power, government policies and other external influences. Another example is personal mobility, where household actors’ cultural ensembles are strongly shaped and constrained by matters beyond their control, such as urban form, the availability of public transport, the safety of walking and cycling and government policies.

The agency boundary in the cultures framework thus invites researchers to differentiate between cultural features that are specific to the group they are studying (within the dashed circle), and other influences that shape (but are rarely influenced by) that culture. It also invites consideration of the factors that are limiting their agency, which may become highly relevant in studies where actors are unable to become more sustainable because of agency constraints. This invites the researcher to consider the implications of differentials in power, the relative responsibility for sustainability outcomes between actors within the agency boundary and those outside it, and their relative ability to act to alter these outcomes. Cultural features beyond actors’ agency belong in ‘external influences’ which may include more powerful cultures.

Determining the External Influences

External influences are exogenous factors that significantly shape the culture that is under study, and are conceptually located outside the agency boundary (Fig.  8.5 ). As discussed in prior chapters, external influences come in many forms, including qualities of the environment and infrastructure, purposeful policies and laws, pricing regimes, availability of technologies, and broadly accepted beliefs and conventions. For research purposes, it will be important to identify external influences that in some way affect the cultural ensembles under study, and thus ultimately affect the sustainability outcomes. They may, for example, reinforce existing cultural ensembles, erode the integrity of cultures that are already sustainable, force actors to become more unsustainable or support cultural change in a more sustainable direction. Depending on the research focus, some external influences may be apparent from the outset of the study, while others may be obscure and will need to be elicited through deep engagement with cultural actors. External factors that clearly have no influence on the culture under study can be ignored for the purposes of cultural analysis.

External influences on cultural ensembles

External influences can also be interpreted as broader cultures that influence the culture you are focusing on. For example, the mobility cultures of citizens are strongly shaped by cultural features of the municipality. A council that decides to invest its transport funding primarily in new motorways is not doing so arbitrarily. The decision will have emerged from a well-established system of beliefs, understandings, aspirations and organisational practices within the council—in other words, their culture. In researching external influences, it may therefore be important to look beyond their presenting qualities to understand the cultures within which they are embedded and replicated.

Another external influence to consider is your own impact on culture as a result of the research process. By asking questions of research participants, you are likely to be raising their own awareness of aspects of their culture that they may not have considered previously. In your interactions, even if it is not intended, you may make them more aware of the sustainability outcomes of their cultural ensembles, and/or aware of disjunctions between, say, their beliefs and practices, or between their aspirations and material possessions. Your interactions may also cause them to develop new understandings about the sustainability issue of interest, or open their eyes to external influences that they had not previously been aware were shaping their culture. The research process is never neutral, so be aware of how your work may influence your participants’ cultures, ensure that your work is carried out ethically and does no harm, and possibly build an evaluation of your impact as a researcher into your research.

Investigating Cultural Stability

Some cultures change very little over time, or at least in the features that give rise to sustainability outcomes. Some enduring cultural ensembles may be positive examples that research can learn much from, such as communities and organisations that have consciously set out to become more sustainable and have maintained that over time. Other cultural ensembles are deeply problematic from a sustainability perspective, and yet continue to endure. We can see this with highly consumptive lifestyles amongst many in the Western world, with beliefs in the value of consumption for its own sake, aspirations for material items goaded by the media (and today, by social influencers), practices of shopping valued in their own right and made more unsustainable through the proliferation of short-lived products, and wellbeing equated with more (or more wealth-signifying) possessions. The cultures framework offers a structure for exploring how and why many unsustainable cultural ensembles change little over time. It would be helpful to review the examples of research into cultural stability discussed in Chapter 5 .

Research into cultural stability might start by examining actors’ cultural ensembles, exploring relevant motivators, material assemblages and activities, and the extent to which these are aligned and mutually supportive. It may investigate cultural vectors in order to understand how cultural attributes are learned, reinforced and conveyed to new members. It would usefully identify what external influences (including structures, institutions and broader-scale cultures) are supporting the culture in its current form and enabling its continuance. It may be useful to look back in time and identify what has shaped the culture you see today. Unpacking these dynamic interactions can help explain how and why this culture is resistant to change.

Understanding these dynamics is particularly important if your research is seeking to understand why change interventions have failed to achieve their targets. Exploring culture as a dynamic system can reveal why change in one external influence or in a single cultural feature (e.g. new knowledge or a new technology) may make little or no difference to sustainability outcomes; for example because its impact is moderated by other cultural dynamics that tend to stabilise the cultural ensemble. Even if some aspects of culture (e.g. values, aspirations) are aligned with sustainable outcomes, other aspects (e.g. routines, agency limitations, external influences) may prevent or limit overall change. It is critical to gain a better understanding of the dynamics of cultural stability if we are to achieve widespread sustainability transitions.

Investigating Cultural Change

The cultures framework can also underpin research on how cultures change. From a sustainability perspective, your investigation might be into positive change, such as new cultural features being adopted with cascading impacts on the entire cultural ensemble. Of particular interest here might be how positive change processes are initiated, and the consequential effects on culture. An example that I described in Chapter 6 was how the replacement of kerosene lamps with solar lights in Vanuatu had a domino effect on many other aspects of culture including everyday practices, gender roles, beliefs, and aspirations for other solar and digital technologies. Your study could equally focus on negative cultural change, seeking to understand how sustainability-oriented cultural characteristics have been lost. For example, in Chapter 6 I described a Māori community where degradation of the inshore fisheries meant that community members could no longer gather traditional foods. The inability to undertake practices resulted in a loss of knowledge and skills that had previously sustained the fishery.

With the cultures framework as a structuring device, a researcher can explore what external influences might be tending to encourage change, as well as what changes are already occurring within that culture and whether these are leading to shifts in other cultural features. In the previous section, I discussed how cultural ensembles could become resistant to change due to strong alignments between motivators, activities and materiality. In contrast, systems where there are misalignments (e.g. aspirations are different to practices; material items don’t fit with beliefs) there is a greater potential for instability, innovation and change. Researchers interested in the potential for change might wish to examine the degree to which the relevant cultural elements are aligned.

Studying the processes of cultural change is critically important to sustainability transformations at all scales. The cultures framework can help to systematise analysis of where cultural change starts, whether it leads to consequential change to the cultural ensemble, the sustainability consequences of this change, and whether incipient changes are prevented by other factors. Cultural change is unlikely to occur all at once—it may involve incremental adjustments to the ensemble over time (e.g. a normative shift may precede a behavioural shift, or a new technology may precipitate new practices). Change also will not be uniform across a culture group, so the analysis may need to include identification of which actors have first made these changes, and through what vectors this has become more widely adopted. More research is needed to better understand the uneven, incremental processes of cultural change as well as the circumstances in which rapid transformation can occur.

People within a culture group rarely get to alter the more powerful external influences shaping their culture. But sometimes it happens, and this is possibly the most powerful driver of transformational change, as discussed towards the end of Chapter 6 . This is where cultural changes spread widely across less powerful actors, and membership of the new culture group grows to the extent that it starts to have influence beyond the agency barrier, reshaping the motivators, activities and/or materiality of more powerful actors. If researchers are interested in the potential for radical sustainability transformations, they should focus on the potential for outward as well as inwards flows through the agency barrier. The urgency of the sustainability crisis means that we need to know as much as possible about how to achieve rapid and widespread transformations of dominant unsustainable cultures.

Having an Impact

By now, your research will have produced an understanding of the various elements of the cultures framework and how they interact dynamically, and any external influences that are tending to prevent or enable change. You will understand the limits of actors’ agency, sub-cultures may have been identified and you may have also discovered cultural influences at other scales. You will have gathered evidence as to whether the cultural ensemble has positive or negative outcomes for the relevant measures of sustainability. You will know whether the culture is in the process of change or is resilient to change, and why this may be the case. If the ensemble has poor sustainability outcomes, your findings should indicate whether it has some latent potential for more sustainable change and possible ways in which change could be initiated or supported to achieve more sustainable consequences.

As a researcher, you might want to apply your findings further to actively help in the sustainability transition. Does it show a culture that already has great sustainability outcomes? If so, what can we learn from this and how can this success be supported and amplified? Does the research show a culture that is stuck in unsustainable patterns and unable to change? If so, where are the opportunities to support change? Does it show a culture that is gradually becoming more sustainable but has a way to go? If so, how can that journey be supported? Does is show a culture where attempts have been made towards greater sustainability but those attempts have been unsuccessful? If so, how can your findings help show why this might be the case?

As with many of the research projects using the cultures framework, you could develop recommendations for policy or practical actions. You might build on your work and develop a programme of action research that enables your insights to be trialled. You might assist an organisation or group of actors to interrogate their own culture and begin a process of change. You could collaborate with an already sustainable community over how to challenge the forces that are depleting it, or how to use cultural vectors to extend its reach. There are endless possibilities for making cultural research into a force for positive change.

Research Methodologies

Research with the cultures framework can be undertaken using a broad sweep of qualitative and quantitative methodologies. In this section, I outline the range of research methods that have been successfully used to date that I am aware of, and what functions these methods have played. This section is heavily referenced so that readers can go to the original papers for more detail on the specific methods of data elicitation and analysis.

Most studies to date using the cultures framework have used qualitative methods to examine cultural ensembles, either on their own or in combination with quantitative methods. Solely qualitative research often involves interviews followed by analysis to draw out evidence illustrating cultural elements (e.g. Bach et al., 2020 ; Lazowski et al., 2018 ; McKague et al., 2016 ; Scott & Lawson, 2018 ; Tesfamichael et al., 2020 ; Walton et al., 2014 ). Some projects have used a combination of qualitative methods such as workshops or focus groups together with interviews (e.g. Ambrosio-Albalá et al., 2019 ; Godbolt, 2015 ; Krietemeyer et al., 2021 ). A study of cultural change over an extensive period of time incorporated reviews of archaeological and historical evidence together with present-day interviews (Stovall, 2021 ). Researchers often apply thematic analyses to their qualitative material, but other analytical methods can be used. For example, a study on energy cultures of poverty analysed the interview texts using a computational social science methodology (Debnath et al., 2021 ).

Other researchers have used quantitative methods to characterise cultural ensembles. The elements of the framework have underpinned the design of surveys to elicit data from a larger population than is possible with face-to-face qualitative methods (e.g. Lawson & Williams, 2012 ) and as the basis of an ‘energy culture’ survey for businesses to determine the maturity of their energy efficiency efforts (Oksman et al., 2021 ). As well as using data produced from surveys specifically designed for this purpose, the cultures framework has been used retrospectively to underpin analysis of existing data sets to identify clusters of similar cultural characteristics aligned with different sustainability outcomes (e.g. Bardazzi & Pazienza, 2017 , 2018 , 2020 ; Walton et al., 2020 ). It has also been used as an integrating framework across multiple quantitative data sets (e.g. Manouseli et al., 2018 ). There will always be variations in the cultural ensembles of any group of actors, and sometimes it will be useful to explore this variability. Larger quantitative data sets have been used as a basis for segmenting populations into statistically distinctive groups  using cluster analysis (e.g. Barton et al., 2013 ; Lawson & Williams, 2012 ).

In studies using mixed qualitative and quantitative methods, the cultures framework has underpinned both design and/or analysis, and has been used to facilitate the integration of findings (e.g. Bell et al., 2014 ; Muza & Thomas, 2022 ; Scott et al., 2016 ). Some studies have gathered both qualitative and quantitative data relating to cultural elements during face-to-face interviews and integrate these in the analysis (e.g. Khan et al., 2021 ). Research on indicators of national energy cultures used a combination of policy analysis and quantitative analysis of comparative data sets (Stephenson et al., 2021 ).

To explore external influences (including multi-level cultures), studies often ask interviewees within the culture group about their perceptions of what shapes their decision-making or constrains their ability to make more sustainable choices (e.g. Ambrosio-Albalá et al., 2019 ; Debnath et al., 2021 ; McKague et al., 2016 ). Some also seek the views of experts or key informants in particular fields (e.g. Stephenson et al., 2015 ) or review the impact of laws and policies (e.g. Barton et al., 2013 ). Some projects have also interviewed actors who represent aspects of external influences (e.g. Jürisoo et al., 2019 ; Nicholas, 2021 ).

Many different research approaches can be used to identify causal relationships between cultural ensembles and sustainability outcomes. Some studies have done this quantitatively, such as identifying relationships between householder age cohorts and energy consumption (Bardazzi & Pazienza, 2017 ) and between timber drying cultures and energy use (Bell et al., 2014 ). One study used regression analysis to relate householders' cultural features to their interest in being involved in a local energy management scheme (Krietemeyer et al., 2021 ). However, in most studies to date using the cultures framework causal relationships are not quantified but are assumed based on well-established understandings of sustainable practices or the impacts of different technologies (e.g. Dew et al., 2017 ; Hopkins, 2017 ). Often the focus of research has been on whether the cultural ensemble has features that are known to align with more sustainable outcomes (e.g. types of technology and practices that represent business energy efficiency [Oksman et al., 2021 ; Walton et al., 2020 ]) rather than setting out to prove the well-understood relationship between these and measurable outcomes.

The framework has also assisted with modelling. A design for agent-based modelling for smart grid development drew from the cultures framework to incorporate energy use behaviours into the models (Snape et al., 2011 ). A project using system dynamics modelling of the uptake of electric vehicles also used the elements of the cultures framework as foundational data for the model (Rees, 2015 ). Methods such as these align well with the original conceptual framing of culture as a system, and offer a dynamic structure to explore system-type interactions between components of the framework.

The framework lends itself to multi-scalar analysis, as with research on PV uptake in Switzerland, where the work described generalised cultural ensembles of adopters and non-adopters and also drew insights on cultural processes from individuals (Bach et al., 2020 ). By focusing on collectives, researchers can observe patterns of similar cultural features across a population and identify broadly similar influences on and outcomes of that culture. By focusing on individual actors, they can also explore in detail the dynamics within cultural ensembles.

The framework has also been used to structure reviews of literature. Examples include reviews of the adoption of energy-efficient technology innovations in buildings (Soorige et al., 2022 ), academic air travel cultures (Tseng et al., 2022 ) and adoption of natural gas (Binney & Grigg, 2020 ). In a study on barriers and drivers for industrial energy efficiency, the framework was refined to fit an industrial context and used as an organising framework for metadata from a literature review on the barriers and drivers of energy behaviour in firms. This approach enabled the researchers to consider many interdependent components of efficiency decision-making by industry, including attitudinal factors, behaviours and technologies (Rotzek et al., 2018 ).

Some studies have investigated the effectiveness of interventions intended to improve sustainability outcomes. In these instances, they have used the framework to guide collection of pre-intervention and post-intervention data on cultural ensembles and/or outcomes (e.g. Rau et al., 2020 ; Scott et al., 2016 ). Other work has used the framework to design evaluation tools (e.g. Ford et al., 2016 ; Karlin et al., 2015 ).

Within larger research programmes, the framework can be used as a structuring device for allocating research roles and methods across an interdisciplinary team. In the Energy Cultures 1 and 2 research programmes, for example, we identified the core elements of culture in relation to energy efficiency (material aspects, practices, norms, beliefs, etc.) through householder questionnaires, focus groups and interviews. To relate cultural ensembles to energy outcomes, we included questions about energy consumption in the surveys and in later work we used data from smart electricity meters. Interrelationships between elements of the framework were explored in various ways. We used a values ‘laddering’ approach (from consumer psychology) to look at the relationships between values and household energy efficiency actions (Mirosa et al., 2013 ) and used choice modelling (an economics tool) to examine the interactivity between people’s motivators and preferences for adoption of efficient technologies (Thorsnes et al., 2017 ). These were staged so that the values work helped in the design of the choice modelling. We explored interactions between norms, material culture and practices with community focus groups, and these groups also assisted in identifying external influence that were barriers to changing behaviour. Desktop studies were used to examine regulatory, market and policy influences on energy culture. We used social network analysis to identify the most common sources of external influence on householder choices to adopt more efficient technologies. All of these different sources of insight were linked though the framework, which supported an integrative approach across the team, learning from each other’s findings and contributing to a holistic understanding of household energy cultures in the New Zealand context (Barton et al., 2013 ; Stephenson et al., 2010 ).

The framework is thus helpful in underpinning the design of research as a single- or multi-method project by an individual researcher, or a multi-method multidisciplinary research programme by a team. It can be used proactively to design research and analyse the findings, or used retrospectively to help analyse existing data from single or multiple sources. It is fruitful when used as a theory in its own right, and also when used in combination with other theories.

Using the Cultures Framework as a Meta-Theoretical Framing

As these examples have shown, research using the cultures framework is not confined to particular methods, and neither is it confined to any particular theoretical or disciplinary perspective. In this sense, the framework offers a meta-theoretical set of universal elements, and leaves it to the researcher to determine which theories and methodologies are best used to examine them. Rau et al. ( 2020 ) describe the advantages of the framework thus:

The benefits of using the [cultures framework] to organise the empirical material and findings of this interdisciplinary energy research were considerable, especially given its focus on the multi-method investigation of a small number of households. Its relative simplicity, easy-to-understand terminology and focus on both social and material aspects of energy use made it an ideal tool for fusing insights from the social sciences, engineering and architecture. At the same time, [the framework] was capable of connecting a higher-order theoretical approach (energy cultures) to concrete empirical energy-related outcomes. (p. 10)

While many studies use the cultures framework as a framing theory in its own right, it is at the same time an organising framework that enables multiple methods, theories and disciplines to contribute to an understanding of culture in relation to sustainability. Studies using the cultures framework to date have drawn from complementary explanatory theories as diverse as sociological theories of agency, structure, institutions and practice, theories of power and gender, behavioural theories, socio-technical systems theories, consumer psychology, economic theories, the multi-level perspective and, of course, theories of culture. Generally, these are used to inform analysis of an aspect of the cultures framework.

This flexibility is well explained by Ambrosio-Albalá et al. ( 2019 ) in their conclusion to a paper on public perceptions on distributed energy storage in the United Kingdom:

… we find that the framework functions as a useful heuristic, allowing us to organise and reflect on a wide range of factors in a way that is more inclusive than a psychology-only perspective. The idea of there being multiple possible cultures in relation to energy use – and the observation of these at different scales – also helps to stimulate thinking on further research directions in terms of how different households, demographic segments, nationalities and entities may differ in terms of the nexus of norms, attitudes, behaviours or practices and material experiences. These cultures will likely need different types of communication, informational, institutional and contractual offers, given likely differing responses. A further value of the ECF [energy cultures framework] – regarding which we would concur with its originators – lies in its comprehensibility for non-social scientists. For more specialised and narrowly specified forms of analysis, we would defer to the psychological and sociological perspectives that the ECF draws upon. (p. 149)

There are many under-explored possibilities for the use of other theories and bodies of knowledge to help explore aspects of culture in relation to sustainability. For example, in relation to the theory of structuration, culture works both to replicate social life and as a creative force for change. The framework positions culture as constrained and shaped by structure, while simultaneously situating more powerful cultures as part of structure. Despite these constraints on their agency, cultural actors can and do make independent choices and can collectively reshape more powerful structures and cultures. This interplay (and the conceptual overlap of culture and structure) invites further exploration in both a theoretical and applied sense, particularly in the context of the implications for sustainability transitions.  

Conceptual fields that underpinned the development of the cultures framework could be drawn from more extensively, including lifestyles literatures, socio-technical studies, actor network theory, systems approaches, and sociological and anthropological theories of culture. For example, social practice theory can help illuminate aspects of the inner elements of the framework, with a focus on habitual actions. Theories of power and justice can help elaborate on the reasons for limitations in agency and choice that are imposed by those outside the agency boundary. Socio-technical systems theories can assist in exploring the relationships between actors’ material items and their activities. Theories of gender can help explores difference in cultural meaning, gender equity and gender leadership in sustainability outcomes. In all of these ways and more, the framework can offer a meta-theoretical structure for deeper analysis depending on the inclinations and interests of the researcher.

Further Contributions From Cultural Theory

A further untapped potential lies in the application of cultural theories more generally to questions of sustainability. Cultural theory is a vast field that I could only sketch out lightly in Chapters 2 and 3 . There I discussed divergences and similarities across cultural theories and identified nine main clusters of perspectives on culture. I believe that each of these perspectives on culture can make an important contribution to research for a more sustainable future.

Culture-as-nature is the oldest of the nine perspectives. It is mostly overlooked by dominant ideologies, and yet its endurance offers the most hope. Culture-as-nature reflects many Indigenous perspectives that defy the intellectual separation of human society and natural systems. Culture-as-nature recognises our utter dependence on the natural world. The most powerful expressions of culture-as-nature continue to come from Indigenous peoples, although recent years have seen an increasingly strong voice from Western scholars (e.g. Haraway, 2016 ; Plumwood, 2005 ; Tsing et al., 2017 ). Culture-as-nature reinforces the indivisibility of human existence from nature and the responsibilities of human societies to maintain the integrity of natural systems. It also breaks down the barriers of cultural membership. Natural features are actors in culture: mountains and creatures are family members, trees communicate, rivers are people; they are all cultural members with agency. Many of the Indigenous societies of the world offer principles, values, practices, knowledges and worldviews that are crucial for a sustainable future (Artelle et al., 2018 ; Mazzocchi, 2020 ; Watene & Yap, 2015 ; Waldmüller et al., 2022 ; Yunkaporta, 2020 ).

Culture-as-nurture reflects the original meaning of culture in old English, referring to processes of husbandry—the careful tending of crops and animals. For the sustainability crisis, we are relearning the urgency of nurturing all life forms and regenerating natural systems. As well as reinforcing the importance of healthy natural systems and food production, culture-as-nurture can be further interpreted as the re-grounding of communities in caring for place, and reviving the spiritual roots of agriculture (Bisht & Rana, 2020 ; van den Berg et al., 2018 ). Urban agriculture or community gardens similarly reconnect people to the practices and rhythms of caring for nature, along with the sharing of food and strengthening a sense of community (Sumner et al., 2011 ). Culture-as-nurture reflects the ways in which we must re-learn practices of caring for nature, and how caring for nature aligns with caring for each other.

The original sense of culture-as-progress was the process of human development towards a so-called civilised state that reflected certain Western ideals of art and behaviours. Although it is now repellent and largely obsolete in this original sense, the idea of ‘progress’ can be reconfigured to refer to cultural journeys towards sustainability. Culture-as-progress in this sense can recognise the many cultural configurations that already have sustainable outcomes. It invites investigations of factors that underpin the relative sustainability of one culture compared to another (Buenstorf & Cordes, 2008 ; Minton et al., 2018 ) and the application of cultural evolution concepts to sustainability challenges (Brooks et al., 2018 ). A practical application of this in the world of business is the concept of energy culture ‘maturity’ and evaluation methods to assess such progress (Soorige et al., 2022 ). If the concept of progress is applied to outcomes rather than to cultural characteristics in themselves, this removes the suggestion that certain forms of cultural ensemble are better than others. Instead, a sustainable future requires a multitude of sustainable cultural ensembles specific to people and place, at a multitude of scales.

Culture is still commonly used to refer to works and practices of artistic and intellectual activity. In this sense, culture-as-product plays an important role as a cultural vector in transmitting ideas, values and possibilities. For the sustainability transition, creative works will play a critical role in challenging systems, institutions and practices that are destroying natural systems and demeaning humanity, as well as offering inspiration for alternate futures. Cultural products have the potential to convey different understandings, such as about the world’s ecological limits, actions for sustainability and new perspectives of the future (Curtis et al., 2014 ). This is already a strong theme in art and performance (Galafassi et al., 2018 ; Kagan, 2019 ) but could play an even stronger role in helping shape awareness and collective visioning for a sustainable future.

Culture-as-lifeways draws originally from anthropological studies of the distinctive way of life of a group of people. From a sustainability perspective, this concept can be redirected from studying the ways of life as a focus in their own right, to looking at the relationship between ways of life and the sustainability outcomes. From a research perspective, it encourages work that explores the variety of ways that people already live sustainably—for example, differences between ways of life in the global north and global south (Hayward & Roy, 2019 ), as well as how group or community ways of life can be re-oriented towards more sustainable consequences (Brightman & Lewis, 2017 ).

Culture-as-meaning focuses on the shared meanings and symbolisms of cultural objects such as text, discourse and possessions. For the sustainability challenge, culture-as-meaning can help reveal the ways in which symbolism can work for or against sustainable outcomes. Theories of cultural meaning could be applied to the analysis of how unsustainability is inherent in dominant rhetoric, text and discourse (e.g. Sturgeon, 2009 ), and the ways in which new meanings are being forged as part of cultural transformations (e.g. Hammond, 2019 ). Other examples of work using culture-as-meaning include a study of how the term ‘sustainable development’ is constructed in the disclosures of Finnish-listed companies (Laine, 2005 ), how the media interprets sustainability (Fischer et al., 2017 ) and the importance of symbolism in marketing for the sustainability transition (Kumar et al., 2012 ; Sheth & Parvatiyar, 2021 ).

Culture-as-structure is interested in the underlying rules by which social systems are reproduced—the cultural codes of social life. Culture-as-structure, as embedded in institutions and discourses, is intimately tied with questions of power and influence regardless of intent (Blythe et al., 2018 ). Drawing on this literature can help identify and challenge ideologies, assumptions and rules that replicate unsustainability. Relevant studies using culture-as-structure include how neoliberal ideology operates through sustainability discourses (Jacobsson, 2019 ) and the mental structures in which finance actors are embedded (Lagoarde-Segot & Paranque, 2018 ).

Culture-as-practice studies the bodily practices that produce and replicate social life, and the intimate linkages between routines, objects, meanings and competencies. This field of work can contribute to questions of how to alter practices, or develop new practices that support sustainability. Practice theory has already been widely applied to how to achieve less resource-intensive habits and routines, including how the reproduction of social practice can sustain inequality and injustice (Shove & Spurling, 2013 ) and to provide insights on collective action for social change (Welch & Yates, 2018 ).

Culture-as-purpose reflects bodies of work that focus on how to change the culture of organisations or groups of actors intentionally. Work in the field of organisational culture includes how to deliberately create more sustainable organisations (Galpin et al., 2015 ; Obal et al., 2020 ). Education for sustainability is another major field working on purposeful culture change, building on and extending educational theories (Huckle & Sterling, 1996 ) and education’s transformative potential (Filho et al., 2018 ). This includes using practices of dance and music to develop pro-social behaviours that align with sustainability goals (Bojner et al., 2022 ).

All nine conceptualisations of culture thus make important contributions to understanding the role of culture in sustainability. It is evident that at least some academics in each of these fields are applying relevant theories and methodologies to sustainability questions, but it appears to be occurring in a fragmented way with different bodies of knowledge scarcely acknowledging each other. Even if there is a ramping up of scholarly contributions on culture and sustainability, there is the risk that the slipperiness of culture as a concept will continue to handicap the use of research findings by practitioners and policymakers. If culture continues to be presented as if each part of the elephant is the full elephant, and the only true elephant, its ongoing indeterminacy will continue to confuse potential research users and dilute the effectiveness of scholarly contributions.

The cultures framework could help here by ‘locating’ these different approaches to culture and their contribution to sustainability challenges. Each of the nine clusters of meaning can offer insights for certain features or qualities of the framework. Using its meta framing, culture-as-purpose focuses on how to purposefully initiate cultural change and achieve better sustainability outcomes. Culture-as-practice focuses on routines as a subset of activities, emphasising how they cannot be understood in isolation from the objects, competencies and meanings associated with them. Culture-as-structure helps explore entrenched external influences or higher-order cultures that use their power to shape the cultural ensembles of less powerful actors. Culture-as-meaning focuses on the meanings and symbolism of activities and objects and can help illuminate the mechanisms of cultural vectors.

Culture-as-lifeways scholarship can help in studying how culture is learned, the dynamics of the core elements of culture, processes of replication or change, and the heterogeneity of cultural ensembles. In the arts, culture-as-product scholarship can help enhance the role of creative activities and products in building a more sustainable future. Academic fields that align with culture-as-progress focus more on the two-ended arrow that links cultural ensembles and outcomes and can help with studies on the many journeys involved in achieving cultures that touch lightly on the earth.

Culture-as-nurture scholarship contributes to the adoption of more nurturing food-production activities that also enhance social and environmental outcomes. Culture-as-nature opens the door to entirely different worldviews and knowledge systems regarding humans’ relationships with the natural world. Importantly, it extends cultural actors to include non-human life forms, spiritual beings and landscape features. In this way, it offers ways of understanding the sustainability transition as a process of restoring health and vitality to all living things and the natural systems that support them.

The cultures framework can thus work as an integrative heuristic, indicating how different interpretations of culture all contribute in important ways to a fuller understanding of the role of culture in sustainability. Used in this way, the framework can help reveal the complementary roles of these diverse approaches to practitioners and non-cultural academics. It can also indicate to researchers where it might be useful to reach back to the original bodies of cultural theory and bodies of knowledge to help illuminate particular aspects of the overall ‘elephant of culture’. In this way, cultural scholarship can be used more comprehensively and systematically to support sustainability transitions, and the slipperiness of culture is somewhat reduced.

As this chapter has demonstrated, there is no ‘right way’ to do research with the cultures framework. It is a set of highly generalised variables and their relationships, which can be explored using a wide range of research methods and theories. Researchers can choose which features within the general variables to focus on and can apply the framework at any scale and to any set of actors. The framework can be used as a framing theory in its own right, or alternatively (or simultaneously) can operate as an integrating frame for interdisciplinary, multi-method research, or as a meta-theoretical framing of the complex field of culture and sustainability. Either on its own or in combination with other frameworks and theories, the cultures framework thus offers ontological and epistemological inclusiveness for transdisciplinary research agendas.

There is an urgent need for a better understanding of the role of culture in the sustainability crisis and how to transform the unsustainable cultures that are inherent in most systems of production and consumption. Technologies alone will not achieve a net-zero world by 2050, or turn around our devastating losses of biodiversity, or enable equitable access to energy for families in developing countries. It will take more than simply changes in behaviour. It will require fundamental changes in the motivators, activities and materialities of people and organisations at every scale. We can learn much from cultures that are already sustainable or are on journeys of transition, but the biggest challenge is how to achieve transformational cultural change, at scale, and with unprecedented speed. To that end, research is desperately needed to improve our understanding of processes of cultural change, and particularly to understand how powerful meta-cultures can be destabilised and their unsustainable ideologies and institutions transformed.

Although the framework has already been used in a wide variety of fields, it has the potential to do much more to assist with journeys of transition. We need to know more about how sustainable cultures develop and endure, a better understanding of the dynamics of cultural change and the role of vectors in cultural learning, as well as processes of cultural expansion and collectivisation. More research is needed on the implications of actors having multiple cultural ensembles in different aspects of their life (e.g. the interplay between their food culture, mobility culture and household energy culture). Researchers could fruitfully explore how these overlapping cultures influence and shape each other, or divergences between cultural settings at home and at work. We need to better understand how cultural transformations can be enabled, and the roles that culture will need to play to achieve sustainability transitions. And while some research using the framework has explored issues of power and justice, there is much more to be done.

Cultural research can work at two levels in this quest for transformation. On the one hand, cultures are unique as to membership and cultural features. Researchers can draw conclusions regarding specific cultural ensembles and their sustainability outcomes, and can make recommendations for change initiatives. However, these will usually only be relevant to the case in question. On the other hand, as more studies are undertaken, we can start to build up generalisable understandings of cultural dynamics as they relate to sustainability. Across multiple studies, the research community can develop a better picture of universal cultural processes and effective  change interventions.

Finally, although this chapter is about culture and sustainability, the research approach I describe in this chapter could be used in other fields of inquiry. It was developed for sustainability-related research and has mainly been used for that purpose, but it could equally be applied to investigations of culture for any other reason, and in relation to any other outcome. But my hope is that it will continue to be primarily used for research that helps achieve a just transition to a sustainable future.

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Exploring Global Cultures: Topics for Your Next Cultural Research Paper

Table of contents

• 1 How to Choose a Cultural Research Topic to Write About 
• 2.1 Cultural Diversity Research Topics
• 2.2 Anthropology Research Topics
• 2.3 Subculture Study Ideas
• 2.4 Heritage and Preservation Studies
• 2.5 Identity Research Topics
• 2.6 Socio-Cultural Essay Ideas
• 2.7 Psychology Research Topics
• 2.8 Western Civilization Essay Ideas
• 2.9 Cross-Cultural Study Topics
• 2.10 Stereotypes and Misconceptions Studies

Cultural research papers are a gateway to exploring the intricate web of human societies and their diverse practices. Such papers cover a broad range of cultural analysis topics, each offering a unique perspective on how communities shape and are shaped by their civilizational norms and values. 

Whether it’s delving into the realms of cultural diversity topics, examining cross-cultural psychological patterns, or investigating specific phenomena, these subjects provide a rich ground for academic inquiry. 

Research topics on culture not only deepen our understanding of human interactions and beliefs but also highlight the importance of nuances in shaping societal dynamics. Engaging and informative, they encourage a deeper exploration of the ethical fabric that weaves together the global human experience, making them both fascinating and essential for a comprehensive understanding of the world.

How to Choose a Cultural Research Topic to Write About 

Choosing a topic for a cultural research paper is a strategic and thoughtful process. Start by identifying your interests in this vast field. Are you fascinated by cross cultural psychology research topics, intrigued by diverse communication practices, or curious about specific cultural phenomenon topics? Pinpointing an area that genuinely interests you is crucial for sustained engagement with your research.

• Consider the scope of your chosen topic. Aim for a balance, selecting a specific subject to be manageable yet broad enough to provide ample material for exploration. For instance, within the realm of cultural psychology research topics, you might focus on how different civilizations perceive mental health.
• Ensure there is sufficient information available. Conduct preliminary research to confirm the availability of resources and data. This step is vital, especially for topics like social analysis or cultural diversity, where empirical evidence is key to a robust paper.
• Think about the relevance and originality of your topic. Strive to contribute new insights or perspectives, particularly in fields like anthropology, where there is always room for fresh interpretations of ethical phenomena.
• Lastly, consider the academic and societal implications of your topic. Select a subject that not only adds value to academic discourse but also has the potential to enlighten and inform broader societal understanding, like studies in diversity or society communication practices. This approach ensures that your work is intellectually fulfilling and socially impactful.

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List of Cultural Research Paper Topics

Embarking on an ethnic research journey opens doors to a world of interesting anthropology research topics. From the complicated field of cross-cultural psychology to the beautiful tapestry of diversity, these cultural topics for research paper cover various areas related to anthropology, communication, and social phenomena, giving you a wide range of interesting culture to research.

Cultural Diversity Research Topics

• Language’s Role in Shaping Identity Across Cultures
• Norms Comparison: Eastern and Western Societies
• Indigenous Civilizations’ Response to Globalization
• Diversity in the Workplace: Opportunities and Challenges
• Media Representation of Varied Societies and its Effects
• Multiculturalism’s Evolution in Urban Environments
• Educational Systems’ Approach to Global Diversity
• Music’s Influence on Ethnical Integration
• Culinary Traditions as a Reflection of Societal Diversity
• Festivals as a Platform for Promoting Diversity

Anthropology Research Topics

• Varied Traditions of Healing in Global Civilizations
• Marriage Customs Across Different Societies
• Kinship and Family Structures: An Anthropological View
• Societal Responses to Natural Disasters: A Comparative Study
• Local Cultures’ Adaptation to Tourism
• Birth and Death Rituals in Diverse Societies
• Religion: Beliefs and Practices Worldwide
• Technology’s Impact on Traditional Societal Roles
• Non-Western Perspectives on Time
• Clothing and Adornment from an Anthropological Lens

Subculture Study Ideas

• Hip-Hop’s Social Influence and Evolution
• Cyberpunk: Blending Technology and Aesthetic
• Skateboarding’s Cultural Journey
• LGBTQ+ Community’s Internal Subcultures
• Gaming’s Social and Cultural Impact
• Punk Fashion and Identity
• Coffee Culture’s Shift from Niche to Mainstream
• Teen Subcultures in the Age of Social Media
• Green Movements: Environmental Awareness as a Subculture
• Fitness Trends and Digital Age Subcultures

Heritage and Preservation Studies

• Ancient Manuscripts’ Digitization for Heritage Preservation
• Museums’ Role in Protecting Ethnical Legacies
• Intangible Heritage Threats in the Modern Era
• Historic Sites’ Architectural Conservation
• War’s Effects on World Heritage
• Indigenous Languages and Oral Traditions’ Preservation
• Heritage Tourism: Balancing Benefits and Risks
• Legal Strategies for Heritage Protection
• Traditional Arts and Crafts Revival
• Post-Colonial Societies’ Heritage Perspectives

Identity Research Topics

• Diaspora’s Impact on Identity Formation
• Bicultural Existence in a Globalized Era
• Art’s Reflection of Societal Identity
• Language Loss and its Effect on Identity
• Social Media Influences on Youth Identity
• Fashion as a Cultural Expression Tool
• Gastronomy’s Role in Defining Societal Identity
• Race and Identity Intersections
• Second-Generation Immigrants’ Identity Challenges
• Popular Culture’s Influence on National Identity

Socio-Cultural Essay Ideas

• Bilingualism and Multilingualism’s Societal Effects
• Gender Roles: A Global Cultural Comparison
• Mass Migration’s Social Impact
• Social Hierarchies: A Global Cultural Analysis
• Global Economic Inequality’s Cultural Dimensions
• Social Media as a Cultural Change Agent
• Urbanization’s Societal Consequences
• Religion’s Influence on Socio-Cultural Norms
• Aging Populations and Societal Shifts
• Education’s Influence on Societal Values

Psychology Research Topics

• Superstitions’ Psychological Underpinnings in Various Societies
• Emotional Expression: A Cross-Cultural Study
• Decision-Making Influences Across Cultures
• Childhood Development in Diverse Environments
• Personality Shaping through Societal Norms
• Mental Health Approaches in Different Societies
• Immigrant Families and Acculturation Challenges
• Resolving Ethnical Conflicts: A Psychological Perspective
• Behavioral Norms’ Cultural Foundations
• Cultural Communication Practices Paper Proposal: Human Motivation from a Global Perspective

Western Civilization Essay Ideas

• The Renaissance’s Influence on Western Civilization
• Democracy’s Roots in Ancient Greece and Rome
• Industrial Revolution’s Societal Transformations
• Christianity’s Impact on Western Societies
• Philosophical Foundations of Modern Western Thought
• Enlightenment’s Role in Modernity Shaping
• Western Art Evolution from Baroque to Modernism
• Western Societies’ Ecological Footprint
• Colonial Legacy in Western History
• Science’s Progression in Western Context

Cross-Cultural Study Topics

• Work Ethic Comparisons Across Societies
• Effective Communication in Diverse Settings
• Leading in Multicultural Environments
• Love and Marriage: Global Insights
• Parenting Styles’ Ethnical Variations
• International Business Adaptations
• Health Practices: A Global View
• Educational Systems: International Comparisons
• Negotiation Styles in Diverse Contexts
• Eldercare Approaches in Different Civilizations

Stereotypes and Misconceptions Studies

• Hollywood’s Role in Perpetuating Stereotypes
• Racial Stereotypes’ Origins and Impacts
• Gender Assumptions in Societal Contexts
• Media’s Influence in Stereotype Formation
• Stereotypes in International Diplomacy
• Misconceptions’ Psychological Aspects
• Socioeconomic Assumptions in Urban Life
• Stereotyping in Educational Environments
• Youth Culture’s Battle with Stereotypes
• Society’s Age-Related Assumptions and Realities

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Cultural Research Paper Topics: Exploring Heritage and Society

Culture is interconnected and ever-changing. It influences how we think, behave, and interact with everything around us. It is also a significant source of variation, as various cultures have varying values, beliefs, and practices.

Understanding different cultures is more important than ever in today’s globalized world. Cultural research can aid in creating a more inclusive and tolerant society by bridging cultural divisions.

Through a range of cultural research paper themes, such as  pop culture essay topics , this article investigates the characteristics of human civilizations and diversity. These issues cover everything from the significance of culture in developing human identity to the influence of cultural variety on disagreements and partnerships.

How to Choose Research Paper Topics about Culture?

Culture is a vast and complex topic, so it can be difficult to choose a research paper topic that is both interesting and manageable.

Listed are a few tips for choosing research paper topics about culture:

• Consider your own interests

What aspects of culture are you most interested in? What do you know a lot about? Choosing a topic you are interested in will make the research process more enjoyable and rewarding.

• Consider your target audience.

Who is going to read your paper? What background in culture do they ask for? Choosing a topic that is intriguing and helpful to your readers will improve the quality of your paper.

• Conduct preliminary research .

Once you’ve developed a few concepts, perform some early research. This will assist you in selecting your topic and figuring out the sources you will use.

• Make it specific .

To what extent do you want the subject to go? A broader topic will allow you to examine more facets of culture, though it will also be more difficult to investigate.  

• Consult with your lecturer.

Talk to your professor if you need help deciding on a cultural research topic. They can assist you in filtering your alternatives and selecting the best topic for you.

List of Interesting Culture Topics to Write About

Culture is a diverse and intriguing subject that may be approached from various perspectives. There are several interesting cultural research topics to write about, ranging from multiple civilizations’ history to culture’s influence on the arts and media.

This list is an excellent place to begin if you’re looking for fascinating cultural research topics to write about.

Cultural Anthropology Research Topics

The study of human societies and their traditions is known as cultural anthropology. Cultural anthropology research subjects might range from the study of distinct civilizations to the study of cross-cultural comparisons. These subjects in anthropological perspectives go into the cultural practices, rites, and norms of multiple cultures across all nations worldwide. They may include studies on kinship systems, gender roles, religious ceremonies, language development, and cultural adaptation.

Some examples of cultural research topics include;

• Cultural Adaptation and Assimilation of Immigrants in Modern Society
• The Impact of Globalization on Indigenous Cultures and Traditional Knowledge Systems
• Cultural Expressions and Identity Formation Among Marginalized Communities
• The Role of Rituals and Ceremonies in Shaping Cultural Beliefs and Practices
• Cross-Cultural Perspectives on Gender Roles and Sexuality
• Cultural Responses to Environmental Change and Sustainability
• The Influence of Technology on Cultural Performance and Communication Process
• Cultural Perspectives on Healthcare Practices and Healing Rituals
• Cultural Preservation and the Role of Museums in Safeguarding Intangible Heritage
• Comparative Study of Cultural Practices Related to Death and Mourning

Cultural Psychology Research Paper Topics

Cultural psychology research paper topics focus on the intersection between culture and human psychology. These subjects explore how cultural factors shape our thoughts, emotions, behaviors, and mental processes.

By examining these topics, researchers aim to unravel the complex interplay between cultural psychology, shedding light on the cultural influences that shape our individual and collective experiences.

At times, students get overwhelmed with the workload at hand and often ask – who can  write my papers  just how I want them? The answer is yes. There are professional writing services that provide this help.

Cultural research topics in this section are:

• Cultural Variations in Cognitive Processes and Perception
• The Influence of Culture on Personality Development and Individual Differences
• Cross-Cultural Perspectives on Emotion Expression and Regulation
• Cultural Factors in the Development and Treatment of Mental Disorders
• Cultural Influences on Parenting Styles and Child Development
• Cultural Variations in Moral Reasoning and Ethical Decision-Making
• The Role of Cultural Narcissism in Shaping Attitudes and Behaviors Towards Authority
• Cultural Differences in Motivation and Achievement
• The Impact of Acculturation and Bicultural Identity on Psychological Well-Being
• Cultural Factors in Intergroup Relations and Prejudice

Socio-Cultural Essay Topics

Socio-cultural topics explore a wide range of issues related to society and culture. The essays in the socio-cultural context examine the relationship between humanity and culture. Research topics in this field can range from the study of social institutions to the norms and values of cultural studies.

Among the possible cultural research topics are:

• The Societal Fabrication of Race and Its Consequences for Identity and Inequality
• Mass Media’s Involvement in Creating Cultural Norms and Values
• Perspectives on Economic Disparity and Hardship From a Socio-Cultural Perspective
• Social Media’s Influence on Interpersonal Relationships and Self-Esteem
• The Impact of Cultural Diversity on Academic Success in Schooling
• Socio-Cultural Variables Influence Health Inequalities and Access to Healthcare
• Religious Beliefs Influence Societal Attitudes and Behaviors
• Migration and Refugee Integration Have Socio-Cultural Elements
• Cultural Phenomena Influence Environmental Views and Sustainable Practices
• Race, Class, and Gender Intersectionality in Human Beings’ Socioeconomic Inequity

Cultural Diversity Research Topics

This area of study may investigate the impact of cultural diversity on healthcare inequalities, the role of cultural characteristics on psychological outcomes, or the efficacy of ethnically customized therapies in enhancing patient care and health results.

To get your cultural research papers crafted to your requirements, Edusson gets the hassle out of writing essays from start to end.

Being aware of various cultural aspects is essential for establishing inclusive and equitable healthcare systems that meet the specific requirements of varied groups.

The following are some cultural research topics to write on:

• The Effect of Cultural Diversity on Workplace Efficiency and Fulfillment
• The Impact of Ethnic Diversity on the Medical Industry and How Patients Respond
• Investigating the Importance of Cultural Phenomenon in Developing the Education System and Practices
• Cultural Diversity’s Impact on Team Dynamics and Collaboration in a Social Organization
• Cultural Diversity and Its Consequences for International Advertising Tactics
• The Link Between Cultural Diversity and Technological Innovation
• Understanding the Upsides and Challenges of Cultural Diversity in a Multicultural Society
• The Influence of Cultural Competence on Conflict Resolution and Peacebuilding Initiatives
• Multicultural Diversity’s Impact on National Identity and Social and Emotional Development
• Investigating and Preserving Native Culture Uniqueness

Cross-Cultural Research Paper Topics

Intercultural studies compare and analyze different cultures and their effects on many parts of society. Exploring disparities in healthcare beliefs and practices, investigating the efficacy of cross-cultural perspectives in hospital settings, or researching the influence of globalization on cultural practices and medical behaviors are all possible research subjects.

Cultural studies facilitate competence in healthcare and ensure culturally sensitive and effective care to individuals from a particular culture.

Writing a very good research paper is tedious, so you may need to find the  best research paper topics  to get ideas flowing.

Cultural research paper topics in this category include:

• A Comparative Analysis of Cross-Cultural Business Communication Across World Culture
• Cross-Cultural Communication Challenges and Strategies in International Business Negotiations
• The Impact of Cross-Cultural Interactions on Intercultural Competence Development
• Economic Classes in Parenting Styles and Their Effects on Child Development
• Cross-Cultural Perspectives on Sexually Transmitted Diseases Stigma and Its Implications for Non-verbal Communication
• Exploring Cross-Cultural Fashion Trends Variations and Experiences of Beauty and Body Image
• The Influence of Culture on Attitudes and Behaviors Related to Environmental Sustainability
• Cross-Cultural Perspectives on Aging and Elder Care Practices
• Understanding Cross-Cultural Psychology in Ethical Decision-Making Processes
• The Role of Western Culture History in Shaping Attitudes Towards Gender and Sexuality

Art Culture Research Topics for Assignments

The intersection of art and culture provides a rich landscape for research. Research in this field contributes to our understanding of art’s therapeutic and cultural significance and highlights its potential as a tool for healing, self-expression, and cultural values.

Potential cultural research paper topics are:

• The Influence of Ancient Art on Contemporary Artistic Expressions
• Exploring the Cultural Significance of Street Art and Graffiti in Urban Environments
• Female Culture in Art Throughout Ancient Britain
• Art as a Form of Cultural Resistance and Social Activism
• Analyzing How Traditional Food Reflects the Cultural Heritage
• Cultural Appropriation Versus Cultural Appreciation in Art and Its Ethical Implications
• The Intersection of Art and Technology: Exploring Digital Art and Its Cultural Implications
• The Importance of Museums in Maintaining and Displaying Various Works of Art and Cultural Artifacts
• The Study of How Art Reflects and Affects the Stories of Culture
• Therapeutic Art as a Technique for Boosting Mental Health and Well-Being Across Different Cultures

Good Essay Topics about Culture

Culture is an enthralling and varied part of human society. Cultural essay topics include customs, cultural interchange, cultural identity, cultural appropriation, and cultural preservation. Exploring these themes provides a more in-depth understanding of the values, religious practices, cultural clashes, and conventions that define different cultures.

The following are the best cultural studies selections in this category:

• Globalization’s Influence on Indigenous Cultural Practices
• A Critical Appraisal of Cultural Theft
• The Impact of Cultural Background on Individual Growth
• Language’s Impact on Cultural Norms and Values
• Issues and Benefits of Preserving Cultural Diversity in the Workplace
• A Systematic Examination of Gender Roles and Cultural Expectations
• Protection of Historic Resources in the Face of the Modern World
• Finding an Equilibrium Between Cultural Integration and Maintaining Culture
• Gender Stereotypes and Their Effects on Intercultural Relationships
• The Influence of Pop Culture on Societal Norms and Values

Topics on Globalization

The process of globalization has changed the global culture into an interlinked village. Globalization essay themes can cover a wide range of issues, including its influence on economics, politics, technology, interpersonal relationships, and cultural interaction in modern society.

Evaluating globalization’s good and bad consequences, investigating its place in influencing global politics, and debating the difficulties and possibilities it brings may provide significant insights into the complex dynamics of our increasingly linked world and mitigate cultural ignorance.

Among the more intriguing cultural research topics include:

• The Impact of Economic Globalisation on Developing Countries
• Viral Diseases Spread and Globalization
• Multinational Corporations’ Role in Globalization
• The Impact of Globalisation on Isolated Communities
• Cultural Diversity Versus Globalization in a Modern Society
• Environmental Sustainability and Globalization
• Globalization and Trends of Labor Migration
• Globalization’s Political Implications
• The Age of Technology and Its Impact on Globalization
• The Growth of Global Governing Institutions Is a Result of Globalization

American Culture Research Paper Topics

The richness and diversity of American culture make it an appealing subject for study. American culture research paper topics may include the global impact of American pop culture, the development, and history of American cuisine, the representation of American identity in movies and novels, the impact of immigration on modern United States society, or the part of Christian traditions in defining American and African culture.

Popular cultural research topics include:

• American Political Culture’s Development
• The Influence of Hollywood on American Culture
• The Role of Mass Media in Shaping American Societal Norms
• The Impact of Immigration on American Cultural Diversity
• American Exceptionalism: Myth or Reality?
• American Pop Culture and Its Consequences
• The History and Significance of Jazz Music in African Culture
• The Portrayal of Race and Ethnicity in American Pop Culture
• The Influence of American Literature on National Identity
• The American Dream: Its Changing Meaning and Societal Implications

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Culture Research Paper

This sample culture research paper features: 6400 words (approx. 22 pages), an outline, and a bibliography with 31 sources. Browse other research paper examples for more inspiration. If you need a thorough research paper written according to all the academic standards, you can always turn to our experienced writers for help. This is how your paper can get an A! Feel free to contact our writing service for professional assistance. We offer high-quality assignments for reasonable rates.

While disputes surrounding the concept of culture reflect valid ideological disagreements, they are sometimes obscured by misunderstanding; not only is the term commonly used to signify vastly different concepts, but it is also frequently defined in vague and unclear terms (if explicitly defined at all). This research paper tries to clarify the notion by tracking its usage from its earliest applications to its place in contemporary anthropological discourse. First, the concept’s origins and evolution are examined, with a special focus on its development in American anthropology. The modern notion of culture as meanings and symbols is then investigated in depth. Finally, significant criticisms of the concept and responses to those criticisms are provided.

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Get 10% off with 24start discount code, introduction, cultural relativism, culture and the individual, culture as meaning, culture as symbolic systems, the nature of symbols, the pervasiveness of symbols, methodological implications, social anthropology, postmodern anthropology.

• Bibliography

Culture is one of the most complicated academic concepts now in use. It is defined and implemented in numerous and frequently contradictory ways, and there are considerable disagreements within academic disciplines regarding the fundamental nature of human social life and the appropriate method for studying it. For anthropologists, culture typically refers to symbolic systems of ideas, values, and shared understandings that give meaning and comprehension to the world for a certain group of people. While these systems, which provide the foundation for such fundamental concepts as food and kinship and even influence how individuals experience time, space, and other aspects of reality, may appear to their adherents to be natural and objective, they are, in fact, variable, socially accepted models. In order to find order and significance in a world devoid of both, humans must create their own models.

Ironically, just as the anthropological idea of culture has achieved enormous traction in popular culture and fields such as law and politics, it has come under fire from within the study of anthropology. Some anthropologists assert that the concept of culture oversimplifies and stereotypically treats entire societies as isolated and homogeneous, while downplaying individuality and diversity of thought. Others argue, however, that the notion has never involved such assumptions, and that culture is merely a useful method to consider the ideas and shared understandings that enable humans to comprehend their reality.

The Evolution of the Concept of Culture

Both the literal sense of cultivation (as in “of a crop”) and the metaphorical sense of self-improvement (the “cultivation of the mind”) are derived from the Latin term cultura , from which the English word culture derives. This phrase was frequently used in 18th-century England to describe to the improvement of one’s character through the refinement of judgment, taste, and intelligence; and, by extension, to those activities believed to express and maintain this sophistication (Williams, 1983). This basic connotation underlies the most prevalent popular use of the term today, which designates a specific segment of society (such as theater and art) as cultural to the exclusion of others.

The anthropological idea of culture entered the English language via a less direct route, first going through German as the philosophical concept kultur . Kultur was also derived from the concept of cultivation, but shortly thereafter began to evolve in opposition to the French term civilisation as the philosophical traditions of the two countries came into conflict. Civilization was associated with the French Enlightenment and the notion that civilization evolved from a primitive state characterized by ignorance and barbarism toward universal ideals in science, secularism, and rational thought. The “national character” of a people has come to be symbolized by the term Kultur , which has come to represent local and personal notions such as religion and tradition. In 1871, British anthropologist Edward Tylor blended parts of both notions to define culture as “that complex whole that includes knowledge, belief, art, law, morals, custom, and any other skills and practices acquired by man as a member of society” (as cited in Kroeber & Kluckhohn, 1952, p. 81). This is largely regarded as the first formal anthropological definition of the term, as it introduced the concept of culture as a taught, shared, and inclusive framework that encompasses practically every aspect of human social life.

Although Edward Tylor’s definition was innovative, it missed a crucial part of the original German notion that would later become a central aspect of the anthropological concept of culture. Tylor was a cultural evolutionist; he believed that, given sufficient time and favorable conditions, societies evolved toward increasingly superior forms. Consequently, he viewed 19th-century England to be the apex of human civilisation and all other societies (particularly those outside of Western Europe and North America) to be less evolved and fundamentally inferior. Franz Boas, a German-American scientist often considered as the creator of cultural anthropology, was one of the first to challenge the evolutionist perspective. Boas considered the concepts of cultural evolutionism to be unscientific, and he contested the fundamental premise that the prevalence of identical activities across nations inevitably indicates their shared evolutionary origin. He presented counterexamples in which substantially identical cultural institutions arose in various contexts for notably distinct reasons. Boas (1940/1995), using a historical and comparative methodology, contended that society did not follow a linear progression toward a single ideal form, but rather moved in many ways in response to fluid historical conditions.

Importantly, Boas maintained that individuals experience reality differently depending on the cultural context in which they are nurtured; he stated that “the seeing eye is the organ of tradition” (1940/1995). This resulted in the conclusion that a community’s ideals and practices could only be comprehended in relation to how its members experienced and envisioned their reality (1889). Boas reasoned that if cultural patterns of perception and evaluation were the result of socialization, then their adherence must be based on emotions and unconscious attachment rather than rational or practical evaluations of their value or efficacy. Therefore, he decided that any attempt to rank or compare the customs of other communities would be absurd.

Cultural evolutionists erred by considering their own culturally developed concepts and perceptions to be universally applicable and uniquely valid. Boas used the analysis of voice sounds as an example of why this is a dangerous activity. A person inexperienced with the sounds employed in a specific language will frequently perceive those sounds differently than a native speaker, for example, by failing to distinguish between two sounds that are functionally equivalent in his or her own language. The Japanese language, for instance, does not differentiate between the English /r/ and /1/ sounds, and unless exposed to English at a young age, native Japanese speakers tend to wrongly regard those sounds as identical. This tendency led to an unpleasant (though hilarious) incident in which early cultural evolutionists misunderstood the speech sounds of an indigenous American language and deemed it inferior due to what they erroneously perceived to be the absence of a stable phonemic system.

According to Edward Sapir and Benjamin Lee Whorf’s “linguistic relativity hypothesis,” the principle of relativism extends to linguistic meaning systems. Sapir and Whorf believed that the language a person speaks affects not only their ability to communicate, but also how they perceive what would otherwise appear to be fundamental components of reality. Thus, Sapir concluded that learning a language is equivalent to learning the “world.” Whorf drew on his expertise as a fire teacher to demonstrate how the connotation of a word like empty could cause individuals to behave irresponsibly around spent gasoline drums containing hazardous fumes. Subsequent research in this subject has revealed language implications on aspects such as color vision and spatial orientation, as well as on moral reasoning and other types of decision making. Whorf observed that the majority of linguistic categories are “covert,” or existing below conscious awareness; anthropologists Alfred Kroeber and Clyde Kluckhohn (1952) concluded that all cultural knowledge consists of both conscious and unconscious categories that “screen and distort” one’s conception of reality.

Although language analysis may provide the clearest example of relativism in action, the idea appears to apply to a wide variety of cultural phenomena. Not only do views, attitudes, and values vary significantly from one society to the next, but comparative study has demonstrated that people of different cultural groups can also have diverse emotional and physiological responses to stimuli. Many Americans, for instance, would feel disgust and possibly even nausea at the mere prospect of consuming live grubs. However, in many other communities, insects are regarded tasty, whilst the intake of onions and mushrooms is deemed repulsive.

As a result of this relativistic aspect, the concept of culture has been challenged for what is viewed as its role in undermining efforts to construct objective and universally binding principles for moral human action. Moreover, if it is illegitimate to compare distinct beliefs and behaviors, and if everything from nausea to the essence of existence is experienced via the lens of culture, then it becomes extremely challenging to argue in favor of objective, universal moral truth. However, as other theorists have argued, this does not necessarily imply that moral ideas are impossible. It simply means that in order for normative assertions to make meaning, they must be based on commonly held beliefs about the world. As with differing conceptions of the nature and significance of reality, the fact that conceptions of moral truth are unavoidably local and specific does not imply that they are irrational, invalid, or untenable.

An important question in anthropology is whether culture reflects its own level of analysis or whether it can be explained in terms of the thoughts and behaviors of individuals. Alfred Kroeber (1917), an eminent anthropologist and the first of Franz Boas’s several PhD students, believed that it was only a matter of time before culture established a “second level” once it was identified as a “distinctive product of men living in societies.” Kroeber referred to this tier as the superorganic . According to this perspective, the conduct of individuals combines to form a system governed by its own set of rules. In light of the fact that cultural phenomena are emergent aspects of this system, they demand their own degree of explanation. Thus, Kroeber claimed, anthropologists need not be concerned with individuals when dealing with culture; in fact, disregarding individuals could result in more comprehensive analysis.

Edward Sapir (1917), a student of Boas and one of the founders of linguistic anthropology, criticized the superorganic as reflecting “a social determinism amounting to religion.” Sapir argued that the idea regarded culture too much like a thing or a concrete entity, as opposed to an abstract concept, and allowed little room for individuals to behave according to their own free will. Sapir was also critical of the influential theories of Ruth Benedict (1934), an additional student of Boas who pushed the concept of civilizations as highly interwoven, “personality-laden” wholes. Benedict famously stated in a survey of three indigenous people from Melanesia and North America that each might be characterized by a certain personality type (the Dobu of Papua New Guinea, for example, were defined as “paranoid schizophrenic”). Famously, Sapir told his pupils that a culture cannot be “paranoid” in response to this attempt to apply psychological words to characterize entire cultures.

Sapir’s own thesis, outlined in a 1924 essay titled “Culture, Genuine and False,” viewed culture as the peculiar attitudes and methods of living that gave a people their unique position in the world. According to Sapir, a “genuine” culture is a harmonic, balanced, and healthy “spiritual organism.” Nonetheless, while this did necessitate a substantial degree of integration, a genuine culture was not merely “efficient”; that is, humans could not exist as simple gears in a machine. According to Sapir, culture and the individual are inseparable, as culture cannot sustain itself without individuals as “nuclei” and individuals cannot generate culture from nothing. Sapir’s solution and attempt to reconcile the contradictions he perceived in Benedict and others were fundamentally humanistic: The individual discovers a “mastery”—a profession that expresses his or her distinct particular skill while also being congruent with the will and desires of the other community members. Sapir was cautious to note, however, that the terms “culture” and “individual” could only be identified from an anthropologist’s perspective, as the individual himself could not cognitively detect such a distinction. The more humanistic aspects of Sapir’s theory were never widely accepted, but his thoughts on the relationship between culture and the individual foreshadowed numerous critiques present in “postmodern” anthropological theory (see “Criticisms of the Culture Concept”)

The Contemporary Concept: Culture as Meanings and Symbols

Later, some referred to Edward Tylor’s 1871 definition of culture as the “everything-is-culture” definition, as it encompassed not just knowledge, belief, and values, but also customs and conduct, as well as the miscellaneous category “other capabilities.” In the early 20th century, Franz Boas and his pupils gave the notion a more scientific appearance and included the key element of cultural relativism. The belief in the power of sorcery, for example, was culture, as was the ritual dance performed by the sorcerer and possibly even the artifacts made for the rite. Margaret Mead, a student of Boas and one of the most renowned cultural anthropologists in history, utilized a concept of culture that relied on the notion of a “complex of behavior.”

As part of a landmark work on the notion of culture, Kroeber and Kluckhohn (1952) were among the first to advocate excluding conduct from the concept of culture. Their conclusion was founded on the realization that human cognition and behavior is also influenced by causes other than culture. The issue with treating a specific conduct as part of culture was that it implied that the behavior belonged to or was a unique product of culture, while neglecting the important psychological, social, biological, and material components that also influence action. As with the other components, culture could not incorporate behavior because, as Kroeber and Kluckhohn pointed out, culture itself was a “pattern or design” abstracted from observable behavior — something that gave behavior meaning.

However, this concept does not imply that culture is identical to politics, economics, or any other aspect of human social life. Due to the fact that culture is not conduct but rather the beliefs and ideas that give behavior meaning, culture is a vital component of practically every area of social-scientific investigation. Even behaviors that look on the surface to be solely economic or political in nature, for example, are incomprehensible without a grasp of the specific cultural forms that make the contexts in which they occur reasonable and meaningful (see Sewell, 2005).

The contemporary concept of culture, then, focuses not only on behavior and artifacts as such, but also on what that behavior means and what those artifacts symbolize. For David Schneider (1868), an American anthropologist who helped found the approach known as “symbolic anthropology,” this meant that even behavioral norms should be excluded from cultural analysis. Schneider defined culture as a set of “definitions, premises, postulates, presumptions, propositions, and perceptions about the nature of the universe and man’s place in it” (p. 202), explaining that while “norms tell the actor how to play the scene, culture tells the actor how the scene is set and what it all means” (p. 203).

The importance placed on meaning in the modern concept of culture—not only for the anthropologist attempting to understand social life, but for the individual who lives it—is perhaps best accounted for in the writings of Clifford Geertz, whose influential ideas helped to redefine the discipline of anthropology in the late 20th century. Geertz (1973a) observed that humans are “unfinished animals,” set apart not just by our ability to learn, but by the astounding amount that we must learn in order to be able to function at the most basic level. Geertz attributed this to the fact that cultural evolution and biological evolution overlapped by millions of years in the phylogenetic development of the species, such that the human brain became utterly dependent on inherited systems of meaning. While our biological “hardware” might furnish us with basic capabilities, we must be socialized into specific social systems in order to use them. We cannot, for instance, simply speak; we must learn to speak English or Japanese or some other highly particular linguistic form. This accounts for the high degree of variability seen across human societies. As Geertz put it, “We all begin with the natural equipment to live a thousand kinds of life but end having lived only one” (p. 45), since the gap between what biology dictates and what we need to know in order to survive can only be filled with highly particular cultural forms. Without culture, then, humans would not revert to some basic and primary hunter-gatherer form, but would instead be “monstrosities” unable to accomplish even the simplest tasks (1973a, p. 49).

A central feature of the contemporary concept of culture is the emphasis placed on symbols. More than just providing the means to express and transmit cultural knowledge from person to person and generation to generation, symbols are seen as essential to the building of that knowledge in the first place. Anthropologists now tend to regard culture itself as a collection of symbolic systems, where the construction of cultural models and concepts relies on the unique properties of symbolic representation.

According to David Schneider (1968), a symbol is “anything that stands for something else.” The idea is that this “something else,” called the symbol’s referent, is not logically deducible from any characteristic of the symbol itself, but is associated with it purely on the basis of an agreement made by a social group. The word dog, for instance, really has nothing to do with the actual thing that speakers of English call a dog, but the connection is made because a group (the speakers of English) has agreed that a particular symbol (the word dog ) will stand for a particular referent (the domesticated descendants of the Asian red wolf). At first glance, this might seem unremarkable. But as Clifford Geertz (1973a) pointed out, while there are many instances in nature of “patterns for processes”—such as when a duckling learns a set of behaviors by imprinting on his mother, or when DNA issues “instructions” on how to build certain tissues—the capacity to represent objects and occurrences as they are is exceedingly rare, and probably unique to humans. Symbolic representation allows the users of symbolic systems to make reference to and reflect on things that are not actually present at the time, converting them into ideas that can be analyzed, manipulated, and combined with other such concepts in the medium of abstract thought.

Furthermore, symbolic reference involves much more than merely matching a word or other symbol to its counterpart in the “real world” of objects. In a famous example, Edward Sapir illustrated that when someone uses the word house in the general sense, they do not think of any one house, but of any and all houses that have ever existed or could possibly exist, as well as the set of collective beliefs, attitudes, and judgments associated with that class of objects. This is what is called a concept. Conceptual thought opens the door to the imaginative and productive capacities of the mind, allowing humans to do such extraordinary things as wonder about our place in the world, reflect on things that could have happened, but didn’t, and then lie about all of it. Closely related to the ability to lie is the ability to form conceptions of things pregnant with collective attitudes and value judgments that far exceed the natural or objective characteristics of the referents themselves. As French sociologist Émile Durkheim (1912/1995) emphasized in his landmark treatise on religion, symbols allow groups to focus their collective mental energy on concretized representations of social phenomena and give tangible expression to bundles of emotions and attitudes that might otherwise remain ineffable. As anthropologist Marshall Sahlins (1976) phrased it: “Men begin as men . . . precisely when they experience the world as a concept (symbolically)” (p. 142). It is for this reason that symbols are seen as the building blocks of culture.

Language is the most highly developed symbolic system, and the most common form in which cultural meanings are expressed. As the foremost means of “cutting up” the world into sensible and meaningful categories, language is virtually impossible to distinguish from culture, and it’s not surprising that the idiosyncrasies of its particular forms can have a powerful impact on how its speakers perceive reality (see earlier section, “Cultural Relativism”). But words are far from the only type of symbols used by humans. Clifford Geertz (1973b) regarded any “object, act, event, quality, or relation” as a potential symbol, and as it turns out, human social life is replete with organized systems of them. Geertz held up religion as a prototypical example, where acts, artifacts, relationships, and even people serve to symbolize the abstract concept of the supernatural and the beliefs and values associated with it (1973b). Religion also offers examples of what Roy D’Andrade (1984) would later call the directive and evocative functions of symbolic systems, as it serves to guide and motivate action by, as Geertz (1973b) put it, forming an idea of what the world is like and “clothing” that idea in such an “aura of factuality” as to make it seem self-evident.

Symbolic systems can become so engrained in a community’s understanding of the world that they become difficult to spot. Kinship systems, for instance, appeared for a very long time (even to anthropologists) to be deeply rooted in biology. But David Schneider (1968) argued that there is nothing about shared ancestry or genetic relatedness that necessarily leads to a recognition of the rights, duties, and responsibilities associated with cultural systems of kinship. Numerous kin classifications, in fact, ignore that criterion completely. Schneider concluded that biological relatedness is a symbol just like any other, arbitrarily designated to denote shared identity and mutual responsibility among social groups.

The Constitutive Power of Culture

The very act of perceiving an object or event in the world as being a type of something (e.g., perceiving a certain creature as a dog, the clasping of hands as a prayer, or the meeting of lips as a kiss ) entails the symbolic interpretation and generalization of a specific, concrete event. Because symbols represent concepts rather than just things as they exist in the world, almost everything humans perceive is at least partially constituted by collective representations and interpretation. But the power of culture is such that, in many cases, symbols do not attach to any referent at all, and instead actually create the objects or events to which they refer. Philosopher John Searle (1969) referred to this as the capacity to enact constitutive rules. In statements like “when a player crosses the goal line, he scores a touchdown” or “the candidate who receives the plurality of votes in the general election becomes president,” constitutive rules actually create the categories of touchdown and president. Societies are built upon intricate systems of these constitutive rules, which generally take the form “ x counts as y in context c. ” While usually thought of by the members of the community as natural or even commonsensical, these rules are entirely a matter of social agreement. The idea that one owns a house or car or any other piece of property, for instance, is based on the collective belief that transferring something called “money” to an institution called a “bank” entitles one to special rights over some material thing. Most often, others will not even question those rights. But when someone does seek to violate the agreement through force, such as by stealing a car or invading a home, it is understood that people in uniforms with guns will (hopefully) show up to stop them. Those uniformed enforcers of social consensus will only do so, however, insofar as they agree to obey the orders of an imaginary chain of authority that runs all the way to the president of the United States, whose power comes not from any physical or mental capacity of his, but from the collective agreement that he is to have such authority. Thus, personal property—like civil government or American football—relies on a complex, ordered hierarchy of constitutive rules and social facts that have no basis in material reality.

These institutions reflect a more basic property of symbolic representation: The meaning of cultural units tends to be layered upon many other orders of meaning. Something as simple as reading this sentence, for instance, plays upon such varied levels of conventional meaning as the denotation of speech sounds by individual letters, the definitions of words and groups of words, the grammatical rules that operate at the sentence level, and matters of tone and style conveyed by the structure of the paper as a whole.

The centrality of meanings and symbols in contemporary concepts of culture poses challenges for the study of social life. To begin with, there really is no such thing as a symbol per se, although almost anything can function as one. Symbolism is not an inherent quality of any word or sign, but rather a product of interpretation and consensus. Nor is the meaning of a symbol rigidly determined even by the force of collective agreement. As a number of theorists have argued, the interpretation of symbols relies on complex and often emotionally charged processes in the mind of the interpreter, which it must call upon a broad range of preexisting schemas, scripts, and tacit understandings in order to make any sense at all. Consider the following short description of a sequence of events: “Roger went to the restaurant/The waiter was unfriendly/Roger left a small tip.” In their work on artificial intelligence, Schank and Abelson (1977) showed how little sense such a sequence makes without detailed prior knowledge of what normally happens at a restaurant, what is expected of a waiter, and what is communicated in the complex practice of tipping.

For Clifford Geertz (1973c), the ambiguity and polysemy of the subject matter of anthropology meant that cultures could not be explained, but instead could only be interpreted through a process he called “thick description.” To truly grasp the meaning and significance of a belief or action, Geertz argued, one must first acquire a comprehensive understanding of the social and cultural context in which it occurs. Drawing on literary theory, Geertz suggested that culture must be “read” like a text—a text that, from the anthropologist’s point of view, is “foreign and faded,” full of abbreviations, omissions, and contradictions, and written not by anyone’s pen but by sporadic instances of socially meaningful behavior.

Critiques of the Culture Concept

While culture has long been the central object of inquiry in American anthropology (hence the term cultural anthropology ), scholars in the British social-anthropological tradition have historically been skeptical of culture, and have instead framed their investigations around the concept of society . In social anthropology, society refers to a complex web of social relationships and systematized patterns of behaviors and ideologies known as institutions (e.g., the military, primitive magic, the nuclear family, or the National Football League). Social anthropologists compare institutions across different societies in order to ascertain their “function.” They are particularly interested in “latent” functions: those consequences of institutionalized behavior of which the actors are unaware, but which nevertheless work to motivate the very existence of the institution. The functionalist approach rests on the assumption that particular types of institutions, such as kinship or government, are motivated by the same basic factors and oriented toward the same basic ends in all human societies in which they are present. Underneath their superficial differences, the various cultural manifestations of these institutions are seen as essentially similar, like species belonging to the same genus.

As concepts, culture and society are not necessarily incompatible, and have been viewed by some as closely related and even complementary. But for several generations of social anthropologists, culture was something of a taboo term. A. R. Radcliffe-Browne, one of the discipline’s founders, insisted that the concept of culture erroneously treated abstract ideas as real and concrete, and was too broad a concept to be useful in the study of social life. He claimed that society, on the other hand, was the proper object of anthropology, since societies were bounded and concrete, and social structure was embodied in directly observable social behavior. Eventually, however, social anthropologists recognized that no attempt to study social relationships could be successful without consideration of the cultural beliefs and values associated with them. Oxford anthropologist John Beattie (1964) identified this as the primary reason that Radcliffe-Browne’s limited conception of social anthropology as “comparative sociology” never fully caught on: The behavior of people in society cannot be understood without reference to what social relationships mean to those who participate in them.

Still, a number of social anthropologists remain reluctant to refer to the semiotic dimension of social life as culture. Adam Kuper (1999) argued that it is more legitimate to analyze religious beliefs, arts, and other institutions as separate domains than as “bound together in a single bundle labeled culture” (p. 245). But as William Sewell (2005) observed, and as Ruth Benedict (1934) noted before him, basic beliefs and symbolic representations of the world tend to cut across the lines that sociologists would use to carve up the social sphere, reaching across institutions, linguistic communities, age-groups, and even religions to span entire societies. This suggests that any attempt to approach such beliefs as though they were miscellaneous qualities of separate institutions risks completely missing the presence of a single, pervasive cultural theme. The more or less unquestioned belief in the sanctity of human life in modern society, for instance, affects almost every conceivable institution, from industrial development and urban planning to the cultivation of food and medicinal testing. To effectively treat such an idea as a product of any one institution would thus be a significant analytical mistake.

In recent years, some of the strongest criticisms of the culture concept have come from within the discipline of cultural anthropology itself. Adherents of a loosely defined movement known as “postmodern anthropology” (also variably referred to as postcultural, poststructural, and reflexive anthropology) have questioned the very usefulness and validity of culture as an abstract concept. Often associated with a 1986 collection of essays edited by James Clifford and George Marcus called Writing Culture, the movement can be viewed an extension of the theories of Clifford Geertz—particularly his use of literary theory and his emphasis on the importance of context. Michael Silverstein (2005) identified the “symbols and meaning-ism” that Geertz helped usher in as the point at which anthropology became a hermeneutic and interpretive project rather than an observational science. But for those affiliated with the Writing Culture movement, Geertz stopped short of the inevitable conclusion of his argument—that the description or “interpretation” of a culture is as much a reflection of the point of view of the anthropologist as it is of the culture itself. From this perspective, the anthropologist does not simply record facts about others’ ways of life; instead, she actually creates (or at least coconstructs) the culture as she describes it. This is obviously very troubling for the credibility of anthropological knowledge, and it becomes especially problematic when, as was traditionally the case, the anthropologist is a member of a dominant society granted unilateral authority to depict the beliefs and practices of a subjugated population. Critics point to this unequal power dynamic as at least partially to blame for misguided attempts to capture complex realities using false dichotomies like “savage vs. civilized,” “rational vs. irrational,” or “individualist vs. collectivist.”

This “reflexive” critique is linked to an older, more basic criticism in anthropology, suggesting that culture is a tool for the preservation of existing systems of power and oppression. Proponents of this view argue that by ascribing too much importance to tradition, the concept of culture legitimates the domination and mistreatment of traditionally powerless segments of societies. A frequently cited example is the disadvantaged place that women are perceived as occupying in traditionally patriarchal societies. Others have argued, however, that the perception of inequality and discrimination in other cultures is prone to error, since it often fails to take into account the subtle cultural mechanisms that redistribute power and shape social relationships. And while there certainly are cases where the idea of culture is misused to justify atrocities, this does not explain why the concept should be rejected as an analytical tool.

Another dimension of the postmodern critique takes specific aim at the practice of referring to a culture or to cultures in the plural. Some feel that this use—which is often traced, somewhat controversially, to the theories of Ruth Benedict and Margaret Mead—oversimplifies and stereotypes other societies, erroneously treating entire communities as uniform, isolated, and unchanging while downplaying diversity and internal disagreement. This implication is ever more frequently seen in popular usage, where terms like Japanese culture imply a universally shared, unquestioned, and totaling “way of life.” And while integration is not necessarily synonymous with cultural determinism, Benedict (1934), for her part, did little to dispel that interpretation in asserting that the individual “is the little creature of his culture. . . . Its habits are his habits, its beliefs his beliefs” (pp. 2–3). In response, critics like Clifford and Marcus (1986) stressed the importance of individual agency and “resistance” to cultural norms, pointing out that cultures are not bounded, homogeneous, or “pure.” Instead, culture is contested, contradictory, and only loosely integrated, constantly subject to change both from within and without. Postmodernists note that cultures have always been hybridized and permeable, but that this has become increasingly so in recent decades in the face of globalization and capitalist expansion. As Clifford and Marcus (1986) observed, difference is now routinely found next door and familiarity at the end of the earth, suggesting that received notions of culture are not only mistaken, but also irrelevant.

Others maintain, however, that the concept of culture has never implied uniformity, and that no serious anthropologist ever viewed individuals as mindless automatons totally controlled by a self-contained and unchanging cultural system. They argue that culture has always been an abstraction; that is, culture does not represent a “thing” that exists in the world as such, but is instead separated by way of observation and logical inference from the context of real-world actions and utterances in which it is embedded. Alfred Kroeber (1952) defended the practice of speaking of cultures in the plural on this basis, anticipating contemporary critiques in pointing out that one could speak at the same time of a Tokyo or a Japanese or an East Asian culture without implying that any of them represented a homogeneous or totalizing way of life. More recently, Marshall Sahlins (1999) has asserted that the concept of culture critiqued by postmodern anthropologists is a myth. Sahlins does argue that cultural communities can have boundaries, but that these boundaries, rather than being barriers to the flow of people, goods, or ideas, represent conscious designations of identity and inclusion made by the members of the community themselves.

Regarding the uniformity and homogeneity of cultural knowledge, anthropologist Richard Shweder (2003) has argued that culture never implied the passive acceptance of received beliefs and practices or the absence of dispute or debate. Shweder points out that every culture has experts and novices, but that such unequal distribution of knowledge does not mean that anyone is more or less a member of that culture. As one of the chief proponents of the resurgent interdisciplinary field of “cultural psychology,” Shweder has helped demonstrate that basic psychological processes such as selfhood and emotion, rather than being products of deep structural similarity, are rooted in culturally specific modes of understanding (Shweder & Bourne, 1984). Such findings have provided some of the driving force behind the growing influence of the concept of culture in the field of social psychology (e.g., Markus & Kitayama, 1991; et al).

Whether prior theories or particular uses of the term carried misguided implications or not, anthropologists continue to recognize culture as an indispensible consideration in the analysis of human social life. As theorists from nearly every area of study surveyed in this research paper have agreed, shared cultural knowledge is absolutely essential for individuals to function in a way that is recognizably human (see Geertz, 1973a, 1973b, 1973c; Whorf, 1956; Beattie, 1964; Clifford & Marcus, 1986; Sewell, 2005; Sahlins, 1976). Clifford Geertz referred to a gap that exists between our species’ innate biological predispositions and what humans must know in order to survive and function— a gap that could only be filled with highly particular systems of beliefs, values, and representations expressed and transmitted through symbols.

Even those most critical of the concept tend to recognize the centrality and pervasiveness of culture. Culture represents the shared ideas that define and give meaning to objects, events, and relationships in our world and the collective representations that create and maintain social institutions. This is true even of those domains of human activity appearing to follow their own logic and obeying their set of rules and principles. Renato Rosaldo (1989), whose work was also included among the 1986 collection of essays that kindled the postmodern anthropological movement, wrote as follows:

Culture … refers broadly to the forms through which people make sense of their lives … It does not inhabit a set-aside domain as does politics or economics. From the pirouettes of classical ballet to the most brute of brute facts, all human conduct is culturally mediated. Culture encompasses the everyday and the esoteric, the mundane and the elevated, the ridiculous and the sublime. Neither high nor low, culture is all-pervasive. (p. 26)

Thus, the concept of culture, in one way or another, is likely to remain of central concern to the discipline of anthropology for the foreseeable future.

Bibliography:

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373 Culture Research Topics & Ideas for Essays and Papers

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Culture research topics include various human behaviors and beliefs, offering a deep dive into societal norms, values, traditions, and symbols that have shaped and continue to shape civilizations across time and space. Themes encompass many areas, such as linguistics, anthropology, sociology, psychology, history, and arts. Topics also may include investigating the effects of globalization on indigenous cultures, the role of pop culture in shaping societal values, impacts of cultural assimilation, or tracing the evolution of language in a particular region. Studies in this field illuminate the tapestry of human existence, providing rich insights into unique human histories. Thus, culture research topics are not only intrinsically fascinating but also have crucial implications for policy, education, and understanding of identity, community, and coexistence in an increasingly diverse and interconnected world.

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Easy Cultural Essay Topics

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Interesting Culture Topics to Research for Essays and Papers

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Cultural Anthropology Topics for a Research Paper

• Decoding Symbolism in Ancient Mayan Art
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• Globalization and the Cultural Phenomenon of Fast Food
• Cyberculture and the Emergence of Virtual Communities
• Reality TV and Its Cultural Repercussions
• Influence of Celebrity Culture on Youth Values
• Pandemic Culture: Changes in Behavioral Patterns Due to COVID-19
• Examining the Cultural Phenomenon of Social Activism in Digital Spaces
• Coffee Culture: A Global Phenomenon With Local Variations
• Influence of Anime and Manga on Global Pop Culture
• Cultural Phenomena of Aging Societies in Developed Countries
• Nerd Culture and Its Influence on Entertainment Industry
• Fashion Trends as Reflections of Cultural Change
• Online Gaming Communities as Cultural Phenomena
• Cultural Shifts in Attitudes Toward Mental Health
• The Phenomenon of Remote Work and Cultural Implications
• Cultural Perception and Adoption of Renewable Energy Solutions

Cultural Psychology Research Topics in Culture Studies

• Cross-Cultural Perspectives on Emotional Expression
• Psychology of Superstitions in Various Cultures
• Analysis of Collectivist vs. Individualistic Cultural Psychologies
• Cultural Factors Influencing Child Development
• Cultural Psychology of Grief and Mourning Rituals
• Understanding Perception of Time in Different Cultures
• Body Language and Non-Verbal Communication Across Cultures
• Examining the Cultural Context of Dreams
• Cultural Influences on Human Memory
• Cultural Diversity and Its Effects on Learning Styles
• Cognitive Biases and Cultural Influences: A Comparative Study
• Cultural Influences on Risk Perception and Decision-Making
• Psychological Perspectives on Folklore and Mythology Across Cultures
• Understanding the Cultural Aspects of Empathy
• Interplay of Language and Thought in Cultural Psychology
• Cultural Differences in Coping Strategies for Stress
• Cultural Influences on Perception of Pain
• Influence of Culture on Self-Esteem and Self-Concept
• Psychological Analysis of Taboos Across Different Cultures

Environmentalism and Culture Research Topics

• Cultural Practices in Biodiversity Conservation
• Green Architecture: Cultural and Environmental Interactions
• Cultural Perceptions of Climate Change in Island Nations
• Understanding Indigenous Knowledge Systems in Environmental Stewardship
• Environmental Ethics in Native American Cultures
• Ecotourism and Its Influence on Local Culture
• Influence of Environmental Movements on Contemporary Art
• Cultural Factors Affecting Renewable Energy Adoption
• Influence of Traditional Farming Practices on Biodiversity
• Cultural Aspects of Waste Management Practices
• Sacred Natural Sites and Their Role in Conservation
• Cultural Landscapes and Strategies for Their Preservation
• Impact of Climate Migration on Cultural Identity
• Rituals and Myths Related to Nature Across Cultures
• Impact of Environmental Policies on Indigenous Cultures
• Understanding Cultural Dimensions of Urban Green Spaces
• Influence of Culture on Perceptions of Genetically Modified Organisms
• Culture and the Transition to a Circular Economy
• Perceptions of Water Scarcity in Different Cultures
• Cultural Responses to Deforestation in Rainforest Communities

Gender and Culture Research Topics

• Exploring the Cultural Construction of Masculinity
• Perception of Beauty Standards Across Different Cultures
• Cultural Interpretations of Transgender Identities
• Influence of Cultural Norms on Gender Equity in Education
• Understanding Gender Roles in Indigenous Cultures
• Implications of Matrilineal Societies for Gender Equality
• Cultural Factors Affecting Women’s Political Participation
• Gender Dynamics in Traditional Rituals and Festivals
• Intersectionality of Gender, Culture, and Religion
• Gender Representation in Global Advertising
• Investigating Gender Stereotypes in Children’s Literature
• Cultural Perception of Non-Binary Gender Identities
• Influence of Gender Roles on Career Choices Across Cultures
• Cultural Factors Influencing Maternal Health
• Gender Dynamics in Migration and Displacement
• Influence of Culture on Men’s Mental Health
• Gendered Spaces: A Cultural Perspective
• Culture and Gender Inequity in Access to Healthcare
• Cultural Perspectives on Domestic Roles and Responsibilities

Globalization and Culture Topics

• Understanding the Cultural Implications of Globalized Media
• Cultural Resistance to Globalization in Indigenous Communities
• Globalization and the Spread of English: Implications for Linguistic Diversity
• Influence of Globalization on Local Music Genres
• Exploring Cultural Homogenization in Global Cities
• Food Culture in the Age of Globalization: A Case Study
• Globalization and the Commodification of Indigenous Cultures
• Globalization and the Transformation of Traditional Art Forms
• Diaspora Communities: Navigating Globalization and Cultural Identity
• Transnational Cinema: Cross-Cultural Influences and Globalization
• Implications of Globalization for Indigenous Knowledge Systems
• Globalization and Changing Gender Norms: A Cross-Cultural Study
• Cultural Hybridity in Globalized Fashion Trends
• Internet Culture and Globalization: A Complex Relationship
• Globalization and Its Effect on Cultural Heritage Preservation
• Influence of Globalized Education on Cultural Diversity
• Cultural Adaptation in Global Marketing Strategies
• Globalization and Transformation of Religious Practices
• Impact of Global Migration on Cultural Diversity
• Understanding Globalization’s Effect on Cultural Autonomy

Intercultural Communication Topics

• Intercultural Communication in Multinational Corporations
• Exploring Communication Barriers in Intercultural Marriages
• Interpretation of Non-Verbal Cues Across Cultures
• Intercultural Communication in Virtual Teams
• Analysis of Humor in Intercultural Communication
• Influence of Cultural Stereotypes on Intercultural Communication
• Examining Intercultural Communication in Healthcare Settings
• Challenges of Intercultural Communication in Diplomacy
• Influence of Social Media on Intercultural Communication
• Impact of Language Proficiency on Intercultural Communication
• Intercultural Communication in International Development Projects
• Implications of Cultural Taboos in Intercultural Communication
• Intercultural Miscommunication: Case Studies and Analysis
• Influence of Cultural Dimensions on Communication Styles
• Intercultural Communication in Refugee and Immigrant Integration
• Strategies for Effective Intercultural Communication in Education
• Investigating the Role of Empathy in Intercultural Communication
• Impact of Intercultural Communication on Global Marketing Strategies
• Ethics in Intercultural Communication: A Critical Review

List of Culture Research Topics

• Cultural Perspectives on Death and Afterlife
• Influence of Pop Culture on Youth Identity Formation
• Understanding Culturally Specific Healing Practices
• Martial Arts as Cultural Phenomena: A Comparative Study
• Street Art and Its Cultural Significance
• Dynamics of Food Culture: Traditional vs. Modern
• Exploring the Cultural History of Tattoos
• Cultural Aspects of Aging: East vs. West
• Cultural Factors Influencing Childbirth Practices
• Language Revitalization in Endangered Cultures
• Cultural Significance of Traditional Dress Codes
• Examining Body Modification Practices Across Cultures
• Indigenous Knowledge and Sustainable Agriculture
• Analysis of Cultural Aspects in Cybersecurity
• Influence of Culture on Parenting Styles
• Representation of Culture in Animated Films
• Cultural Practices in Disaster Management and Preparedness
• Cultural Transformation in Post-Colonial Societies
• Cultural Understanding of Mental Health Disorders
• Decoding Cultural Symbolism in Mythology and Folklore

Multiculturalism and Diversity Research Topics

• Multiculturalism in Children’s Literature: A Content Analysis
• Exploring the Dynamics of Multicultural Teams in Organizations
• Multicultural Education and Student Achievement: An Empirical Study
• Influence of Multiculturalism on Urban Design and Architecture
• Multiculturalism and Its Effect on National Identity
• Implications of Multiculturalism for Social Justice Education
• Perceptions of Diversity in the Media Industry
• Understanding the Challenges of Multicultural Counselling
• Cultural Diversity and Innovation in Start-Up Ecosystems
• Effect of Multiculturalism on Interpersonal Relationships in Diverse Societies
• Diversity and Inclusion in the Tech Industry: Case Studies
• Cultural Diversity in the Judiciary: An International Comparison
• Multilingual Education in Multicultural Societies: Best Practices
• Multiculturalism and Its Influence on Public Health Policies
• Social Cohesion in Multicultural Neighborhoods: A Field Study
• Cultural Diversity in Political Representation: A Global Perspective
• Inclusion of Minority Cultures in National History Curriculum
• Multiculturalism and Its Influence on Contemporary Art Movements
• Challenges of Managing Diversity in Higher Education Institutions
• Multiculturalism and the Transformation of Urban Food Culture

Sociology of Culture Research Topics

• Sociological Perspectives on Cultural Taboos
• Culture and Social Class: Interplay and Implications
• Cultural Factors in the Sociology of Deviance
• Exploring Cultural Capital in Educational Achievement
• Sociological Analysis of Food Culture and Social Status
• Subcultures and Their Influence on Mainstream Society
• Sociology of Cultural Assimilation in Immigrant Communities
• Cultural Factors Affecting Social Mobility: An Empirical Study
• Sociological Dimensions of Popular Culture
• Understanding Cultural Factors in Health Disparities
• Sociology of Aging in Different Cultural Contexts
• Exploring the Sociology of Cultural Trauma
• Cultural Context of Social Movements
• Sociological Analysis of Celebrity Culture
• Cultural Dimensions of Urban Sociology
• Influence of Culture on Social Networks
• Sociological Perspectives on Cultural Appropriation
• Cultural Factors in Gender Inequality: A Sociological View
• Understanding the Cultural Aspects of Gentrification
• Sociology of Culture and Social Change: Case Studies
• Cultural Transformation and Its Sociological Implications
• Understanding Cultural Stigma in Mental Health
• Body Image Perceptions Across Different Cultures
• Cultural Influences on Societal Trust and Cohesion
• Sociology of Music: Exploring Cultural Genres
• Cultural Factors in Youth Gangs and Deviance
• Cultural Nuances in the Sociology of Emotions
• Exploring the Cultural Context of Aging Societies
• Cultural Perspectives on Social Stratification
• Sociological Implications of Intercultural Marriages
• Cultural Narratives in Gender Identity Construction
• Sociology of Art: Understanding Cultural Expressions
• Understanding Cultural Perspectives on Human Rights
• Cultural Factors in Environmental Sociology
• Cultural Interpretations of Religious Symbols
• Sociology of Language and Cultural Identity
• Cultural Influences on Children’s Socialization Processes
• Exploring the Cultural Dynamics of Social Protests
• Sociological Perspectives on Cultural Heritage and Identity
• Cultural Context of Intergenerational Relationships

Subculture Research Ideas

• Gothic Subculture: A Sociological Perspective
• Exploring the Culture of eSports Enthusiasts
• Punk Rock: An Ethnographic Study of Rebellion and Resistance
• Exploring the Vegan Subculture: Beliefs and Lifestyle
• Cosplay Subculture: Identity and Community
• Street Art: A Study of Subcultural Expression
• Influence of Hip-Hop Subculture on Urban Fashion
• In-Depth Study of the Online Gaming Subculture
• Psychedelic Subculture: Perception, Art, and Social Norms
• Understanding the Straight Edge Subculture: Music and Morality
• Subculture and Identity Formation in Adolescents
• Tattoo Subculture: Expressions of Individuality or Conformity?
• Exploring the Subculture of Comic Book Fandom
• Bodybuilding Subculture: Discipline, Lifestyle, and Body Image
• Subcultural Study of Skateboarders: Rebellion or Recreation?
• Hacker Subculture: Values, Beliefs, and Ethos
• Exploring the Subculture of Minimalist Lifestyle
• The Culture of Craft Beer Enthusiasts: A Subcultural Analysis
• Unveiling the Mysterious World of Secret Societies

Western Civilization Essay Topics in Culture Research

• Democracy and Its Origins in Ancient Greece
• Influence of Renaissance Art on Western Culture
• Exploring the Cultural Significance of the Magna Carta
• Western Civilization and the Emergence of Scientific Thinking
• Christianity’s Influence on Western Morality and Ethics
• Enlightenment Thought and Its Influence on Modern Western Society
• Fall of the Roman Empire: A Pivot Point in Western Civilization
• Imperialism and Western Civilization: A Historical Analysis
• Historiography of the French Revolution in Western Discourse
• Industrial Revolution: The Engine of Western Progress
• Influence of Western Civilization on Global Legal Systems
• The Age of Exploration: Western Civilization Expands
• Western Civilization: From Gutenberg’s Press to the Internet
• Interpretations of the American Revolution in Western Thought
• Historical and Cultural Analysis of Western Romanticism
• Contribution of Western Civilization to Modern Medicine
• Development and Influence of Western Classical Music
• The Influence of Western Philosophy on Modern Thought
• The Role of Western Civilization in Shaping Modern Economics
• Western Civilization and Its Influence on Modern Democracy

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• v.34; 2020 Mar

Bacterial culture through selective and non-selective conditions: the evolution of culture media in clinical microbiology

1) Aix-Marseille Univ, IRD, APHM, MEPHI, Marseille, France

J.C. Lagier

2) Institut Hospitalo-Universitaire Méditerranée Infection, Marseillle, France

S. Khelaifia

Microbiology has been largely developed thanks to the discovery and optimization of culture media. The first liquid artificial culture medium was created by Louis Pasteur in 1860. Previously, bacterial growth on daily materials such as some foods had been observed. These observations highlighted the importance of the bacteria's natural environment and their nutritional needs in the development of culture media for their isolation. A culture medium is essentially composed of basic elements (water, nutrients), to which must be added different growth factors that will be specific to each bacterium and necessary for their growth.

The evolution of bacterial culture through the media used for their culture began with the development of the first solid culture medium by Koch, allowing not only the production of bacterial colonies, but also the possibility of purifying a bacterial clone. The main gelling agent used in solid culture media is agar. However, some limits have been observed in the use of agar because of some extremely oxygen-sensitive bacteria that do not grow on agar media, and other alternatives were proposed and tested. Then, the discovery of antimicrobial agents and their specific targets prompted the emergence of selective media. These inhibiting agents make it possible to eliminate undesirable bacteria from the microbiota and select the bacteria desired. Thanks to a better knowledge of the bacterial environment, it will be possible to develop new culture media and new culture conditions, better adapted to certain fastidious bacteria that are difficult to isolate.

Introduction

The discovery of culture media allowed the development of microbiology in the nineteenth century [ 1 ]. Bacterial culture was the first method developed to study the human microbiota [ 2 ], using an artificial medium that allows growth and isolation of bacteria. The first to have cultured a bacterium in a reproducible way was Louis Pasteur in 1860 thanks to the development of the first so-called artificial culture medium [ 3 ]. Recently, after the emergence of molecular techniques in the 1970s, such as PCR, sequencing and more particularly metagenomics, microbiologists have favoured these innovative techniques to the detriment of culture. Nevertheless, metagenomics presents certain disadvantages and in particular a depth bias, due to the lack of sensitivity of the primers used, because it does not detect bacteria present at concentrations <10 5 bacteria per gram of stool [ 2 ]. Moreover, these techniques only detect DNA: it is impossible with these techniques to differentiate DNA belonging to living bacteria from that of the transient bacteria of the microbiota studied, or from that of dead bacteria.

A few years ago, culturomics, a new culture technique that uses a very large number of culture media and culture conditions to extend the repertoire of bacteria, was developed in our laboratory [ 2 ]. This technique demonstrates the complementarity between metagenomics and culturomics. Therefore, the metagenomic identification of bacterial species existing in a given microbiota can be exploited by culturomics through the optimization of new specific culture media for the isolation of these species. This complementarity allows culturomics to become a targeted technique.

New culture media today mimic the natural environment of bacteria by adding different elements in culture medium to cultivate bacteria that were previously uncultivated.

We propose here a bibliographical review of culture media and the evolution of techniques through the development of microbiology over time.

Empirical approach of microbiology

Observational microbiology.

Microbiology is defined not only by the organisms it studies, but also by the tools used to study them. The first observation of a bacterium was made around 1673 by the Dutch microscopist Anton van Leeuwenhoek thanks to the microscopes he had developed. Those enlarged from 50 to 300 times what he observed [ 1 , 3 ].

In the course of his research, he highlighted small structures that he called ‘animalcules’ [ 4 ], because he thought he was observing small animals [ 5 ]. Throughout his observations, he described and drew yeast cells, filiform fungi, microscopic algae and protozoa [ 4 ]. Leeuwenhoek was also the first to observe a parasite, Giardia lamblia [ 3 ]. However, microscopy alone cannot address all the questions about the microorganisms studied. For about 200 years microbiology was stagnating until the development of microbial isolation techniques in pure cultures. This is another important milestone in the history of microbiology.

Cultural microbiology

The birth of culture broth.

In the thirteenth century, 400 years before Leeuwenhoek, a blood-like substance appeared on the communion bread. In line with Christian beliefs, this red substance was assumed to be the blood of Christ. Bartholomeo Bizio, an Italian pharmacist, solved this mystery in 1817 thanks to advances in microbiology and showed that it was not blood, but a microorganism that he named Serratia marcescens . This bacterium appeared as red colonies on bread when stored in a warm and humid atmosphere [ 6 ]. It is one of the first natural cultures of a bacterium. The origins of culture media date back to the nineteenth century. Many bacteriologists have tried, with varying degrees of success, to grow bacteria on the food or material on which the microorganism was first developed.

Evolution of microbiology was made possible by challenging the theory of spontaneous generation, according to which living organisms could develop from dead or decaying matter and so spontaneously appear in cultures. Hence, it was inconceivable to obtain pure cultures. In 1861, Louis Pasteur, a French microbiologist [ 3 ], solved this problem through an experiment. He placed nutrient solutions in flasks, heated their necks with flame and stretched them in various ways, keeping the end open to the air. Pasteur boiled the solutions for a few minutes and cooled them. No growth appeared even if the contents of the flasks had been exposed to air. Pasteur noticed that there was no growth because dust and germs had been trapped on the walls of the curved tubes. If the tubes were broken, growth began immediately. In this way, Pasteur not only demonstrated that spontaneous generation was nonsense, but also found ways to keep sterile solutions [ 3 ].

The first to have cultured bacteria reproducibly in a liquid culture medium was Louis Pasteur. In 1860, he developed a culture medium containing ‘yeast soup’, ashes, sugar and ammonium salts [ 7 , 8 ]. His objective was to create a fermentation medium to demonstrate that each fermentation (alcoholic, acetic, lactic …) was associated with the development of a particular microorganism [ 9 ]. The presence of these different elements in the medium allowed him to observe that some of these components could promote or inhibit the growth of certain bacteria and that they could also allow the emergence of certain bacteria compared with others [ 8 ].

Indeed, in the course of the study of fermentation of beer, he was confronted with a problem: when the beer was healthy, the microscope only showed brewer's yeast, but when the beer was acid, Pasteur noticed that the tanks contained ‘tiny rod-shaped objects’ producing lactic acid. This fermentation medium therefore made it possible to highlight the multiplication of this bacterium [ 1 , 3 ].

In 1881, Robert Koch demonstrated optimal growth of bacteria when they were incubated in a broth composed of fresh beef serum or meat extract. However, the use of a liquid culture medium did not produce pure bacterial cultures. Koch therefore sought a way to solidify the medium [ 8 ] ( Fig. 1 ).

Evolution of culture media: from the first bacterial culture (1673) to culturomics.

Emergence of pure cultures in solid media

First, he tested coagulated egg albumin, starch paste or an aseptically cut slice of potato. However, not all of these techniques allowed him to isolate colonies. Koch then added gelatin to his broth and poured it all over a flat glass plate. However, gelatin had disadvantages as it liquefied at temperatures above 25°C and could be consumed by gelatinase, an enzyme produced by certain bacteria. Thanks to the wife of one of his assistants, Fannie Hesse, who used agar to solidify her jams, he replaced gelatin with agar, which allowed him to obtain firm agars and isolate bacteria. In 1887, Julius Richard Petri replaced the glass plate with a circular culture box, the Petri box was created, and is still used today [ 8 ]. This allowed him to obtain and observe isolated colonies and to limit contamination.

How to design an enriched culture medium?

An enriched culture medium is a medium to which have been added elements essential for the growth of bacteria.

The nutrients

In order to grow, bacteria need a minimum of nutrients: water, a carbon source, a nitrogen source and some mineral salts [ 10 ].

Water plays a fundamental role in solubilizing nutrients, transporting them and ensuring hydrolysis reactions. Some bacteria need free water for their growth. If evaporation occurs during the incubation of the agar, there may be a loss of this water, resulting in a decrease in colony size and inhibition of bacterial growth [ 10 , 11 ].

Carbon sources

Carbon is the most abundant constituent element in bacteria. It is essential for bacteria to produce carbon molecules, such as fats, carbohydrates, proteins and nucleic acids. Bacteria can use inorganic carbon sources, such as carbon dioxide, or organic sources such as sugars and alcohols [ 10 , 12 ].

Nitrogen sources

As for nitrogen sources, they are numerous and can be found in a large number of compounds used in the composition of a culture medium. It is found in the organic form, corresponding to protein hydrolysates, particularly in case of hydrolysate, proteose-peptone or tryptone [ 12 ], but also in an inorganic form, nitrates [ 13 ]. Nitrogen allows bacteria to synthesize their proteins.

Finally, among the common mineral salts, phosphate, sulphate, magnesium or calcium [ 11 ] are regularly found.

Energy sources

There are two types of bacteria, phototrophic bacteria, such as Thiocapsa roseopersicina [ 14 ], which uses light as an energy source by transforming it into an electrochemical gradient of protons [ 14 ], and chemotrophic bacteria, which use the energy of oxidation of mineral or organic compounds as energy sources [ 9 , 15 ]. Among these bacteria, we can find Listeria monocytogenes [ 16 ].

Growth factors

The use of a minimal medium does not allow the growth of certain bacteria that need specific elements to grow. It is sometimes necessary to add growth factors to culture media to boost the multiplication of bacteria. Growth factors are elements that bacteria are unable to synthesize from the nutrients available in the environment [ 10 , 17 ]. Growth factors are required in small quantities in the culture medium and their need is justified by the absence or blocking of a metabolic pathway in the bacterium.

Purine and pyrimidine bases

There are different categories of growth factors among which we find purine and pyrimidine bases. They are necessary for synthesis of nucleic acids. Indeed, some lactic acid bacteria need adenine, guanine, thymine or uracil for growth [ 17 ]. This is the case in particular for the bacterium Leuconostoc mesenteroides , for which guanine is essential for its growth [ 18 ].

Amino acids

Amino acids are also growth factors and are used for protein synthesis. Dunn et al. [ 19 ] showed in 1946 that only two amino acids were essential for Leuconostoc mesenteroides , glutamic acid and valine, whereas for Lactobacillus brevis , no less than 15 amino acids were necessary for its growth. This high requirement for amino acids can be explained by the fact that the base medium used at the time was not rich in common nutrients. Indeed, nowadays, Lactobacillus brevis grows on a COS agar (Columbia Blood Agar) (Biomérieux, Marcy l’Étoile, France), not supplemented with amino acids [ 20 ], but composed of casein hydrolysate and peptone proteose, themselves sources of amino acids [ 11 ].

Vitamins are also part of growth factors. They are coenzymes or precursors of coenzymes. A vitamin is an organic substance, necessary in small quantities for the metabolism of a living organism, which cannot be synthesized in sufficient quantity by that organism. Faecalibacterium prausnitzii , which is a fastidious bacterium, requires a large number of vitamins to grow, such as biotin, folic acid, riboflavin or vitamin B12 [ 21 ]. This bacterium also requires the presence of other growth factors such as volatile fatty acids (acetic acid, propionic acid or valeric acid) [ 21 ].

Blood use and its derivatives

Blood and its derivatives will also boost the growth of certain bacteria. In culture media, it is common to use sheep's blood or horse's blood. The role of blood is to act as a protective agent against toxic oxygen radicals [ 22 ], but also as a nutritional supplement. For instance, cooked sheep's blood provides the factor X (haem) necessary for the growth of many pathogenic species, including Haemophilus influenzae [ 23 ]. Most often, 5% blood is added to the culture media [ 22 ]. Serum, such as fetal calf or lamb serum, can also be used as a growth factor by providing a large number of elements such as lipids, vitamins, triglycerides, minerals and others [ 24 ]. This blood has been cleared of cells, platelets and clotting factors. Fetal calf serum, which is most commonly used in microbiology [ 25 , 26 ], must be inactivated by heat before use (56°C for 30 min) to inactivate all components of the complement system present in this serum [ 27 , 28 ]. It must be stored at –20°C and heated to room temperature rather than in a water bath to avoid deterioration of the proteins it contains.

Rumen fluid

Finally, it is also possible to use the rumen fluid [ 2 , 29 ] to promote the growth of certain bacterial species by mimicking their natural environment. The rumen fluid used corresponds to the rumen of the sheep. To prepare it, it is first necessary to recover the juice from the fermented plants in the stomach by filtering it through a fine cloth. This juice is then centrifuged (10 000 rpm for 90 min) and the supernatant is collected. Then, it undergoes three successive filtrations at 0.8 μm, 0.45 μm and 0.22 μm [ 2 , 30 ]. 5% rumen juice is usually added to the culture media. The rumen fluid can promote the growth of certain species of Treponema , such as Treponema hyodysenteriae and Treponema innocens [ 31 ].

Antioxidants

Some anaerobic bacteria are fastidious to grow and new culture strategies have been developed to isolate them. Indeed, anaerobic bacteria are most abundant in the human intestinal microbiota, accounting for up to 99.9% of total bacteria [ 32 ] and are extremely sensitive to oxygen, which is toxic to them. Antioxidants have therefore been added to culture media to allow the culture of strict anaerobic bacteria under aerobic conditions [ 33 , 34 ]. A number of antioxidants have been tested and have shown satisfactory results. This is the case for ascorbic acid and glutathione [ 34 ] or uric acid [ 35 ]. The addition of these antioxidants to the culture medium and its incubation under aerobic conditions allowed the growth of 135 strict anaerobic bacteria, 12 microaerophilic bacteria and 22 strict aerobic bacteria [ 35 ].

How can we have a selective culture medium?

A selective culture medium is used to isolate a particular bacterial species or genus. After the addition of a number of inhibitors to the culture medium, the objective of this type of medium is to eliminate unwanted microbial flora. The selective medium is composed of a basic medium to which antibiotics, chemicals, dyes, antiseptics, sodium salts or phages can be added [ 36 ].

Antibiotics

Antibiotics are the most commonly used selective agents. Their spectrum of action being well known, it is easier to anticipate their action on bacteria. There are a large number of antibiotics that can be used in culture media, some of which are called antibacterial because they target bacteria and others antifungal because they eliminate fungi and yeasts [ 37 ]. Some molecules target Gram-positive bacteria, such as penicillin G, bacitracin or vancomycin, whereas others target Gram-negative bacteria, such as colistin or polymixin B. Amphotericin B, cycloheximide or nystatin have an action against fungi and yeasts ( Table 1 ) [ 10 , 39 ]. Several antibiotics can be combined to obtain a more selective medium [ 37 ].

Table 1

Antibiotics agents used in bacterial culture

✓ Action against bacteria or fungi; χ No action against bacteria or fungi.

Antiseptics

Antiseptics are more rarely used in culture media. However, cetrimide [ 43 , 44 ] or acriflavin [ 10 ] can be found in some culture media. Chlorhexidine can be used to select Mycobacterium tuberculosis [ 45 , 46 ] ( Table 2 ). Ethanol can also select bacterial species, including sporulated bacteria [ 47 , 48 ] such as Clostridioides difficile [ 47 ].

Table 2

Antiseptics used in bacterial culture

Cetrimide Agar Base is a culture medium used to selectively isolate and identify Pseudomonas aeruginosa . Cetrimide is a quaternary ammonium that inhibits a large number of bacteria, including those of the genus Pseudomonas , other than Pseudomonas aeruginosa [ 10 ].

Sodium salts

Sodium salts are known for their inhibitory properties. The best known is sodium chloride, used to select halophilic bacteria that resist very high amounts of salts [ 49 ]. In addition, sodium deoxycholate has a strong solvent action on bacteria [ 50 ] ( Table 3 ).

Table 3

The Marine Agar 2216E culture medium is used to enumerate marine heterotrophic bacteria. It is composed of a high concentration of salt, which eliminates a large number of bacteria and preserves marine bacteria of interest [ 51 ].

Chemical substances

Chemical substances can be added to culture media to inhibit certain bacteria. These inhibiting substances include potassium tellurite and bile salts, which inhibit Gram-positive bacteria [ 10 , 39 , 52 ] or lithium chloride [ 10 , 39 ], which eliminates Gram-negative bacteria ( Table 4 ).

Table 4

Brayton et al. [ 53 ] have created a selective culture medium for Vibrio vulnificus , which is a pathogenic halophilic bacterium. This medium, VV agar, consists, among other things, of potassium tellurite as selective agent for inhibiting Enterobacteriaceae .

Dyes can be used as a colour indicator in a culture medium or as a selective agent against certain bacteria. Crystal violet is one of the most commonly used dyes to inhibit bacteria [ 37 , 54 ]. Malachite green and methylene blue are also used to inhibit Gram-positive and Gram-negative bacteria and Gram-positive bacteria, respectively [ 10 , 55 ] ( Table 5 ).

Table 5

A selective medium of Streptococcus pneumoniae has been developed, containing crystal violet. This dye is used to select streptococci and inhibit staphylococci as well as other Gram-positive bacteria [ 54 ].

Bacteriophages are specific viruses of bacteria that can infect and even destroy bacteria, in the case of lytic phages. In order to isolate Mycobacterium tuberculosis , the use of phage lysin decontaminates the sputum of other bacteria present in the pulmonary microbiota [ 56 ].

Sillankorva et al. [ 57 ] worked on permanent urinary tract infections due to Escherichia coli . In order to treat these infections, they tested different phages (T1, T4 and φX174-like phages) against E. coli . After 2 hours of treatment, phage T1 reduced the E. coli population by 45%, demonstrating the efficacy of this selective agent.

Disadvantages of gelling agents use

Liquid culture media versus solid culture media.

There are two main types of culture media, liquid and solid.

In liquid culture media, also called culture broths, nutrients are dissolved in water. The growth of bacteria in this type of medium can be demonstrated by the appearance of a turbidity in the medium, although this is not always the case. It is difficult to isolate a bacterium specifically in this type of medium. Indeed, the bacteria obtained from a sample inoculated into the culture broth are all mixed with each other. In addition, this type of culture medium does not allow the morphological characteristics of bacterial species to be identified [ 9 ].

However, liquid culture media facilitate access to nutrients for bacteria. These nutrients are all the more accessible as the culture media are incubated under agitation, allowing a renewal of nutrients for bacteria.

Solid culture media are obtained by adding a gelling agent, such as agar, to the culture broth. They make it possible to obtain isolated colonies of different bacterial species, which can be identified. The different morphological characteristics of the bacterium can be described from these cultures [ 9 , 58 ]. However, in solid culture media, access to nutrients for bacteria may be limited. Media with high gel content, such as agar, will form smaller colonies than low gel content media because nutrient flow and toxin removal are reduced [ 7 ].

In addition, it has been shown that agar, in excessive quantities, can inhibit the growth of certain bacteria, highlighting the need to find other gelling agents [ 9 ].

Different gelling agents

One of the first gelling agents used in culture media was gelatin. The problem with this gelling agent is that it melts at 37°C, which is the incubation temperature of most bacteria. Moreover, the presence of an enzyme in certain bacteria, gelatinase, causes the digestion of gelatin and therefore its degradation. Agar was then used in culture media. However, over-consumption of agar has led to a reduction in its source, red algae [ 59 ], which has increased costs. In addition, agarase, present in some bacteria, destroys agar, preventing the isolation of these bacteria [ 60 ]. In addition, agar can inhibit the growth of some anaerobic bacteria because inhibitory growth compounds can be produced from autoclaving phosphate with agar [ 61 ]. Finally, agar can cause inhibition of PCR of fungal DNA when extracted directly from the solid culture medium [ 62 ]. For all these reasons, new gelling agents have been sought. These gelling agents include κ-carrageenan, ι-carrageenan, sodium alginate, high-methoxyl and low-methoxyl pectins and gellan gum [ 60 , 63 ]. All these gelling agents have different properties and particular needs to gel ( Table 6 ).

Table 6

Gelling agents used in culture media [ 60 , 63 , 67 ]

Carrageenan gums

κ-carrageenan and ι-carrageenan are part of the carrageenan gums.

The first will form a firm gel with a rapid mass build-up when combined with potassium ions. It allows the growth of some bacteria. This gelling agent resists very alkaline pH values above 12.5, so can isolate very highly alkaliphilic bacteria [ 64 ]. It can be used to replace agar because many bacteria grow on κ-carrageenan-based media [ 65 ].

ι-carrageenan is rarely used because it gives elastic gels that make bacterial culture difficult [ 65 ].

Sodium alginate

This gelling agent is produced from brown seaweed extract and forms a flexible gel in the presence of calcium ions. However, this gelling agent does not provide a gel firm enough to grow bacteria [ 63 ].

High methoxyl and low methoxyl pectins

High-methoxyl pectins require sugar and high acidity to gel. Gel setting is slow and results in the formation of a ‘spreadable’ gel.

Low-methoxyl pectins form brittle gels in the presence of Ca 2+ [ 62 ].

Gellan gum is a polysaccharide produced by a bacterial genus, Sphingomonas spp. According to Tamaki et al. [ 66 ], 108 bacteria tested on media with gellan gum as gelling agent showed growth.

The use of these different gelling agents could allow the culture of new bacteria, which do not grow on the agar, because of the presence of an agarase for example or because the agar forms a network too dense to allow motility and optimal growth of certain bacteria [ 9 ].

Colony size

The amount of nutrients available in a culture medium will determine the size of bacterial colonies [ 58 ]. An overly firm culture medium, due to a high concentration of gelling agent, causes a decrease in the flow of nutrients and so a decrease in the access to these nutrients by bacteria [ 7 , 9 ]. On the other hand, in some culture media, the amount of nutrients available is too high and can be toxic for certain bacteria that require a poor culture medium to grow [ 68 ]. Microcolonies are colonies that are barely visible to the naked eye (between 100 and 300 μm in diameter). To obtain larger colonies, it is sometimes necessary to mimic the bacterium's natural environment by providing it with specific elements. This is the case, for example, for Phascolarctobacterium faecium and Phascolarctobacterium succinatutens , which form microcolonies. However, when the medium is supplemented with succinate, the colonies have a diameter ranging from 0.8 to 1.2 mm [ 69 , 70 ].

After stagnation in the development of new culture techniques, due to the rapid evolution of new microbiological methods such as metagenomics, bacterial culture is experiencing a new boom. In recent years, culturomics, with the use of new culture media and new culture conditions, has enabled the enrichment of the bacterial repertoire through the isolation of new bacterial species. This shows that, despite the abandonment of culture by a large number of microbiologists, culture media remain a fundamental tool for bacteriologists for the isolation of commensal but also pathogenic bacteria.

Studying the natural environment of bacteria that have remained uncultivated to date would be interesting because it would provide the essential elements for the bacteria to grow. Indeed, although there are many enriched culture media, each bacterium is unique and has specific requirements. The use of new gelling agents could also allow the isolation of new species for which agar was not suitable for their growth. Although many gelling agents have been tested, few are still used in commercial culture media and therefore in laboratories. Many developments in bacterial culture are therefore still to come, making it possible to enrich the bacterial repertoire and gain a better understanding of certain diseases.

In addition, intracellular bacteria such as Coxiella burnetii or Tropheryma whipplei require a host cell to survive and multiply. Some of these bacteria cause severe diseases and pose a diagnostic problem because of their fastidious growth or lack of growth on conventional media [ 71 ]. It would be interesting to develop culture media that allow faster and easier detection of these bacteria. In addition, as the microbiota plays an increasingly important role in human health [ 72 , 73 ], the development of probiotics is on the rise [ 74 ]. The use of targeted culture media to select certain bacteria with an important medical role therefore remains a priority.

Funding sources

This research is funded by the Agence Nationale de la Recherche as part of the Méditerranée Infection 10-IAHU-03 project.

Conflict of interest

No conflict of interest has been declared.

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Open Access

Peer-reviewed

Research Article

Archaeology in space: The Sampling Quadrangle Assemblages Research Experiment (SQuARE) on the International Space Station. Report 1: Squares 03 and 05

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Art, Chapman University, Orange, CA, United States of America, Space Engineering Research Center, University of Southern California, Marina del Rey, CA, United States of America

Roles Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of History, Carleton University, Ottawa, ON, United States of America

Roles Conceptualization, Data curation, Methodology, Project administration, Supervision, Writing – review & editing

Affiliation College of Humanities, Arts and Social Sciences, Flinders University, Adelaide, Australia

Roles Software, Writing – original draft

Roles Investigation, Writing – original draft

Affiliation Archaeology Research Center, University of Southern California, Los Angeles, CA, United States of America

• Justin St. P. Walsh, 
• Shawn Graham, 
• Alice C. Gorman, 
• Chantal Brousseau, 
• Salma Abdullah

• Published: August 7, 2024
• https://doi.org/10.1371/journal.pone.0304229
• Reader Comments

Between January and March 2022, crew aboard the International Space Station (ISS) performed the first archaeological fieldwork in space, the Sampling Quadrangle Assemblages Research Experiment (SQuARE). The experiment aimed to: (1) develop a new understanding of how humans adapt to life in an environmental context for which we are not evolutionarily adapted, using evidence from the observation of material culture; (2) identify disjunctions between planned and actual usage of facilities on a space station; (3) develop and test techniques that enable archaeological research at a distance; and (4) demonstrate the relevance of social science methods and perspectives for improving life in space. In this article, we describe our methodology, which involves a creative re-imagining of a long-standing sampling practice for the characterization of a site, the shovel test pit. The ISS crew marked out six sample locations (“squares”) around the ISS and documented them through daily photography over a 60-day period. Here we present the results from two of the six squares: an equipment maintenance area, and an area near exercise equipment and the latrine. Using the photographs and an innovative webtool, we identified 5,438 instances of items, labeling them by type and function. We then performed chronological analyses to determine how the documented areas were actually used. Our results show differences between intended and actual use, with storage the most common function of the maintenance area, and personal hygiene activities most common in an undesignated area near locations for exercise and waste.

Citation: Walsh JSP, Graham S, Gorman AC, Brousseau C, Abdullah S (2024) Archaeology in space: The Sampling Quadrangle Assemblages Research Experiment (SQuARE) on the International Space Station. Report 1: Squares 03 and 05. PLoS ONE 19(8): e0304229. https://doi.org/10.1371/journal.pone.0304229

Editor: Peter F. Biehl, University of California Santa Cruz, UNITED STATES OF AMERICA

Received: March 9, 2024; Accepted: May 7, 2024; Published: August 7, 2024

Copyright: © 2024 Walsh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: JW was the recipient of funding from Chapman University’s Office of Research and Sponsored Programs to support the activities of Axiom Space as implementation partner for the research presented in this article. There are no associated grant numbers for this financial support. Axiom Space served in the role of a contractor hired by Chapman University for the purpose of overseeing logistics relating to our research. In-kind support in the form of ISS crew time and access to the space station’s facilities, also awarded to JW from the ISS National Laboratory, resulted from an unsolicited proposal, and therefore there is no opportunity title or number associated with our work. No salary was received by any of the investigators as a result of the grant support. No additional external funding was received for this study.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The International Space Station Archaeological Project (ISSAP) aims to fill a gap in social science investigation into the human experience of long-duration spaceflight [ 1 – 3 ]. As the largest, most intensively inhabited space station to date, with over 270 visitors from 23 countries during more than 23 years of continuous habitation, the International Space Station (ISS) is the ideal example of a new kind of spacefaring community—“a microsociety in a miniworld” [ 4 ]. While it is possible to interview crew members about their experiences, the value of an approach focused on material culture is that it allows identification of longer-term patterns of behaviors and associations that interlocutors are unable or even unwilling to articulate. In this respect, we are inspired by previous examples of contemporary archaeology such as the Tucson Garbage Project and the Undocumented Migration Project [ 5 – 7 ]. We also follow previous discussions of material culture in space contexts that highlight the social and cultural features of space technology [ 8 , 9 ].

Our primary goal is to identify how humans adapt to life in a new environment for which our species has not evolved, one characterized by isolation, confinement, and especially microgravity. Microgravity introduces opportunities, such as the ability to move and work in 360 degrees, and to carry out experiments impossible in full Earth gravity, but also limitations, as unrestrained objects float away. The most routine activities carried out on Earth become the focus of intense planning and technological intervention in microgravity. By extension, our project also seeks to develop archaeological techniques that permit the study of other habitats in remote, extreme, or dangerous environments [ 10 , 11 ]. Since it is too costly and difficult to visit our archaeological site in person, we have to creatively re-imagine traditional archaeological methods to answer key questions. To date, our team has studied crew-created visual displays [ 12 , 13 ], meanings and processes associated with items returned to Earth [ 14 ], distribution of different population groups around the various modules [ 15 ], and the development of machine learning (ML) computational techniques to extract data about people and places, all from historic photographs of life on the ISS [ 16 ].

From January to March 2022, we developed a new dataset through the first archaeological work conducted off-Earth. We documented material culture in six locations around the ISS habitat, using daily photography taken by the crew which we then annotated and studied as evidence for changes in archaeological assemblages of material culture over time. This was the first time such data had been captured in a way that allowed statistical analysis. Here, we present the data and results from Squares 03 and 05, the first two sample locations to be completed.

Materials and methods

Square concept and planning.

Gorman proposed the concept behind the investigation, deriving it from one of the most traditional terrestrial archaeological techniques, the shovel test pit. This method is used to understand the overall characteristics of a site quickly through sampling. A site is mapped with a grid of one-meter squares. Some of the squares are selected for initial excavation to understand the likely spatial and chronological distribution of features across the entire site. In effect, the technique is a way to sample a known percentage of the entire site systematically. In the ISS application of this method, we documented a notional stratigraphy through daily photography, rather than excavation.

Historic photography is a key dataset for the International Space Station Archaeological Project. Tens of thousands of images have been made available to us, either through publication [ 17 ], or through an arrangement with the ISS Research Integration Office, which supplied previously unpublished images from the first eight years of the station’s habitation. These photographs are informative about the relationships between people, places, and objects over time in the ISS. However, they were taken randomly (from an archaeological perspective) and released only according to NASA’s priorities and rules. Most significantly, they were not made with the purpose of answering archaeological questions. By contrast, the photographs taken during the present investigation were systematic, representative of a defined proportion of the habitat’s area, and targeted towards capturing archaeology’s primary evidence: material culture. We were interested in how objects move around individual spaces and the station, what these movements revealed about crew adherence to terrestrial planning, and the creative use of material culture to make the laboratory-like interior of the ISS more habitable.

Access to the field site was gained through approval of a proposal submitted to the Center for the Advancement of Science in Space (also known as the ISS National Laboratory [ISS NL]). Upon acceptance, Axiom Space was assigned as the Implementation Partner for carriage of the experiment according to standard procedure. No other permits were required for this work.

Experiment design

Since our work envisioned one-meter sample squares, and recognizing the use of acronyms as a persistent element of spacefaring culture, we named our payload the Sampling Quadrangle Assemblages Research Experiment (SQuARE). Permission from the ISS NL to conduct SQuARE was contingent on using equipment that was already on board the space station. SQuARE required only five items: a camera, a wide-angle lens, adhesive tape (for marking the boundaries of the sample locations), a ruler (for scale), and a color calibration card (for post-processing of the images). All of these were already present on the ISS.

Walsh performed tests on the walls of a terrestrial art gallery to assess the feasibility of creating perfect one-meter squares in microgravity. He worked on a vertical surface, using the Pythagorean theorem to determine where the corners should be located. The only additional items used for these tests were two metric measuring tapes and a pencil for marking the wall (these were also already on the ISS). While it was possible to make a square this way, it also became clear that at least two people were needed to manage holding the tape measures in position while marking the points for the corners. This was not possible in the ISS context.

Walsh and Gorman identified seven locations for the placement of squares. Five of these were in the US Orbital Segment (USOS, consisting of American, European, and Japanese modules) and two in the Russian Orbital Segment. Unfortunately, tense relations between the US and Russian governments meant we could only document areas in the USOS. The five locations were (with their SQuARE designations):

• 01—an experimental rack on the forward wall, starboard end, of the Japanese Experiment Module
• 02—an experimental rack on the forward wall, port end, of the European laboratory module Columbus
• 03—the starboard Maintenance Work Area (workstation) in the US Node 2 module
• 04—the wall area “above” (according to typical crew body orientation) the galley table in the US Node 1 module
• 05—the aft wall, center location, of the US Node 3 module

Our square selection encompassed different modules and activities, including work and leisure. We also asked the crew to select a sixth sample location based on their understanding of the experiment and what they thought would be interesting to document. They chose a workstation on the port wall of the US laboratory module, at the aft end, which they described in a debriefing following their return to Earth in June 2022 as “our central command post, like our shared office situation in the lab.” Results from the four squares not included here will appear in future publications.

Walsh worked with NASA staff to determine payload procedures, including precise locations for the placement of the tape that would mark the square boundaries. The squares could not obstruct other facilities or experiments, so (unlike in terrestrial excavations, where string is typically used to demarcate trench boundaries) only the corners of each square were marked, not the entire perimeter. We used Kapton tape due to its bright yellow-orange color, which aided visibility for the crew taking photographs and for us when cropping the images. In practice, due to space constraints, the procedures that could actually be performed by crew in the ISS context, and the need to avoid interfering with other ongoing experiments, none of the locations actually measured one square meter or had precise 90° corners like a trench on Earth.

On January 14, 2022, NASA astronaut Kayla Barron set up the sample locations, marking the beginning of archaeological work in space ( S1 Movie ). For 30 days, starting on January 21, a crew member took photos of the sample locations at approximately the same time each day; the process was repeated at a random time each day for a second 30-day period to eliminate biases. Photography ended on March 21, 2022. The crew were instructed not to move any items prior to taking the photographs. Walsh led image management, including color and barrel distortion correction, fixing the alignment of each image, and cropping them to the boundaries of the taped corners.

Data processing—Item tagging, statistics, visualizations

We refer to each day’s photo as a “context” by analogy with chronologically-linked assemblages of artifacts and installations at terrestrial archaeological sites ( S1 and S2 Datasets). As previously noted, each context represented a moment roughly 24 hours distant from the previous one, showing evidence of changes in that time. ISS mission planners attempted to schedule the activity at the same time in the first month, but there were inevitable changes due to contingencies. Remarkably, the average time between contexts in Phase 1 was an almost-perfect 24h 0m 13s. Most of the Phase 1 photos were taken between 1200 and 1300 GMT (the time zone in which life on the ISS is organized). In Phase 2, the times were much more variable, but the average time between contexts during this period was still 23h 31m 45s. The earliest Phase 2 photo was taken at 0815 GMT, and the latest at 2101. We did not identify any meaningful differences between results from the two phases.

Since the “test pits” were formed of images rather than soil matrices, we needed a tool to capture information about the identity, nature, and location of every object. An open-source image annotator platform [ 18 ] mostly suited our needs. Brousseau rebuilt the platform to work within the constraints of our access to the imagery (turning it into a desktop tool with secure access to our private server), to permit a greater range of metadata to be added to each item or be imported, to autosave, and to export the resulting annotations. The tool also had to respect privacy and security limitations required by NASA.

The platform Brousseau developed and iterated was rechristened “Rocket-Anno” ( S1 File ). For each context photograph, the user draws an outline around every object, creating a polygon; each polygon is assigned a unique ID and the user provides the relevant descriptive information, using a controlled vocabulary developed for ISS material culture by Walsh and Gorman. Walsh and Abdullah used Rocket-Anno to tag the items in each context for Squares 03 and 05. Once all the objects were outlined for every context’s photograph, the tool exported a JSON file with all of the metadata for both the images themselves and all of the annotations, including the coordinate points for every polygon ( S3 Dataset ). We then developed Python code using Jupyter “notebooks” (an interactive development environment) that ingests the JSON file and generates dataframes for various facets of the data. Graham created a “core” notebook that exports summary statistics, calculates Brainerd-Robinson coefficients of similarity, and visualizes the changing use of the square over time by indicating use-areas based on artifact types and subtypes ( S2 File ). Walsh and Abdullah also wrote detailed square notes with context-by-context discussions and interpretations of features and patterns.

We asked NASA for access to the ISS Crew Planner, a computer system that shows each astronaut’s tasks in five-minute increments, to aid with our interpretation of contexts, but were denied. As a proxy, we use another, less detailed source: the ISS Daily Summary Reports (DSRs), published on a semi-regular basis by NASA on its website [ 19 ]. Any activities mentioned in the DSRs often must be connected with a context by inference. Therefore, our conclusions are likely less precise than if we had seen the Crew Planner, but they also more clearly represent the result of simply observing and interpreting the material culture record.

The crew during our sample period formed ISS Expedition 66 (October 2021-March 2022). They were responsible for the movement of objects in the sample squares as they carried out their daily tasks. The group consisted of two Russians affiliated with Roscosmos (the Russian space agency, 26%), one German belonging to the European Space Agency (ESA, 14%), and four Americans employed by NASA (57%). There were six men (86%) and one woman (14%), approximately equivalent to the historic proportions in the ISS population (84% and 16%, respectively). The Russian crew had their sleeping quarters at the aft end of the station, in the Zvezda module. The ESA astronaut slept in the European Columbus laboratory module. The four NASA crew slept in the US Node 2 module (see below). These arrangements emphasize the national character of discrete spaces around the ISS, also evident in our previous study of population distributions [ 15 ]. Both of the sample areas in this study were located in US modules.

Square 03 was placed in the starboard Maintenance Work Area (MWA, Fig 1 ), one of a pair of workstations located opposite one another in the center of the Node 2 module, with four crew berths towards the aft and a series of five ports for the docking of visiting crew/cargo vehicles and two modules on the forward end ( Fig 2 ). Node 2 (sometimes called “Harmony”) is a connector that links the US, Japanese, and European lab modules. According to prevailing design standards when the workstation was developed, an MWA “shall serve as the primary location for servicing and repair of maximum sized replacement unit/system components” [ 20 ]. Historic images published by NASA showing its use suggested that its primary function was maintenance of equipment and also scientific work that did not require a specific facility such as a centrifuge or furnace.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

An open crew berth is visible at right. The yellow dotted line indicates the boundaries of the sample area. Credit: NASA/ISSAP.

https://doi.org/10.1371/journal.pone.0304229.g001

Credit: Tor Finseth, by permission, modified by Justin Walsh.

https://doi.org/10.1371/journal.pone.0304229.g002

Square 03 measured 90.3 cm (top) x 87.8 (left) x 89.4 (bottom) x 87.6 (right), for an area of approximately 0.79 m 2 . Its primary feature was a blue metal panel with 40 square loop-type Velcro patches arranged in four rows of ten. During daily photography, many items were attached to the Velcro patches (or held by a clip or in a resealable bag which had its own hook-type Velcro). Above and below the blue panel were additional Velcro patches placed directly on the white plastic wall surface. These patches were white, in different sizes and shapes and irregularly arranged, indicating that they had been placed on the wall in response to different needs. Some were dirty, indicating long use. The patches below the blue panel were rarely used during the sample period, but the patches above were used frequently to hold packages of wet wipes, as well as resealable bags with electrostatic dispersion kits and other items. Outside the sample area, the primary features were a crew berth to the right, and a blue metal table attached to the wall below. This table, the primary component of the MWA, “provides a rigid surface on which to perform maintenance tasks,” according to NASA [ 21 ]. It is modular and can be oriented in several configurations, from flat against the wall to horizontal ( i . e ., perpendicular to the wall). A laptop to the left of the square occasionally showed information about work happening in the area.

In the 60 context photos of Square 03, we recorded 3,608 instances of items, an average of 60.1 (median = 60.5) per context. The lowest count was 24 in context 2 (where most of the wall was hidden from view behind an opaque storage bag), and the highest was 75 in both contexts 20 and 21. For comparison between squares, we can also calculate the item densities per m 2 . The average count was 76.1/m 2 (minimum = 30, maximum = 95). The count per context ( Fig 3(A)) began much lower than average in the first three contexts because of a portable glovebag and a stowage bag that obscured much of the sample square. It rose to an above-average level which was sustained (with the exception of contexts 11 and 12, which involved the appearance of another portable glovebag) until about context 43, when the count dipped again and the area seemed to show less use. Contexts 42–59 showed below-average numbers, as much as 20% lower than previously.

(a) Count of artifacts in Square 03 over time. (b) Proportions of artifacts by function in Square 03. Credit: Rao Hamza Ali.

https://doi.org/10.1371/journal.pone.0304229.g003

74 types of items appeared at least once here, belonging to six categories: equipment (41%), office supplies (31%), electronic (17%), stowage (9%), media (1%), and food (<1%). To better understand the significance of various items in the archaeological record, we assigned them to functional categories ( Table 1 , Fig 3(B)) . 35% of artifacts were restraints, or items used for holding other things in place; 12% for tools; 9% for containers; 9% for writing items; 6% for audiovisual items; 6% for experimental items; 4% for lights; 4% for safety items; 4% for body maintenance; 4% for power items; 3% for computing items; 1% for labels; and less than 1% drinks. We could not identify a function for two percent of the items.

https://doi.org/10.1371/journal.pone.0304229.t001

One of the project goals is understanding cultural adaptations to the microgravity environment. We placed special attention on “gravity surrogates,” pieces of (often simple) technology that are used in space to replicate the terrestrial experience of things staying where they are placed. Gravity surrogates include restraints and containers. It is quite noticeable that gravity surrogates comprise close to half of all items (44%) in Square 03, while the tools category, which might have been expected to be most prominent in an area designated for maintenance, is less than one-third as large (12%). Adding other groups associated with work, such as “experiment” and “light,” only brings the total to 22%.

Square 05 (Figs 2 and 4 ) was placed in a central location on the aft wall of the multipurpose Node 3 (“Tranquility”) module. This module does not include any specific science facilities. Instead, there are two large pieces of exercise equipment, the TVIS (Treadmill with Vibration Isolation Stabilization System, on the forward wall at the starboard end), and the ARED (Advanced Resistive Exercise Device, on the overhead wall at the port end). Use of the machines forms a significant part of crew activities, as they are required to exercise for two hours each day to counteract loss of muscle mass and bone density, and enable readjustment to terrestrial gravity on their return. The Waste and Hygiene Compartment (WHC), which includes the USOS latrine, is also here, on the forward wall in the center of the module, opposite Square 05. Finally, three modules are docked at Node 3’s port end. Most notable is the Cupola, a kind of miniature module on the nadir side with a panoramic window looking at Earth. This is the most popular leisure space for the crew, who often describe the hours they spend there. The Permanent Multipurpose Module (PMM) is docked on the forward side, storing equipment, food, and trash. In previous expeditions, some crew described installing a curtain in the PMM to create a private space for changing clothes and performing body maintenance activities such as cleaning oneself [ 22 , 23 ], but it was unclear whether that continued to be its function during the expedition we observed. One crew member during our sample period posted a video on Instagram showing the PMM interior and their efforts to re-stow equipment in a bag [ 24 ]. The last space attached to Node 3 is an experimental inflatable module docked on the aft side, called the Bigelow Expandable Activity Module (BEAM), which is used for storage of equipment.

The yellow dotted line indicates the boundaries of the sample area. The ARED machine is at the far upper right, on the overhead wall. The TVIS treadmill is outside this image to the left, on the forward wall. The WHC is directly behind the photographer. Credit: NASA/ISSAP.

https://doi.org/10.1371/journal.pone.0304229.g004

Square 05 was on a mostly featureless wall, with a vertical handrail in the middle. Handrails are metal bars located throughout the ISS that are used by the crew to hold themselves in place or provide a point from which to propel oneself to another location. NASA’s most recent design standards acknowledge that “[t]hey also serve as convenient locations for temporary mounting, affixing, or restraint of loose equipment and as attachment points for equipment” [ 25 ]. The handrail in Square 05 was used as an impromptu object restraint when a resealable bag filled with other bags was squeezed between the handrail and the wall.

The Brine Processing Assembly (BPA), a white plastic box which separates water from other components of urine for treatment and re-introduction to the station’s drinkable water supply [ 26 ], was fixed to the wall outside the square boundaries at lower left. A bungee cord was attached to both sides of the box; the one on the right was connected at its other end to the handrail attachment bracket. Numerous items were attached to or wedged into this bungee cord during the survey, bringing “gravity” into being. A red plastic duct ran through the square from top center into the BPA. This duct led from the latrine via the overhead wall. About halfway through the survey period, in context 32, the duct was wrapped in Kapton tape. According to the DSR for that day, “the crew used duct tape [ sic ] to make a seal around the BPA exhaust to prevent odor permeation in the cabin” [ 27 ], revealing an aspect of the crew’s experience of this area that is captured only indirectly in the context photograph. Permanently attached to the wall were approximately 20 loop-type Velcro patches in many shapes and sizes, placed in a seemingly random pattern that likely indicates that they were put there at different times and for different reasons.

Other common items in Square 05 were a mirror, a laptop computer, and an experimental item belonging to the German space agency DLR called the Touch Array Assembly [ 28 ]. The laptop moved just three times, and only by a few centimeters each time, during the sample period. The Touch Array was a black frame enclosing three metal surfaces which were being tested for their bacterial resistance; members of the crew touched the surfaces at various moments during the sample period. Finally, and most prominent due to its size, frequency of appearance, and use (judged by its movement between context photos) was an unidentified crew member’s toiletry kit.

By contrast with Square 03, 05 was the most irregular sample location, roughly twice as wide as it was tall. Its dimensions were 111 cm (top) x 61.9 (left) x 111.4 (bottom) x 64.6 (right), for an area of approximately 0.7 m 2 , about 89% of Square 03. We identified 1,830 instances of items in the 60 contexts, an average of 30.5 (median = 32) per context. The minimum was 18 items in context 5, and the maximum was 39 in contexts 24, 51, and 52. The average item density was 43.6/m 2 (minimum = 26, maximum = 56), 57% of Square 03.

The number of items trended upward throughout the sample period ( Fig 5(A)) . The largest spike occurred in context 6 with the appearance of the toiletry kit, which stored (and revealed) a number of related items. The kit can also be linked to one of the largest dips in item count, seen from contexts 52 to 53, when it was closed (but remained in the square). Other major changes can often be attributed to the addition and removal of bungee cords, which had other items such as carabiners and brackets attached. For example, the dip seen in context 25 correlates with the removal of a bungee cord with four carabiners.

(a) Count of artifacts and average count in Square 05 over time. (b) Proportions of artifacts by function in Square 05. Credit: Rao Hamza Ali.

https://doi.org/10.1371/journal.pone.0304229.g005

41 different item types were found in Square 05, about 55% as many as in Square 03. These belonged to five different categories: equipment (63%), electronic (17%), stowage (10%), office supplies (5%), and food (2%). The distribution of function proportions was quite different in this sample location ( Table 2 and Fig 5(B)) . Even though restraints were still most prominent, making up 32% of all items, body maintenance was almost as high (30%), indicating how strongly this area was associated with the activity of cleaning and caring for oneself. Computing (8%, represented by the laptop, which seems not to have been used), power (8%, from various cables), container (7%, resealable bags and Cargo Transfer Bags), and hygiene (6%, primarily the BPA duct) were the next most common items. Experiment was the function of 4% of the items, mostly the Touch Array, which appeared in every context, followed by drink (2%) and life support (1%). Safety, audiovisual, food, and light each made up less than 1% of the functional categories.

https://doi.org/10.1371/journal.pone.0304229.t002

Tracking changes over time is critical to understanding the activity happening in each area. We now explore how the assemblages change by calculating the Brainerd-Robinson Coefficient of Similarity [ 29 , 30 ] as operationalized by Peeples [ 31 , 32 ]. This metric is used in archaeology for comparing all pairs of the contexts by the proportions of categorical artifact data, here functional type. Applying the coefficient to the SQuARE contexts enables identification of time periods for distinct activities using artifact function and frequency alone, independent of documentary or oral evidence.

Multiple phases of activities took place in the square. Moments of connected activity are visible as red clusters in contexts 0–2, 11–12, 28–32, and 41 ( Fig 6(A)) . Combining this visualization with close observation of the photos themselves, we argue that there are actually eight distinct chronological periods.

• Contexts 0–2: Period 1 (S1 Fig in S3 File ) is a three-day period of work involving a portable glovebag (contexts 0–1) and a large blue stowage bag (context 2). It is difficult to describe trends in functional types because the glovebag and stowage bag obstruct the view of many objects. Items which appear at the top of the sample area, such as audiovisual and body maintenance items, are overemphasized in the data as a result. It appears that some kind of science is happening here, perhaps medical sample collection due to the presence of several small resealable bags visible in the glovebag. The work appears particularly intense in context 1, with the positioning of the video camera and light to point into the glovebag. These items indicate observation and oversight of crew activities by ground control. A white cargo transfer bag for storage and the stowage bag for holding packing materials in the context 2 photo likely relate to the packing of a Cargo Dragon vehicle that was docked to Node 2. The Dragon departed from the ISS for Earth, full of scientific samples, equipment, and crew personal items, a little more than three hours after the context 2 photo was taken [ 33 ].
• Contexts 3–10: Period 2 (S2 Fig in S3 File ) was a “stable” eight-day period in the sample, when little activity is apparent, few objects were moved or transferred in or out the square, and the primary function of the area seems to be storage rather than work. In context 6, a large Post-It notepad appeared in the center of the metal panel with a phone number written on it. This number belonged to another astronaut, presumably indicating that someone on the ISS had been told to call that colleague on the ground (for reasons of privacy, and in accordance with NASA rules for disseminating imagery, we have blurred the number in the relevant images). In context 8, the same notepad sheet had new writing appear on it, this time reading “COL A1 L1,” the location of an experimental rack in the European lab module.
• Contexts 11–12: Period 3 (S3 Fig in S3 File ) involves a second appearance of a portable glovebag (a different one from that used in contexts 0–1, according to its serial number), this time for a known activity, a concrete hardening experiment belonging to the European Space Agency [ 34 , 35 ]. This two-day phase indicates how the MWA space can be shared with non-US agencies when required. It also demonstrates the utility of this flexible area for work beyond biology/medicine, such as material science. Oversight of the crew’s activities by ground staff is evident from the positioning of the video camera and LED light pointing into the glovebag.
• Contexts 13–27: Period 4 (S4 Fig in S3 File ) is another stable fifteen-day period, similar to Period 2. Many items continued to be stored on the aluminum panel. The LED light’s presence is a trace of the activity in Period 3 that persists throughout this phase. Only in context 25 can a movement of the lamp potentially be connected to an activity relating to one of the stored items on the wall: at least one nitrile glove was removed from a resealable bag behind the lamp. In general, the primary identifiable activity during Period 4 is storage.
• Contexts 28–32: Period 5 (S5 Fig in S3 File ), by contrast, represents a short period of five days of relatively high and diverse activity. In context 28, a Microsoft Hololens augmented reality headset appeared. According to the DSR for the previous day, a training activity called Sidekick was carried out using the headset [ 36 ]. The following day, a Saturday, showed no change in the quantity or type of objects, but many were moved around and grouped by function—adhesive tape rolls were placed together, tools were moved from Velcro patches into pouches or straightened, and writing implements were placed in a vertical orientation when previously they were tilted. Context 29 represents a cleaning and re-organization of the sample area, which is a common activity for the crew on Saturdays [ 37 ]. Finally, in context 32, an optical coherence tomography scanner—a large piece of equipment for medical research involving crew members’ eyes—appeared [ 38 ]. This device was used previously during the sample period, but on the same day as the ESA concrete experiment, so that earlier work seems to have happened elsewhere [ 39 ].
• Contexts 33–40: Period 6 (S6 Fig in S3 File ) is the third stable period, in which almost no changes are visible over eight days. The only sign of activity is a digital timer which was started six hours before the context 39 image was made and continued to run at least through context 42.
• Context 41: Period 7 (S7 Fig in S3 File ) is a single context in which medical sample collection may have occurred. Resealable bags (some holding others) appeared in the center of the image and at lower right. One of the bags at lower right had a printed label reading “Reservoir Containers.” We were not able to discern which type of reservoir containers the label refers to, although the DSR for the day mentions “[Human Research Facility] Generic Saliva Collection,” without stating the location for this work [ 40 ]. Evidence from photos of other squares shows that labeled bags could be re-used for other purposes, so our interpretation of medical activity for this context is not conclusive.
• Contexts 42–60: Period 8 (S8 Fig in S3 File ) is the last and longest period of stability and low activity—eighteen days in which no specific activity other than the storage of items can be detected. The most notable change is the appearance for the first time of a foil water pouch in the central part of the blue panel.

Visualization of Brainerd-Robinson similarity, compared context-by-context by item function, for (a) Square 03 and (b) Square 05. The more alike a pair of contexts is, the higher the coefficient value, with a context compared against itself where a value of 200 equals perfect similarity. The resulting matrix of coefficients is visualized on a scale from blue to red where blue is lowest and red is highest similarity. The dark red diagonal line indicates complete similarity, where each context is compared to itself. Dark blue represents a complete difference. Credit: Shawn Graham.

https://doi.org/10.1371/journal.pone.0304229.g006

In the standards used at the time of installation, “stowage space” was the sixth design requirement listed for the MWA after accessibility; equipment size capability; scratch-resistant surfaces; capabilities for electrical, mechanical, vacuum, and fluid support during maintenance; and the accommodation of diagnostic equipment [ 20 ]. Only capabilities for fabrication were listed lower than stowage. Yet 50 of the 60 contexts (83%) fell within stable periods where little or no activity is identifiable in Square 03. According to the sample results, therefore, this area seems to exist not for “maintenance,” but primarily for the storage and arrangement of items. The most recent update of the design standards does not mention the MWA, but states, “Stowage location of tool kits should be optimized for accessibility to workstations and/or maintenance workbenches” [ 25 ]. Our observation confirms the importance of this suggestion.

The MWA was also a flexible location for certain science work, like the concrete study or crew health monitoring. Actual maintenance of equipment was hardly in evidence in the sample (possibly contexts 25, 39, and 44), and may not even have happened at all in this location. Some training did happen here, such as review of procedures for the Electromagnetic Levitator camera (instructions for changing settings on a high-speed camera appeared on the laptop screen; the day’s DSR shows that this camera is part of the Electromagnetic Levitator facility, located in the Columbus module [ 41 ]. The training required the use of the Hololens system (context 28 DSR, cited above).

Although many item types were represented in Square 03, it became clear during data capture how many things were basically static, unmoving and therefore unused, especially certain tools, writing implements, and body maintenance items. The MWA was seen as an appropriate place to store these items. It may be the case that their presence here also indicates that their function was seen as an appropriate one for this space, but the function(s) may not be carried out—or perhaps not in this location. Actualization of object function was only visible to us when the state of the item changed—it appeared, it moved, it changed orientation, it disappeared, or, in the case of artifacts that were grouped in collections rather than found as singletons, its shape changed or it became visibly smaller/lesser. We therefore have the opportunity to explore not only actuality of object use, but also potentiality of use or function, and the meaning of that quality for archaeological interpretation [ 42 , 43 ]. This possibility is particularly intriguing in light of the archaeological turn towards recognizing the agency of objects to impact human activity [ 44 , 45 ]. We will explore these implications in a future publication.

We performed the same chronological analysis for Square 05. Fig 6(B) represents the analysis for both item types and for item functions. We identified three major phases of activity, corresponding to contexts 0–5, 6–52, and 53–59 (S9-S11 Figs in S3 File ). The primary characteristics of these phases relate to an early period of unclear associations (0–5) marked by the presence of rolls of adhesive tape and a few body maintenance items (toothpaste and toothbrush, wet wipes); the appearance of a toiletry kit on the right side of the sample area, fully open with clear views of many of the items contained within (6–52); and finally, the closure of the toiletry kit so that its contents can no longer be seen (53–59). We interpret the phases as follows:

• Contexts 0–5: In Period 1 (six days, S9 Fig in S3 File ), while items such as a mirror, dental floss picks, wet wipes, and a toothbrush held in the end of a toothpaste tube were visible, the presence of various other kinds of items confounds easy interpretation. Two rolls of duct tape were stored on the handrail in the center of the sample area, and the Touch Array and laptop appeared in the center. Little movement can be identified, apart from a blue nitrile glove that appeared in context 1 and moved left across the area until it was wedged into the bungee cord for contexts 3 and 4. The tape rolls were removed prior to context 5. A collection of resealable bags was wedged behind the handrail in context 3, remaining there until context 9. Overall, this appears to be a period characterized by eclectic associations, showing an area without a clear designated function.
• Contexts 6–52: Period 2 (S10 Fig in S3 File ) is clearly the most significant one for this location due to its duration (47 days). It was dominated by the number of body maintenance items located in and around the toiletry kit, especially a white hand towel (on which a brown stain was visible from context 11, allowing us to confirm that the same towel was present until context 46). A second towel appeared alongside the toiletry kit in context 47, and the first one was fixed at the same time to the handrail, where it remained through the end of the sample period. A third towel appeared in context 52, attached to the handrail together with the first one by a bungee cord, continuing to the end of the sample period. Individual body maintenance items moved frequently from one context to the next, showing the importance of this type of activity for this part of Node 3. For reasons that are unclear, the mirror shifted orientation from vertical to diagonal in context 22, and then was put back in a vertical orientation in context 31 (a Monday, a day which is not traditionally associated with cleaning and organization). Collections of resealable bags appeared at various times, including a large one labeled “KYNAR BAG OF ZIPLOCKS” in green marker at the upper left part of the sample area beginning of context 12 (Kynar is a non-flammable plastic material that NASA prefers for resealable bags to the generic commercial off-the-shelf variety because it is non-flammable; however, its resistance to heat makes it less desirable for creating custom sizes, so bags made from traditional but flammable low-density polyethylene still dominate on the ISS [ 14 ]). The Kynar bag contained varying numbers of bags within it over time; occasionally, it appeared to be empty. The Touch Array changed orientation on seven of 47 days in period 2, or 15% of the time (12% of all days in the survey), showing activity associated with scientific research in this area. In context 49, a life-support item, the Airborne Particulate Monitor (APM) was installed [ 46 ]. This device, which measures “real-time particulate data” to assess hazards to crew health [ 47 ], persisted through the end of the sample period.
• Contexts 53–59: Period 3 (S11 Fig in S3 File ) appears as a seven-day phase marked by low activity. Visually, the most notable feature is the closure of the toiletry kit, which led to much lower counts of body maintenance items. Hardly any of the items on the wall moved at all during this period.

While body maintenance in the form of cleaning and caring for oneself could be an expected function for an area with exercise and excretion facilities, it is worth noting that the ISS provides, at most, minimal accommodation for this activity. A description of the WHC stated, “To provide privacy…an enclosure was added to the front of the rack. This enclosure, referred to as the Cabin, is approximately the size of a typical bathroom stall and provides room for system consumables and hygiene item stowage. Space is available to also support limited hygiene functions such as hand and body washing” [ 48 ]. A diagram of the WHC in the same publication shows the Cabin without a scale but suggests that it measures roughly 2 m (h) x .75 (w) x .75 (d), a volume of approximately 1.125 m 3 . NASA’s current design standards state that the body volume of a 95th percentile male astronaut is 0.99 m 3 [ 20 ], meaning that a person of that size would take up 88% of the space of the Cabin, leaving little room for performing cleaning functions—especially if the Cabin is used as apparently intended, to also hold “system consumables and hygiene item[s]” that would further diminish the usable volume. This situation explains why crews try to adapt other spaces, such as storage areas like the PMM, for these activities instead. According to the crew debriefing statement, only one of them used the WHC for body maintenance purposes; it is not clear whether the toiletry kit belonged to that individual. But the appearance of the toiletry kit in Square 05—outside of the WHC, in a public space where others frequently pass by—may have been a response to the limitations of the WHC Cabin. It suggests a need for designers to re-evaluate affordances for body maintenance practices and storage for related items.

Although Square 03 and 05 were different sizes and shapes, comparing the density of items by function shows evidence of their usage ( Table 3 ). The typical context in Square 03 had twice as many restraints and containers, but less than one-quarter as many body maintenance items as Square 05. 03 also had many tools, lights, audiovisual equipment, and writing implements, while there were none of any of these types in 05. 05 had life support and hygiene items which were missing from 03. It appears that flexibility and multifunctionality were key elements for 03, while in 05 there was emphasis on one primary function (albeit an improvised one, designated by the crew rather than architects or ground control), cleaning and caring for one’s body, with a secondary function of housing static equipment for crew hygiene and life support.

https://doi.org/10.1371/journal.pone.0304229.t003

As this is the first time such an analysis has been performed, it is not yet possible to say how typical or unusual these squares are regarding the types of activities taking place; but they provide a baseline for eventual comparison with the other four squares and future work on ISS or other space habitats.

Some general characteristics are revealed by archaeological analysis of a space station’s material culture. First, even in a small, enclosed site, occupied by only a few people over a relatively short sample period, we can observe divergent patterns for different locations and activity phases. Second, while distinct functions are apparent for these two squares, they are not the functions that we expected prior to this research. As a result, our work fulfills the promise of the archaeological approach to understanding life in a space station by revealing new, previously unrecognized phenomena relating to life and work on the ISS. There is now systematically recorded archaeological data for a space habitat.

Squares 03 and 05 served quite different purposes. The reasons for this fact are their respective affordances and their locations relative to activity areas designated for science and exercise. Their national associations, especially the manifestation of the control wielded by NASA over its modules, also played a role in the use of certain materials, the placement of facilities, and the organization of work. How each area was used was also the result of an interplay between the original plans developed by mission planners and habitat designers (or the lack of such plans), the utility of the equipment and architecture in each location, and the contingent needs of the crew as they lived in the station. This interplay became visible in the station’s material culture, as certain areas were associated with particular behaviors, over time and through tradition—over the long duration across many crews (Node 2, location of Square 03, docked with the ISS in 2007, and Node 3, location of Square 05, docked in 2010), and during the specific period of this survey, from January to March 2022. During the crew debriefing, one astronaut said, “We were a pretty organized crew who was also pretty much on the same page about how to do things…. As time went on…we organized the lab and kind of got on the same page about where we put things and how we’re going to do things.” This statement shows how functional associations can become linked to different areas of the ISS through usage and mutual agreement. At the same time, the station is not frozen in time. Different people have divergent ideas about how and where to do things. It seems from the appearance of just one Russian item—a packet of generic wipes ( salfetky sukhiye ) stored in the toiletry kit throughout the sample period—that the people who used these spaces and carried out their functions did not typically include the ISS’s Russian crew. Enabling greater flexibility to define how spaces can be used could have a significant impact on improving crew autonomy over their lives, such as how and where to work. It could also lead to opening of all spaces within a habitat to the entire crew, which seems likely to improve general well-being.

An apparent disjunction between planned and actual usage appeared in Square 03. It is intended for maintenance as well as other kinds of work. But much of the time, there was nobody working here—a fact that is not captured by historic photos of the area, precisely because nothing is happening. The space has instead become the equivalent of a pegboard mounted on a wall in a home garage or shed, convenient for storage for all kinds of items—not necessarily items being used there—because it has an enormous number of attachment points. Storage has become its primary function. Designers of future workstations in space should consider that they might need to optimize for functions other than work, because most of the time, there might not be any work happening there. They could optimize for quick storage, considering whether to impose a system of organization, or allow users to organize as they want.

We expected from previous (though unsystematic) observation of historic photos and other research, that resealable plastic bags (combined with Velcro patches on the bags and walls) would be the primary means for creating gravity surrogates to control items in microgravity. They only comprise 7% of all items in Square 03 (256 instances). There are more than twice as many clips (572—more than 9 per context) in the sample. There were 193 instances of adhesive tape rolls, and more than 100 cable ties, but these were latent (not holding anything), representing potentiality of restraint rather than actualization. The squares showed different approaches to managing “gravity.” While Square 03 had a pre-existing structured array of Velcro patches, Square 05 showed a more expedient strategy with Velcro added in response to particular activities. Different needs require different affordances; creating “gravity” is a more nuanced endeavor than it initially appears. More work remains to be done to optimize gravity surrogates for future space habitats, because this is evidently one of the most critical adaptations that crews have to make in microgravity (44% of all items in Square 03, 39% in 05).

Square 05 is an empty space, seemingly just one side of a passageway for people going to use the lifting machine or the latrine, to look out of the Cupola, or get something out of deep storage in one of the ISS’s closets. In our survey, this square was a storage place for toiletries, resealable bags, and a computer that never (or almost never) gets used. It was associated with computing and hygiene simply by virtue of its location, rather than due to any particular facilities it possessed. It has no affordances for storage. There are no cabinets or drawers, as would be appropriate for organizing and holding crew personal items. A crew member decided that this was an appropriate place to leave their toiletry kit for almost two months. Whether this choice was appreciated or resented by fellow crew members cannot be discerned based on our evidence, but it seems to have been tolerated, given its long duration. The location of the other four USOS crew members’ toiletry kits during the sample period is unknown. A question raised by our observations is: how might a function be more clearly defined by designers for this area, perhaps by providing lockers for individual crew members to store their toiletries and towels? This would have a benefit not only for reducing clutter, but also for reducing exposure of toiletry kits and the items stored in them to flying sweat from the exercise equipment or other waste particles from the latrine. A larger compartment providing privacy for body maintenance and a greater range of motion would also be desirable.

As the first systematic collection of archaeological data from a space site outside Earth, this analysis of two areas on the ISS as part of the SQuARE payload has shown that novel insights into material culture use can be obtained, such as the use of wall areas as storage or staging posts between activities, the accretion of objects associated with different functions, and the complexity of using material replacements for gravity. These results enable better space station design and raise new questions that will be addressed through analysis of the remaining four squares.

Supporting information

S1 movie. nasa astronaut kayla barron installs the first square for the sampling quadrangle assemblages research experiment in the japanese experiment module (also known as kibo) on the international space station, january 14, 2022..

She places Kapton tape to mark the square’s upper right corner. Credit: NASA.

https://doi.org/10.1371/journal.pone.0304229.s001

S1 Dataset.

https://doi.org/10.1371/journal.pone.0304229.s002

S2 Dataset.

https://doi.org/10.1371/journal.pone.0304229.s003

S3 Dataset. The image annotations are represented according to sample square in json formatted text files.

The data is available in the ‘SQuARE-notebooks’ repository on Github.com in the ‘data’ subfolder at https://github.com/issarchaeologicalproject/SQuARE-notebooks/tree/main ; archived version of the repository is at Zenodo, DOI: 10.5281/zenodo.10654812 .

https://doi.org/10.1371/journal.pone.0304229.s004

S1 File. The ‘Rocket-Anno’ image annotation software is available on Github at https://github.com/issarchaeologicalproject/MRE-RocketAnno .

The archived version of the repository is at Zenodo, DOI: 10.5281/zenodo.10648399 .

https://doi.org/10.1371/journal.pone.0304229.s005

S2 File. The computational notebooks that process the data json files to reshape the data suitable for basic statistics as well as the computation of the Brainerd-Robinson coefficients of similarity are in the.ipynb notebook format.

The code is available in the ‘SQuARE-notebooks’ repository on Github.com in the ‘notebooks’ subfolder at https://github.com/issarchaeologicalproject/SQuARE-notebooks/tree/main ; archived version of the repository is at Zenodo, DOI: 10.5281/zenodo.10654812 . The software can be run online in the Google Colab environment ( https://colab.research.google.com ) or any system running Jupyter Notebooks ( https://jupyter.org/ ).

https://doi.org/10.1371/journal.pone.0304229.s006

https://doi.org/10.1371/journal.pone.0304229.s007

Acknowledgments

We thank Chapman University’s Office of Research and Sponsored Programs, and especially Dr. Thomas Piechota and Dr. Janeen Hill, for funding the Implementation Partner costs associated with the SQuARE payload. Chapman’s Leatherby Libraries’ Supporting Open Access Research and Scholarship (SOARS) program funded the article processing fee for this publication. Ken Savin and Ken Shields at the ISS National Laboratory gave major support by agreeing to sponsor SQuARE and providing access to ISS NL’s allocation of crew time. David Zuniga and Kryn Ambs at Axiom Space were key collaborators in managing payload logistics. NASA staff and contractors were critical to the experiment’s success, especially Kristen Fortson, Jay Weber, Crissy Canerday, Sierra Wolbert, and Jade Conway. We also gratefully acknowledge the help and resources provided by Dr. Erik Linstead, director of the Machine Learning and Affiliated Technology Lab at Chapman University. Aidan St. P. Walsh corrected the color and lens barrel distortion in all of the SQuARE imagery. Rao Hamza Ali produced charts using accessible color combinations for Figs 3 and 5 . And finally, of course, we are extremely appreciative of the efforts of the five USOS members of the Expedition 66 crew on the ISS—Kayla Barron, Raja Chari, Thomas Marshburn, Matthias Maurer, and Mark Vande Hei—who were the first archaeologists in space.

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ORIGINAL RESEARCH article

Data science's cultural construction: qualitative ideas for quantitative work.

• Department of Sociology, Sciences Po/CSO, Paris, France

Introduction: “Data scientists” quickly became ubiquitous, often infamously so, but they have struggled with the ambiguity of their novel role. This article studies data science's collective definition on Twitter.

Methods: The analysis responds to the challenges of studying an emergent case with unclear boundaries and substance through a cultural perspective and complementary datasets ranging from 1,025 to 752,815 tweets. It brings together relations between accounts that tweeted about data science, the hashtags they used, indicating purposes, and the topics they discussed.

Results: The first results reproduce familiar commercial and technical motives. Additional results reveal concerns with new practical and ethical standards as a distinctive motive for constructing data science.

Discussion: The article provides a sensibility for local meaning in usually abstract datasets and a heuristic for navigating increasingly abundant datasets toward surprising insights. For data scientists, it offers a guide for positioning themselves vis-à-vis others to navigate their professional future.

1 Introduction

Digital transformation has impacted many areas of social life, including politics ( Schradie, 2019 ; Bail, 2021 ), news ( Christin, 2020 ), and the economy ( Zuboff, 2019 ), particularly through social media. The impacts differ, ranging from efficiency gains to polarization and misinformation, but they have in common the entanglement of the novel “data scientists” profession in these changes. This new role has remained obscure despite its salience and older foundations ( González-Bailón, 2017 ). While the ambiguity has likely had benefits for data science ( Dorschel and Brandt, 2021 ), data scientists have struggled with the lack of clarity ( Avnoon, 2021 ). This article asks how the emerging data scientist community has defined their novel role on social media and addresses methodological issues that come with studying an emergent case.

The problem is complicated as strategies of established professions are not immediately available to an emerging profession. Evidence shows how existing professions respond to the ongoing changes in organizational settings (see, e.g., Greenwood et al., 2002 ; Armour and Sako, 2020 ; Goto, 2021 ), but traces of data science's self-definition first appeared on the Internet in blog posts, or on Twitter. A now-classic tweet serves as an example and a working definition: “Data scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.” 1 The definition presents data science as an expert role and, read verbatim, gives a sense of the quantitative and coding skills this work entails, but it does not try to be comprehensive or entirely clear and demands that any systematic analysis reconciles local specificity and the phenomenon's global salience.

The immediate questions of how much software engineering a statistician has to know or which parts have been answered by various training programs and textbooks ( Schutt and O'Neil, 2013 ; Salganik, 2018 ; Saner, 2019 ; Dorschel and Brandt, 2021 ). A more puzzling question remains in the definition's imitation of a dictionary definition on social media, where that formalism was unnecessary and long before one existed in print. The style instead leveraged the lay view of expert work as jurisdictions of formal professions ( Freidson, 2001 ). It connects the problem of data science's construction to discussions in the literature on expert knowledge and work. This literature has long developed a nuanced understanding of professions as a system of competitors ( Abbott, 1988 ), emergent relational arrangements ( Eyal, 2013 ), and their organizational dimensions ( Muzio and Kirkpatrick, 2011 ). In contrast, the definition's playfully premature formalism highlights cultural processes underpinning emergent professions.

Culture has an everyday meaning and a technical meaning. Data scientists have recognized the role of culture in the everyday sense, at least sporadically and casually, in terms of “two cultures” in quantitative thinking ( Breiman, 2001 ) or the “culture of big data” ( Barlow, 2013 ). They mean characteristics of their work that do not follow purely technical or formal steps. Sociological theories of expert work acknowledge cultural processes in a more technical sense but often assign them less weight compared to other mechanisms, competition, informal relations, and organizational dynamics. Culture featured in Abbott's (1988) classic account in the background of the main argument as the “diagnosis, treatment, and inference” that jointly form the “cultural machinery of jurisdiction” ( Abbott, 1988 , p. 60). Culture also played an external role such as when public opinion creates problem areas that professions can claim as their jurisdictions ( Abbott, 1988 , ch.7). Fourcade's (2009) comprehensive analysis of economists and their history worked out this side in the interplay of economic culture and institutions, indicating that contexts shape economic theories, which, in turn, shape their environments.

Capturing meaning-making presents a unique challenge in an emergent setting where technological and economic forces converge with the ideas of professional pioneers. Cultural processes have shaped quantitative expertise for a long time ( Porter, 1986 , 1995 ; Desrosières, 1998 ), and data scientists have made a new iteration visible through their appearances in public discourse and popular culture. 2 Several studies have demonstrated the complexity of this outside relationship between experts, and their publics (e.g., Wynne, 1992 ; Epstein, 1996 ), which may in part stem from mismatching views as outsiders have low regard for the technically advanced knowledge that experts value ( Abbott, 1981 ). This article addresses its motivating question of how the data scientist community has defined their role from a cultural perspective that builds on Burke's (1945) notion of A Grammar of Motives . This modern interpretation, which John Mohr introduced as “computational hermeneutics” ( Mohr et al., 2013 ), extends research on expert work into the digital age and gives the intuition data scientists have had since their beginning a rigorous foundation.

The analysis integrates recent arguments for understanding culture in professions into novel computational procedures for formal measures of culture. Spillman and Brophy (2018 , p. 156) stressed the “implicit and explicit claims about the practical or craft knowledge” in addition to the common focus on abstract or technical expertise. Whereas, they illustrated their argument with reference to documentary and ethnographic analyses, this study moves to the digital context, where data scientists often discussed their role. It uses a large dataset of tweets to capture public discussions and draws on advances among scholars of culture around using computational social science techniques (see Edelmann et al., 2020 ). The focus in qualitative research on “vocabularies of motive about work” ( Spillman and Brophy, 2018 , p. 159) links to methodological ideas for recovering cultural features from large numbers of textual documents to reconstruct the meaning that actors assign to situations ( Mohr et al., 2013 , 2015 ).

This conceptual approach guides a computational analysis of data science's cultural construction. The combination informs an analytical strategy for studying expert work, meaning construction, and disputes on social media where they unfold in public. It is able to track meaning-making on different levels to capture data science's local definition and global salience. The results reveal data science within the larger changes of the digital era as a rhetorical strategy for circumventing established groups, their leaders, and legacies to adapt old skills to contemporary issues (see Frickel and Gross, 2005 ; Suddaby and Greenwood, 2005 ). They show an arrangement of actors and themes that suggests new ethical and technical ideas and practical challenges around implementing them as a previously unreported motive of data science's construction. To develop this argument, the article first introduces the data science case, the reflexive analytical approach, and the empirical strategy before summarizing and discussing the observations.

2 Data science as an emergent profession

Data scientists have told origin stories that centered on Facebook and LinkedIn in their early startup days, struggling to get users to connect and navigate the then-new world of social media ( Hammerbacher, 2009 ; Davenport and Patil, 2012 ), but the data science label first appeared in academic circles during the 1990s and early 2000s (e.g., Hayashi, 1998 ; Cleveland, 2001 ), and many underlying ideas are much older ( Donoho, 2015 ; González-Bailón, 2017 ). Data scientists recognize their ties to established quantitative expertise and present their integration of it with computer sciences as a distinguishing feature (e.g., Schutt and O'Neil, 2013 ).

Such origin stories and programmatic definitions do not necessarily spread along direct and linear paths. Historical research of quantitative work and thinking has shown how quantitative experts shared technical ideas about their work in ways that indicate cultural processes ( Porter, 1995 ), such as through “evidential cultures” of data analysis ( Collins, 1998 ). Following the practical work in social media startups during the mid to late 2000s, data science has spread into various industries and public services, all the way to the Obama administration ( Hammerbacher, 2009 ; Davenport and Patil, 2012 ; Lohr, 2015 ; Smith, 2015 ). Its appearance and diffusion indicate another iteration in the long and storied history of quantitative expertise as it extends into the digital age.

Sociological accounts of data scientists have studied data science from different perspectives, beginning with their emergence ( Brandt, 2016 ). Some research shows that data scientists struggle with integrating the multiple competencies and areas of expertise of their roles in their workplaces ( Avnoon, 2021 ). Other research suggests that precisely the ambiguities that undergird the data science role, at least on the level of the larger educational and economic fields, have advanced data science's professional recognition ( Börner et al., 2018 ; Dorschel and Brandt, 2021 ). Journalistic accounts of data science described socio-technical arrangements (e.g., Lohr, 2015 ), where the sociology of expertise would partly locate data science's roots ( Eyal, 2013 ). Social scientists have even reflected on their own relationship with data science, both conceptually, in STS ( Ribes, 2019 ), and practically, in quantitative research ( González-Bailón, 2017 ; Salganik, 2018 ), and stressed the threats to society ( O'Neil, 2016 ; Eubanks, 2018 ). These critical perspectives have initiated concerns with ethics among data scientists ( Loukides et al., 2018 ), another familiar step in the development of professions ( Abbott, 1983 ). The question of how data scientists resolve the ambiguity of their new role as a group a cultural process has remained unexplored.

3 Empirical strategy

3.1 a reflexive perspective.

The early discussions of data science on social media offer a promising opportunity for shedding further light on this new case, but an analysis of data science's cultural construction on social media faces challenges as some who contribute to it may not self-identify as data scientists, and new ideas may not immediately appear relevant. For example, some social scientists helped define data science without affiliating with the new group (e.g., González-Bailón, 2017 ; Salganik, 2018 ). This problem raises questions about the analyst's perspective, which anthropologists and sociologists discuss as reflexivity ( Gouldner, 1970 ; Geertz, 1988 ). Reflexivity has gained new attention and motivated the idea of “asymmetric comparisons,” wherein an analysis captures “the larger diversity in the world” ( Krause, 2021 , p. 9). These comparisons address the problems with an analysis of data science on social media by suggesting comparisons between narrower views of data science to broader observations that are missing initially.

Quantitative research often aims for representative samples and conceives of foregone observations as a problem of missing data that introduces biases. It has addressed that issue systematically for a long time (e.g., Kim and Curry, 1977 ; Little and Rubin, 2019 ). Assuming that all relevant variables are available, which quantitative methodologists acknowledge is not always the case, the main distinction is between missing information on single items for respondents and entire units that did not respond ( Loosveldt and Billiet, 2002 ; Peytchev, 2013 ). The debate further discusses missing data in specific areas of research, such as social networks, which raise questions about the completeness of the units used for studying them (e.g., Kossinets, 2006 ).

Both perspectives can help shed light on data science's formation. For an asymmetric data science comparison that the qualitative perspective counsels, the quantitative perspective would mean adding information on a set of data scientists for which some information may be missing. Such a case should consist of a larger network boundary to reveal the implication of the initial boundary decision. Finally, it seems unlikely that research subjects routinely discuss relevant social dynamics directly ( Jerolmack and Khan, 2014 ), especially as they still define their identity, such as data scientists. The boundary ( Laumann et al., 1983 ) needs to capture more and less overtly related types of content. This complication captures a specific challenge in the larger program of bringing qualitative ideas to quantitative research (e.g., Mützel, 2015 ; Evans and Foster, 2019 ; Brandt, 2023 ).

3.2 Observations and operationalization

This cultural analysis of data science's emergence on social media is part of a larger project that began with field observations of the early data science community in New York City between 2012 and 2015. Those observations covered public events where data scientists presented their work and views of the field. They captured data scientists from close proximity in an important setting but missed many other settings, as well as data science's ongoing construction after the fieldwork ended. This article analyzes the subsequent discussions of data science issues on Twitter, avoiding some constraints from in-person observations even as new limitations come up, which I discuss below. Twitter was ubiquitous in the community during the field observations, where data scientists often mentioned their Twitter accounts when they introduced themselves to audiences. I started following data scientists whom I encountered and added others that appeared in my timeline and seemed relevant. I avoided a general search to ensure consistency with the field observations that had identified central perspectives in the larger data science discussion.

The analysis follows Mohr et al. (2013) to reveal data science's cultural construction on Twitter as a “grammar of motives” that considers “what was done (act), when or where it was done (scene), who did it (agent), how [they] did it (agency [that is, by what means]), and why (purpose)” ( Burke, 1945 , p. xv). Mohr et al. (2013) proposed formal methods for extracting motives from quantitative data. On Twitter, the data scientists (and other users) are “actors,” and Twitter is the “agency” that allows individuals, organizations, and other groups to register, publish tweets of 280 characters or less, follow other accounts to see their tweets, and react to those tweets via liking them or responding. These activities were the “acts.” Both the acts and Twitter, as infrastructure, remained largely stable throughout this analysis and did, therefore, not contribute to an analysis of data science's ongoing construction. 3

Purposes and scenes are the relevant analytic dimensions in addition to the actors. The analysis identifies purposes through Twitter's hashtag functionality. Twitter allows users to include hashtags (#) followed by 1 grams, such as #ArabSpring, #MeToo, or #datascience. These hashtags highlight causes that a tweet seeks to promote and link to other tweets with the same hashtag. I use weighted log odds ratios to identify dominant purposes. For revealing “scenes,” Mohr et al. (2013) used text analytic methods, which I apply to tweet texts. Table 1 summarizes these connections between concepts, operationalization, and analytic techniques (columns 1, 2, and 7). The respective sections provide details on each technique. Together, they reveal key dimensions of data science's cultural construction on social media.

Table 1 . Sample design and raw data structure for asymmetrical comparison.

3.3 Data structure

Twitter's digital infrastructure offers access to vast observations. Concepts from the sociology of professions and expertise, outlined in the introduction, guided the original collection of relevant tweets, but the digital transformation has made vast observations of social activities easily accessible. To design an asymmetric comparison for a reflexive analysis ( Krause, 2021 ), I used Twitter's API to obtain the publicly available timelines of the accounts that posted the tweets in the initial dataset, the connections between accounts, and accounts missing from the initial dataset. The design responds to methodological concerns with capturing actors and what they have to say.

I introduce an intermediary comparison for better understanding the effect of changing boundary conditions and specifying data science's emergent contours. When developing his hermeneutic perspective, Burke (1945 , p. xix–xx) noted that “an agent might have [their] act modified (hence partly motivated) by friends (co-agents) or enemies (counter-agents).” In this reflexive analysis, my Twitter “friends”—Twitter-speak and Burke's conceptual language overlap for what network analysts call first-degree neighbors—may have captured a more focused discussion. 4 The idea of a counter-agent makes sense for the accounts that my ongoing observations missed in as far as they possibly covered a broader discussion. Social network analysis language refers to these accounts as second-degree neighbors. The subsequent analysis captures the “larger diversity in the world” ( Krause, 2021 ) by comparing (1) the patterns that emerge from the dataset of actively collected tweets to those of digitally obtained full timelines and, within those timelines, (2) patterns in friends tweets to those in strangers tweets, or first and second-degree neighbors.

The initial dataset consisted of the tweets that I collected from my timeline as insightful moments from the project's theoretical perspective, beginning in March 2017. This analysis includes tweets until March 2020, when the coronavirus pandemic took over much of the data science conversation. During this time, I manually collected 1,025 tweets from 395 accounts ( Table 1 , column 3). The next section summarizes their content. These observations missed the vast majority of tweets these users posted and shared. I obtained additional tweets by these users and their relations through the Twitter API ( Table 1 , columns 4–6). The resulting dataset includes 455,344 second-degree Twitter ties and a corpus of 752,815 tweets that explicitly indicated English as their language. 5

3.4 Data science on Twitter

This section summarizes data science-related tweets as a first illustration of how Twitter featured in data science's definition, capturing talk of positions, expertise, promises, and threats. Several tweets in the small dataset discussed jobs, which are critical for claiming an area of work ( Abbott, 1988 ). One tweet from November 2018 mentioned an opening in Facebook's Core Data Science team. Others advertised an opening at Detroit's Innovation Team to data scientists who look in that region, or a vacancy at MindGeek, which that tweet identified as the owner of an adult content website. 6 Many others commented on hiring issues, warning, for example, of a lack of demand or that those hiring data scientists mainly look for versions of themselves. Some were quite reflective, noting, for example, that “In my experience, people who [do] data science well tend to get PhDs, but the PhD itself is negative preparation for the job.” In a topic as straightforward as work, tweets can capture more nuance than the popular celebrations or critiques of their large demand capture.

Data science also involves technical expertise, which seems much harder to fit into tweets. Some tweets have taken a light take on methods, joking, for example, how someone may falsely underestimate their significance for data science or, conversely, that some use the common perception of methods as leading to rigor without understanding them. Others share more profound thoughts. Yann LeCun, a pioneer in artificial intelligence and the first director of NYU's data science institute, used the idea of methods across data work, painting, or musical composition to explain the meaning of deep learning. 7 As for the job tweets, these tweets develop technical data expertise instead of broadcasting simple lists of skills.

Many tweets that mentioned data science did not shed additional light on data science's professional construction. I recorded some of them, such as one in which Kirk Borne, a data science popularizer, announced a webinar and used many hashtags, presumably to increase its visibility. This tweet, and a few like it, entered the observations as a record of promotions that mentioned data science without developing its meaning.

The tweets so far illustrate how the data science community discussed the meaning of jobs or methods and their promise online. Other tweets problematized the question of the community itself. The idea of ethics in data science flared up occasionally, and prominently so in the fall of 2018 when well-known data scientists Hilary Mason and DJ Patil published a book titled Ethics and Data Science together with Mike Loukides ( Loukides et al., 2018 ). Another instance of community formation unfolded as a collective reaction to bullying when several data scientists spoke up against one account formally affiliated with data science for having bullied a member of their community. While these examples capture clear moments of community building, others remain more subtle.

This summary shows that Twitter served, at least in some instances, as a discursive space for defining data science. The subsequent analysis models the community's collective construction of data science on Twitter in terms of its underlying motives and across varying boundary specifications.

4 Analysis and results

The first analytical step considers actors, the Twitter accounts that posted tweets about data science. Burke (1945 , p. xix–xx) suggested that agents “subdivide” into groups. This step first analyzes the group structure of the 395 accounts that constitute the small dataset of qualitative observations with respect to the connections between them as well as connections in the large dataset of 455,344 accounts they followed. The “walktrap” community finding algorithm, a standard function in R's igraph package ( Csardi and Nepusz, 2006 ) that builds on the widely used modularity measure ( Pons and Latapy, 2005 ) with a focus on communication settings ( Smith et al., 2020 ), revealed the relational subdivisions of these actors. It uses random walks to partition a network into groups of nodes with dense connections between each other and sparse connections to other nodes.

I begin with the most comprehensive dataset. The large dataset includes 455,344 accounts, all contacts followed by the 395 accounts from the qualitative observations. I created a bipartite network of these following relations, with the 395 focal accounts on one level and the ones they follow as the second level. I projected this bipartite network on the level of the focal nodes, retaining ties between nodes that follow the same other account, weighted by the number of common accounts, and applied the community finding algorithm. This strategy ensures the interpretability of the structural characteristics in terms of the focal nodes while considering a wider structural context. Substantively, it captures that although two accounts may not follow each other, say, two junior data scientists where one is in a university and another in a startup, they may still follow the same prominent accounts. The weighting accounts for the number of accounts in which the two data scientists may share an interest.

The algorithm identified two main communities and a third, smaller community. This result amid an average out-degree of over one thousand nodes for the focal accounts before the projection indicates a strong interest in other Twitter accounts. The two larger groups consist of 265 and 101 accounts and the smaller one of 26 accounts. The modularity score is 0.08, indicating substantial integration. Only 14% of the node pairs have no accounts in common among those they follow, while 49% share ten or more. Qualitative inspection revealed that the largest one consists of more hands-on accounts, including software coders in applied roles but also academics from different disciplines and a few commentators from media and industry, but these two groups of accounts more distinctively cluster in the second larger group, which includes less of the hands-on accounts, capturing the role of often self-described “thought leaders” in these early data science discussions. This structure offers a plausible image of data science's emergent community structure that includes core contributors and some hangers-on. While it reflects abundant records, it is simple and does not indicate any underlying motives.

The next analytical step changes perspective. It considers the immediate relational structure within the tighter boundary of the small dataset of 395 accounts and the 11,580 ties between them. 8 The community detection produced five groups with a modularity score of 0.15. 9 Figure 1 shows this network on an aggregate level where the node sizes indicate the number of accounts in each group (reported in separate discussions below); the arrows between them bundle individual ties from one group to another. The line thickness of the arrows indicates the followership ties from the sender-group perspective. Each group has at least one connection to each other group, except for the media group, where no account follows any account in the social scientists group. On the aggregate level, the strong connections stand out between what I will be introducing as the hacker group and the visionaries, with 123 and 104 ties in the respective directions. Both groups are large and have intuitive links to data science's emergence, but while their interconnection is strong, they are much weaker than the internal connections, consisting of 1,919 and 4,560 ties, which led to the clusters that I discuss next. This network of only direct following relations recovers existing groups that contributed to early data science conversations on Twitter.

Figure 1 . Network of groups and their aggregate relations.

The first group contains prominent accounts ( Figure 2 ; squares represent second-degree accounts from the data collection perspective, and circles represent first-degree accounts). The 29 accounts in this group have a dense core but otherwise moderate interconnections with a density of 0.14. 10 Several belong to newspapers and magazines, such as Forbes, The Economist, CNN, WIRED, and TechCrunch, an online publisher covering the tech industry. These accounts capture data science's cultural context ( Abbott, 1988 ; Fourcade, 2009 ), signaling the broader interest in data issues during data science's emergence. There are also HarvardBiz and Columbia_Tech, two university-affiliated accounts, and IBM Services from the technology industry, which all represent official and corporate actors. Circular node shapes indicate first-degree accounts, which capture one of Burke's ideas on actors. This group includes only a few direct neighbors, such as CNN, The Economist, and chicagolucius, a personal account of a user who indicates roles as a chief data scientist and data officer with the City of Chicago. 11 The outsized salience of second-degree accounts here increases exposure to their tweets through retweets. This group reflects the institutional attention that data science has attracted and the power of some accounts in broadcasting data science ideas even in the confines of the small dataset.

Figure 2 . Followership relations within the media group (1).

The second group consists of 24 accounts ( Figure 3 ), which capture a different side of the community, and one with more interconnections than the previous group at a density of 0.31. 12 There are few, if any, broadly familiar accounts, which mostly belong to epidemiologists and biostatisticians. We see accounts with Harvard affiliations, but this time, they belong to a data initiative and the public health school. Most of these accounts are, again, second-degree neighbors who have entered the observations via direct connections, which are central in this group. The public prominence of media accounts ensured the diffusion of their tweets in the first group. In contrast, this group's academic culture of communicating knowledge and ideas contributed to their diffusion beyond a tight boundary. As these accounts entered the analysis via data science-related tweets, they reflect the idea that expert work unfolds in problem areas rather than formal groups ( Abbott, 1988 ).

Figure 3 . Followership relations within the biostatistics group (2).

Table 2 presents the structurally most central actors of cluster three, which is too large to show visually (it consists of 115 accounts). This group is quite tightly interconnected, considering its size, with a density of 0.15. The most central first-degree neighbor account belongs to hadleywickham, a former professor of statistics, developer of popular R packages, and now a research scientist at RStudio, a software company with free software options. There is also seanjtaylor, who introduced himself on Twitter as a research scientist at Lyft at the time of this analysis but has used the data scientist label for his roles in the past and has continued commenting on data science issues. Another central account is robinson_es, who introduced herself as a data scientist at Warby Parker and advertised a book on building a data science career in her Twitter bio. The most central second-degree accounts are similar, with JennyBryan as a former professor who is now with RStudio, like Wickham, or skyetetra, who introduced herself as a data scientist and author of a book on data science careers, like robinson_es. While not all are equally technical, they all work with data, both first- and second-degree accounts. We can think of this group as data hackers and potentially the group that fits the opening definition of data science most closely. The dominance of second-degree neighbors in this institutionally undefined group of technical profiles indicates the relational backbone of data science's construction.

Table 2 . Overview over 15 most central accounts in the hacker group (3).

Consider, in contrast, the fourth group, which consists of only 15 accounts and contains some of the social scientists that have shaped data science (see Figure 4 ). The interconnections are strong, like in the other cluster of predominantly academic accounts, and have a density value of 0.39. The most central account among them belongs to Duncan Watts (duncanjwatts), 13 now a professor at The University of Pennsylvania, following several years as a research scientist at Microsoft and as a sociology professor at Columbia University. During my field observations, I heard a story that quantitative analysts at Facebook, where the mythology locates data science's origin in the mid-2000s ( Hammerbacher, 2009 ; Davenport and Patil, 2012 ), consulted Watts for advice on the label. Matt Salganik (msalgnaik), another central node, is a quantitative sociologist at Princeton University who wrote a book about quantitative research in the digital age that addressed both social scientists and data scientists ( Salganik, 2018 ). Laura Nelson (LauraK_Nelson) is a sociologist at the University of British Columbia and promotes principles from qualitative methods for computational research (e.g., Nelson, 2020 ). Not necessarily well-known outside academic circles, all these scholars have apparent connections to data science. Shamus Khan (shamuskhan), on the other hand, does mostly qualitative research, but he has published quantitative studies as well (e.g., Accominotti et al., 2018 ). He appears in this dataset because he still tweeted about a data science opportunity at Columbia University, where he taught at the time. Following a media group, epidemiologists, and the hacker group, this is a social science group. The large share of first-degree neighbors in this group of social scientists amid its small size captures my own position in this analysis and suggests that social scientists are keeping quieter than they could about data science [see Ribes (2019) and Brandt (2022) on this issue].

Figure 4 . Followership relations with the social scientists group (5).

The last group, cluster five, is also the largest (177 accounts) and has some of the nominally most explicit connections to data science. Table 3 once again focuses on the most central accounts out of another quite interconnected cluster, considering its size, with a density value of 0.15. The names may not be immediately familiar, but many of them participate actively in the advancement of digital tools. In contrast to the hacker group, this group often comments on broader issues and developments. hmason is the most central node among the first-degree accounts, consistent with her status as a data scientist, founder of a data startup, and co-author of an early data science definition, 14 as well as a book on data science ethics ( Loukides et al., 2018 ). AndrewYNg is a Stanford professor, co-founder of Coursera, and head of artificial intelligence at Alibaba. Then, there are also wesmckinn and amuellerml, who do quite technical work. There is KirkDBorne, formally the chief data scientist at Booz Allen Hamilton at the time and a data science popularizer, but also mathbabedotorg, who was a math professor before she became a data scientist and eventually an activist and author who points at issues with algorithms ( O'Neil, 2016 ). The second-degree accounts mirror the direct neighbors, as for the hacker group, just trailing them slightly in centrality. Many have similar technical skills as those in group three, and several have PhD-level training, but they also bring weightier institutional affiliations, which makes them possible data science visionaries. The balance between two groups in this more talk- and thought-focused cluster shows the beginnings of data science as a distinct object.

Table 3 . Overview over 15 most central accounts in the visionary group (5).

The network's fragmentation into five groups in the small dataset captures the distributed organization of the data science conversation. It reveals the technical and popular perspectives in data science as well as potential sources for non-technical ideas and my social scientific perspective. The first analysis of the large dataset suggested a simple picture that reproduced the familiar divisions. It captured the larger divide between technical expertise and general issues in which data science flourished but not its micro-level foundation. The second analysis of the small dataset revealed fragmentation of the accounts followership network into groups that are internally plausible and reveal a more complex relational underpinning of data science's construction on social media, which involved some densely connected communities that still tied into neighboring groups. The two analytic lenses complement each other to indicate a fractal structure ( Abbott, 2001 ). This additional complexity shows the counterintuitive implications of accounting for “the larger social world” and its promise for studying an emergent group. The different group compositions have started suggesting different motives for data science's definition. The next two steps study them directly.

4.2 Purposes

This step turns to purposes to move further toward a Burke-informed cultural understanding of data science's construction on social media from Mohr's computational hermeneutics perspective. Twitter users can indicate a tweet's purpose through hashtags, and popular hashtags in a group indicate the group's purposes. This step analyzes the prominence of different hashtags using weighted log odds ratios. Odds ratios in text analyses measure the odds for a word occurring in one corpus compared to another ( Silge and Robinson, 2017 ), such as in speeches by Republicans and Democrats or in tweets in the small and large datasets. The frequency of words in two corpora may vary vastly, and they do so by design in the large dataset of missed tweets and the small dataset of qualitative observations. Log odds ratios correct for these asymmetries, but words that do not occur at all in one corpus remain problematic. The following analysis uses weighted log odds ratios, which account for words that may have occurred by chance ( Monroe et al., 2008 ; Schnoebelen et al., 2020 ). 15

This step starts once again with the most comprehensive dataset. The tweets in the large dataset include 335,337 hashtags (46,971 unique hashtags). Figure 5 shows the 25 hashtags with the highest weighted log odds ratios from the large corpus compared to hashtags from the small tweet dataset. The large one includes tweets that promote technical and commercial concerns through hashtags such as artificialintelligence, neuralnetworks , which operationalize artificial intelligence, and internetofthings , on one side, and startups and innovation , on the other. nyc was promoted as well, reflecting the location of the qualitative observations but also its significance in broader discourse, as were women in tech. The blockchain hashtag captures broader technology purposes among these tweets. These are big issues and a range of different ones. Consistent with some of the existing writing ( O'Neil, 2016 ; Eubanks, 2018 ; Zuboff, 2019 ), data science and related concerns thus emerge as part of a comprehensive effort, or a larger cultural discourse, to promote technology and business, the large corpus shows.

Figure 5 . Weighted log odds ratios of hashtags in small dataset and large datasets.

Similar to the initial community structure, these are reflections of familiar purposes of technology and data science advocates. Their occurrence in the tweets dataset underlines Twitter's utility for studying data science's construction, but the bird's-eye view offers few new insights. Next, I turn to the small dataset.

The small dataset includes 475 hashtags (213 unique hashtags). The list of hashtags with the largest weighted log odds ratios on the side of the small dataset includes several that directly or indirectly promoted data science, such as datascience, data, bigdata, AI, ML , and technology themes, such as python, pydata, rstatsnyc , and rladies . The hashtags rladies and data4good promoted political and moral purposes, similar to some prominent purposes in the large dataset but with different political connotations and more concrete initiatives. Some of the hashtags stand for groups or conferences, such as strataconf and datadive . datadive described events where a group meets to work closely on a dataset, while strataconf referred to a major data conference with expensive tickets. rstatsnyc captured the promotion of a local community and reflected the new hope that New York gained as a tech location vis-à-vis Silicon Valley in the latest technological transformation. The hashtags that capture local or topically specific purposes show the payoff of taking different perspectives and moving to a smaller dataset. Twitter facilitates global discussions, but it also accommodates local ones, and they are potentially crucial for mobilizing support and involvement.

The distinctive hashtags reflect purposes that start revealing data science's roots in a collective project around technical skills and ideas for a professional community. The technical hashtags are not distinctive for data science, however, as critics have often noted. The hashtags that stand for community activities, which are not part of the popular data science discussion, suggest a process wherein diverse technologies gain a joint meaning as data science.

The contrast between the large and small datasets serves as a necessary first step to establish the utility of this approach but may overlook variation from more gradual shifts of perspective. One complementary step compares purposes associated with second-degree accounts to those of the first-degree accounts within the large dataset of missed tweets (see Figure 6 ). Tweets by second-degree accounts included 186,607 hashtags (36,131 unique hashtags), and tweets by direct neighbor accounts included 148,718 hashtags (17,291 unique hashtags). Some outlier hashtags appear on these lists. 16 Purposes are once again more diffuse across second-degree tweets in the large dataset. They include oracle , which is a database firm and synonymous with that firm's technology, and storage, referring to data storage that data scientists have relied on from early on ( Hammerbacher, 2009 ), and voicesinai or learntocode —other technical concerns. Then, there is more on sales and several hashtags that promote different technical conferences in the late 2010s. New York City features again as well.

Figure 6 . Weighted log odds ratios of hashtags in tweets of first- and second-degree accounts in the large dataset.

The first-degree accounts tweeted about a combination of the issues that appeared in the small dataset and the large dataset. Data science again tops the list, with machine learning and artificial intelligence nearby and R not far behind. w ids2018 and 2019 appear on this list, promoting women in data science in general and a conference that Stanford University hosts for this purpose, an initiative that has spread to a large number of institutions. This list still includes more of the commercial concerns that the small dataset missed, such as techstartups and businesscoaching .

The differences between first-degree and second-degree purposes remain smaller than between the small and large datasets to capture a more continuous view of the different levels and contexts of data science's construction on social media. The small dataset systematically reveals locally and topically specific purposes that connect the purposes data science supporters share more generally to the situations of specific supporters or beneficiaries. Overall, the small tweet dataset captured most clearly the promotion of data science issues, even in technical terms, and collective activities that would be part of data science's “cultural machinery” ( Abbott, 1988 , p. 60). Together, the different perspectives captured how new socio-technical arrangements come together in expert work ( Eyal, 2013 ). The purposes across the large tweet dataset spoke to broader tech and business concerns, reflecting the larger cultural shifts of the digital era. These purposes, missing from the small dataset, were more prominent among second-degree accounts than among direct neighbors. Instead of constraining the analysis to a representative picture, the comparisons capture the “larger diversity in the world” ( Krause, 2021 ) at varying depths of data science definitions.

The final analytical step turns to “scenes” to see the contexts wherein the actor groups articulate purposes ( Burke, 1945 , p. 3) as part of their construction of data science on social media. Mohr et al. (2013) used latent Dirichlet allocation (LDA) topic models for recovering scenes from texts, which identify words that co-occur in documents within a larger corpus of documents. Each word may be part of one or more topics, and each document may consist of one or more topics ( Blei et al., 2003 ). Several specialized topic modeling approaches are available for specific research problems. This analysis follows Mohr's approach and uses LDA topic models “to identify the lens through which one can see the data most clearly” more than “to estimate population parameters correctly” ( DiMaggio et al., 2013 , p. 582). In this sense, the following models provide an initial image of data science's cultural construction while tracing its contours from varying perspectives. 17 They treat tweets as documents after removing hashtags, addressed accounts, URLs, stop words and numbers, and use word stemming. 18 Consistent with the earlier steps, I generated separate topic models for the large dataset of missed tweets and the small tweet dataset and, within the large dataset, for the tweets of first- and for those of second-degree accounts. This division into distinct corpora captures the scenes as fresh looks from each of the perspectives, revealing their misses, and gains. Computational limitations demanded taking samples of 35,000 tweets from the large dataset of missed tweets for each of the three analytical steps. 19

The first step starts again with the large tweet dataset of full timelines missing from the small dataset. The analysis revealed 45 topics, of which many have no connection to data science, reflecting that it was not a strategic endeavor and instead part of the much broader conversation on Twitter, but data science-related topics still emerged even in this bird's-eye view. Overall, ten topics were about data science issues, another ten about tech or science issues, and then nine, six, and ten about current issues, mostly politics, miscellaneous topics, and different types of chatter (see also Table 4 ).

Table 4 . Summaries for topic models of large tweet dataset.

The tech and science topics comment on the digital transformation, for example, startup opportunities and the big technology companies, as well as articles and journals that are relevant to these accounts. The topics that capture discussions of generally important issues include topics around Trump and politics, education, the economy, and healthcare, as well as urban and civil rights issues. Then, there is a group of leisure topics, including sports, movies, and music, cultural concerns in the lay sense. Finally, several topics have no specific substantive meaning and instead reflect observations, opinions, pleasantries, and general Twitter chatter.

As Supplementary Table S1 shows, the data topics captured quite a few dimensions of data science, a striking result considering the simple modeling procedure, diverse accounts, and openness of Twitter as a discursive space. More specifically, data topics cover practical issues, such as careers and hiring, but also training and studying. The more technical among them revolve around different data analytic approaches or procedures, ranging from statistics and causal inference to machine learning and artificial intelligence, as well as coding-related issues or data visualizations. Perhaps most interestingly, this analysis revealed a topic that picked up on issues of bias and ethics. These topics cover the dimensions of data science that are familiar from more formal, deliberate, and curated discussions directly from concrete conversations. They still present a mirror image of the familiar themes of data science discussions. This broad view responds more to data science rise than its meaning construction, which the small dataset was designed to capture.

The tweets in the small dataset cover 13 topics or, in Burke's terms, scenes. Table 5 lists these topics as 20 words most closely associated with each of them. The table also lists names that I assigned to topics as summaries. Topics two (2) and 13 may be labeled statistics and machine learning. Topic 2 includes words such as model, logistic, regression , and algorithm , and topic 13 includes machine, learning, code , and python , a popular programming language. Topic 11 is about software issues and their importance for data science, several words suggest. Topic seven (7) seems to discuss data science relative to other roles, and topics nine (9) and ten (10) include career advice and open positions. Topic four (4) describes data science training, which seems essential if topic three (3) is right about the challenges it indicates. The tweets associate successful data science with team efforts, as topic six (6) suggests. Topics five (5) and twelve (12) capture discussions and exchanges at conferences and in digital formats as other scenes.

Table 5 . Thirteen level topic model of small tweet dataset.

These topics reveal a more refined set of scenes that still show analytically important depth and diversity. The scenes are familiar from the popular data science discourse, and they reflect themes from sociological ideas about expert work. Several books describe the technical challenges associated with data science work (e.g., Schutt and O'Neil, 2013 ; Wickham and Grolemund, 2016 ), universities have started to offer data science training ( Börner et al., 2018 ; Saner, 2019 ), data scientists have discussed their roles and careers ( Shan et al., 2015 ), and how to build teams ( Patil, 2011 ). The concern with neighboring roles echoes Abbott's classic idea about conflicts between expert professions ( Abbott, 1988 ). The overlap between existing contributions, topics from the large dataset, and this collection of tweets gives confidence in the utility of a small dataset for analyzing data science's cultural definition on social media. In contrast to the existing contributions, these topics portray scenes of ongoing development requiring concrete engagement rather than definite frames of reference and larger processes.

However, the first topic (1) seems neither intuitive nor familiar. Some words are clear enough: Data scientists often work in companies, for instance, while challenge, win , and happy may also go together, as data analysis competitions are a popular sport and recruitment tool in data science. say, word, hour , and room , in contrast, make less intuitive sense. A topic modeling approach provides the opportunity to deal with such surprising results by returning the documents that included these words (e.g., Karell and Freedman, 2019 ). Some tweets were about an analysis of gender diversity that won a data challenge; others discussed the diversity of data scientists in the room should reflect the outside world. Authors of further tweets wondered what they should say to their audience in a room during the half-hour that they had to speak to them. Topic eight (8) echoes the reflective ideas behind these issues. It consists of words that suggest these users reflect on broader problems, including ethics, discussion, thought, read , and better , but the first topic insists on recognizing the collective challenges around advancing these issues as part of data science, adding substance to the conference-related purposes in the previous analysis.

Like the other topics, the reflective perspective has appeared in the broader discourse ( O'Neil, 2016 ), and some of these tweets may concern proposals for a code of ethics for data science (e.g., Loukides et al., 2018 ). These observations capture the collective discussion of these topics and the original implications for active data scientists. Again, however, the general ethic topic manifests itself in discussions of practical questions about implementing it in the community. The initial ambiguity about the words in topic one captures the close connection between these generally familiar ideas and the real experience of constructing a novel professional role.

The final comparison reiterates the analytical strategy of comparing a wider perspective to a narrower one without the radical difference between the full large dataset and the small dataset. It compares topic models of corpora from subsets within the large dataset of missed tweets of tweets of first- and second-degree accounts, which remain closer to the project's theoretical focus. 20 Similar to the full large dataset, these models revealed 45 and 40 topics, which I once again report in thematic groups. Table 4 presents the summaries (together with the full dataset as an additional reference); Supplementary Tables S2 , S3 show all topics in terms of their top 15 words.

Like the initial model for the large tweets dataset, these models reveal familiar scenes and additional ones that the small dataset missed and a more refined set of these topics from tweets by first-degree accounts than in the second-degree tweets. The different groups map onto those from the initial description, with some details that I discuss below. More interestingly, the shifting perspective shows, again, benefits for locating data science's construction in its larger social context. The slightly broader perspective focusing on second-degree tweets has much fewer topics focused on data issues and, to a lesser degree, on tech and science, and more on current issues and especially general social media chatter. While they do not have an evident connection to data science's construction, they serve as an important indicator of where that construction happened, namely, among general concerns and not only the specialized scientific concerns that were more salient in the network analysis.

The dataset of missed tweets by first-degree accounts already reveals a more refined set of data-related topics as well as reflexive discussions. It includes an ethics topic, reflecting this issue's prominence in data science discussions and the well-documented strategy for gaining legitimacy ( Abbott, 1983 ). Here, ethics appear in the context of algorithmic bias, which is part of the larger conversation. In the small dataset, in contrast, the diversity concerns appeared as well around the problem of discussing it in the data science community and its audience and self-reflection on recognizing the purpose of the data science role. Both ethics scenes, in the large and small datasets, are about non-technical questions about what is right, but they differ on how this concern presents itself to those who confront the scene.

The asymmetric comparison shows the limits of the each dataset for capturing meaning construction. Shifting perspectives to narrower dataset designs reveals locally meaningful scenes of concrete engagement with the collective construction of data science as a social object. This pragmatic reflexivity from the small dataset remained largely absent from the larger datasets. The analytic strategy then indicates the utility of considering different levels of data science's cultural construction instead of settling on one definite level for studying an emergent process, especially one that seeks the largest possible view. It also points to technical directions for implementing a more refined text analysis that considers immediate word contexts on the large dataset that tests ideas following from the small dataset.

5 Discussion

This analysis departed from a limited perspective to gain analytical traction on data science discussions on social media from a cultural perspective, an emergent process that poses unique research design challenges that today's digital affordances can help address. Initial examples of tweets illustrated reflections of an emerging profession around technical knowledge, training, and jobs, as well as the wider digital change. The results of network and text analyses found patterns consistent with existing research on data science, as well as ideas in the literature on expert work and quantification. They extend recent arguments that data science's emergence follows from an ambiguous image in its outside construction in firms and sciences ( Dorschel and Brandt, 2021 ) and the struggle of individual data scientists with that ambiguity ( Zuboff, 2019 ; Avnoon, 2021 ). This analysis captured how the data science community sorted out that ambiguity on social media. The qualitative research on which this study built identified meaning-making around concrete analytical and relational issues. This computational ethnography showed that data science pioneers reflected on these challenges between each other and how they arrived at the specific issues in more general discussions.

The analysis addressed the research design challenge of studying emergent processes by adopting an “active approach to data” ( Leifer, 1992 ). It integrated ideas from qualitative and quantitative research about missing observations to guide an analysis of two complementary datasets in an asymmetric comparison ( Krause, 2021 ). This comparison captured the interplay of how actors integrate broader cultural shifts and their more technical ideas into a novel professional identity. Instead of resorting to a single scope or boundary, this article makes an argument for using computational tools to gain analytic leverage from the variation across different boundary specifications. For quantitative analysts, this approach means that rather than departing from the idea of a general analysis, which has merit in many situations but works less well for capturing localized meaning-making processes (e.g., Nelson, 2021 ), they can approach a research problem in relation to their point of departure and comparing different angles on a specific case or process. This approach offers one solution to the increasingly important question of the relevant scope of quantitative analyses ( Lazer et al., 2021 ).

These conclusions are subject to limitations. Subsequent research has to establish connections between the scenes and purposes and the actors for better understanding data science's development. This article's focus on the emergent moment and the methodological challenges that come with it benefited from relying on basic network and text analytic procedures. They can serve as points of departure for analyses that discover more nuanced social and meaning structures. More advanced social network analysis techniques can untangle the precise attachment processes between accounts, such as between the groups this initial analysis reveals. Similarly, more advanced text analytic techniques can identify more nuanced topics and meaning changes of words, such as around the technical and non-technical issues this analysis revealed. More broadly, additional studies of data science have to step outside the Twitter setting to consider agency and acts, but these findings also invite research on further professional or otherwise collective activities on Twitter and how they use social media to discuss with each other in public.

Keeping those limitations in mind, these insights into the collective definition of a professional role complement existing views on professions of expert workers defending their boundaries against competitors ( Abbott, 1988 ), establishing themselves in modern corporations ( Muzio et al., 2011 ), or navigating more extensive socio-technical arrangements ( Eyal, 2013 ). The analysis revealed actors outside of broad commercial and narrow technical concerns, a potential source of new views, and a distinct motivation behind starting data science: building a platform to adopt new practical and ethical standards. While familiar from other scientific and intellectual movements (see Frickel and Gross, 2005 ), this motive appears here for the first time for data science. Compared to other professions that acknowledge non-technical aspects of their work (e.g., MacKenzie and Millo, 2003 ), data scientists discuss these concerns as a community, integrating them into their stock of knowledge.

Practicing data scientists can use this glimpse into their early days as a reference point for assessing their current situation and future direction as a profession. The digital era renders the institutional scaffolding of classic professions less necessary for collective organizing ( Avnoon, 2023 ). This advantage does not relieve professionals from mutual engagement over the content and contours of their work if they seek autonomy from their employers. More immediately, data scientists can also find utility in the culturally informed computational analysis and design around qualitative approaches.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical approval was not required for the study involving human data in accordance with the local legislation and institutional requirements. The social media data was accessed and analyzed using the Twitter API in accordance with the platform's terms of use and all relevant institutional/national regulations. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article because only information participants chose to share publicly on Twitter was used for the analysis.

Author contributions

PB: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Funded by the European Union (ERC, ReWORCS, #101117844).

Conflict of interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Author disclaimer

Views and opinions expressed are those of the author only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fdata.2024.1287442/full#supplementary-material

1. ^ https://twitter.com/josh_wills/status/198093512149958656

2. ^ Newspapers regularly cite data scientists as sources in or protagonists of their stories, and data scientists have featured in popular culture such as in Netflix's House of cards (seasons four and five).

3. ^ Twitter and the interface have gone through substantial change, even before the Elon Musk takeover and its rebranding into X. This analysis focuses on a relatively short window, however, and within that window on a specific corner of the Twitter discussion. The stability assumption is robust within that scope.

4. ^ See Alexander et al. (2012) for this reflexive view on computational hermeneutics.

5. ^ The large dataset missed tweets because Twitter only grants access to a given account's 3,200 most recent tweets. Potentially problematic for some purposes, the over seven hundred thousand available observations offer important context to the small dataset.

6. ^ This tweet was from January 2018, before revelations of MindGeek benefited from videos posted without consent. While such a tweet would indicate ignorance today, at the time it more likely tried to present a progressive twist on possible areas of professional work.

7. ^ I identify individuals by name if they maintained a public profile in the community.

8. ^ While this number looks large, it only represents 8% of all possible ties. In addition, 13 accounts did not follow any accounts and remained outside of the network.

9. ^ There was a sixth group with only three accounts as well as 15 isolates and two isolated pairs that I leave out of this description.

10. ^ Density is a social network analysis measure that indicates the share of all ties in a network out of all possible ties with 1 as the highest score.

11. ^ I refer to the Twitter account names since they serve as the main method for using Twitter and what users have chosen to share as their public profiles.

12. ^ The density measure is sensitive to networks of different sizes in terms of numbers of nodes. In this analysis, the similar density scores between this group and the media group despite their vastly different sizes highlight the great importance of direct following relationships in this group.

13. ^ I report the names together with Twitter usernames for this group because the accounts belong to social scientists and may already be familiar to readers.

14. ^ https://web.archive.org/web/20160220042455/dataists.com/2010/09/a-taxonomy-of-data-science/

15. ^ A related measure with similar qualities is the tf-idf measure. The weighted log-odds-ratios capture better words that are common in different corpora but still more salient in one than another, which is important for this analysis that compares different perspectives.

16. ^ li and rottweiler were outliers in tweets of second-degree accounts. One promotes the account itself and the other the account owner's dog amid other tweets about data science issues, indicating personal promotion efforts. On the friends side, the sexual citizens hashtag does not fit with data science. It refers to a book that had been recently published by Shamus Khan, one of the academic friends accounts, together with Hirsch and Khan (2020) . This hashtag also promotes a personal project, a book, that has a collective orientation at the same time. This difference indicates that the project's interest in data science's collective construction may have led to overlooking actors who pursue more self-serving purposes, supporting the benefits of the asymmetric comparison. As both agendas appear systematically, data science may not have a uniform definition at this early stage.

17. ^ The more specialized implementations can account for meta information on the documents for estimating topic models. At this initial research step focusing on the effect of different perspectives on the emergent image of data science, no specific meta information informed the topic estimation. The discussion will outline how this study's results inform such more refined implementations in future research.

18. ^ I used the topicmodels package ( Grün and Hornik, 2011 ) in R with the Gibbs sampler method and an alpha of .1. I obtained the number of topics after testing a series of possible numbers of topics using the ldatuning package ( Nikita, 2020 ) and considering the four evaluation metrics the packages provides, particularly Griffiths and Steyvers's (2004) . My qualitative reading of the results and familiarity with the case confirmed that this implementation provided satisfactory results for the purposes of observing data science's construction across the different perspectives.

19. ^ This limitation only has small effects on the results. While topic models of more tweets obviously capture more topics (in contrast to other many other corpora, Twitter specializes in no particular set of issues), analyses of different sample sizes and randomly composed corpora have revealed the same set of main topics.

20. ^ Specialized techniques exist [e.g., correlated topic models ( Blei and Lafferty, 2009 )] for modeling these two corpora jointly while considering the two types of accounts. Rather than finding the one precise topic model, however, this analysis aims to compare the “lenses” different points of departure offer.

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Keywords: data science, emergence, expertise, professions, reflexivity, computational social science, social network analysis, computational ethnography

Citation: Brandt P (2024) Data science's cultural construction: qualitative ideas for quantitative work. Front. Big Data 7:1287442. doi: 10.3389/fdata.2024.1287442

Received: 01 September 2023; Accepted: 22 July 2024; Published: 14 August 2024.

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*Correspondence: Philipp Brandt, philipp.brandt@sciencespo.fr

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• Published: 14 August 2024

A Scottish provenance for the Altar Stone of Stonehenge

• Anthony J. I. Clarke   ORCID: orcid.org/0000-0002-0304-0484 1 ,
• Christopher L. Kirkland   ORCID: orcid.org/0000-0003-3367-8961 1 ,
• Richard E. Bevins 2 ,
• Nick J. G. Pearce   ORCID: orcid.org/0000-0003-3157-9564 2 ,
• Stijn Glorie 3 &
• Rob A. Ixer 4  

Nature volume  632 ,  pages 570–575 ( 2024 ) Cite this article

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• Archaeology

Understanding the provenance of megaliths used in the Neolithic stone circle at Stonehenge, southern England, gives insight into the culture and connectivity of prehistoric Britain. The source of the Altar Stone, the central recumbent sandstone megalith, has remained unknown, with recent work discounting an Anglo-Welsh Basin origin 1 , 2 . Here we present the age and chemistry of detrital zircon, apatite and rutile grains from within fragments of the Altar Stone. The detrital zircon load largely comprises Mesoproterozoic and Archaean sources, whereas rutile and apatite are dominated by a mid-Ordovician source. The ages of these grains indicate derivation from an ultimate Laurentian crystalline source region that was overprinted by Grampian (around 460 million years ago) magmatism. Detrital age comparisons to sedimentary packages throughout Britain and Ireland reveal a remarkable similarity to the Old Red Sandstone of the Orcadian Basin in northeast Scotland. Such a provenance implies that the Altar Stone, a 6 tonne shaped block, was sourced at least 750 km from its current location. The difficulty of long-distance overland transport of such massive cargo from Scotland, navigating topographic barriers, suggests that it was transported by sea. Such routing demonstrates a high level of societal organization with intra-Britain transport during the Neolithic period.

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Stonehenge, the Neolithic standing stone circle located on the Salisbury Plain in Wiltshire, England, offers valuable insight into prehistoric Britain. Construction at Stonehenge began as early as 3000  bc , with subsequent modifications during the following two millennia 3 , 4 . The megaliths of Stonehenge are divided into two major categories: sarsen stones and bluestones (Fig. 1a ). The larger sarsens comprise duricrust silcrete predominantly sourced from the West Woods, Marlborough, approximately 25 km north of Stonehenge 5 , 6 . Bluestone, the generic term for rocks considered exotic to the local area, includes volcanic tuff, rhyolite, dolerite and sandstone lithologies 4 (Fig. 1a ). Some lithologies are linked with Neolithic quarrying sites in the Mynydd Preseli area of west Wales 7 , 8 . An unnamed Lower Palaeozoic sandstone, associated with the west Wales area on the basis of acritarch fossils 9 , is present only as widely disseminated debitage at Stonehenge and possibly as buried stumps (Stones 40g and 42c).

a , Plan view of Stonehenge showing exposed constituent megaliths and their provenance. The plan of Stonehenge was adapted from ref.  6 under a CC BY 4.0 license. Changes in scale and colour were made, and annotations were added. b , An annotated photograph shows the Altar Stone during a 1958 excavation. The Altar Stone photograph is from the Historic England archive. Reuse is not permitted.

The central megalith of Stonehenge, the Altar Stone (Stone 80), is the largest of the bluestones, measuring 4.9 × 1.0 × 0.5 m, and is a recumbent stone (Fig. 1b ), weighing 6 t and composed of pale green micaceous sandstone with distinctive mineralogy 1 , 2 , 10 (containing baryte, calcite and clay minerals, with a notable absence of K-feldspar) (Fig. 2 ).

Minerals with a modal abundance above 0.5% are shown with compositional values averaged across both thin sections. U–Pb ablation pits from laser ablation inductively coupled plasma mass spectrometry (LA-ICP–MS) are shown with age (in millions of years ago, Ma), with uncertainty at the 2 σ level.

Previous petrographic work on the Altar Stone has implied an association to the Old Red Sandstone 10 , 11 , 12 (ORS). The ORS is a late Silurian to Devonian sedimentary rock assemblage that crops out widely throughout Great Britain and Ireland (Extended Data Fig. 1 ). ORS lithologies are dominated by terrestrial siliciclastic sedimentary rocks deposited in continental fluvial, lacustrine and aeolian environments 13 . Each ORS basin reflects local subsidence and sediment infill and thus contains proximal crystalline signatures 13 , 14 .

Constraining the provenance of the Altar Stone could give insights into the connectivity of Neolithic people who left no written record 15 . When the Altar Stone arrived at Stonehenge is uncertain; however, it may have been placed within the central trilithon horseshoe during the second construction phase around 2620–2480  bc 3 . Whether the Altar Stone once stood upright as an approximately 4 m high megalith is unclear 15 ; nevertheless, the current arrangement has Stones 55b and 156 from the collapsed Great Trilithon resting atop the prone and broken Altar Stone (Fig. 1b ).

An early proposed source for the Altar Stone from Mill Bay, Pembrokeshire (Cosheston Subgroup of the Anglo-Welsh ORS Basin), close to the Mynydd Preseli source of the doleritic and rhyolitic bluestones, strongly influenced the notion of a sea transport route via the Bristol Channel 12 . However, inconsistencies in petrography and detrital zircon ages between the Altar Stone and the Cosheston Subgroup have ruled this source out 1 , 11 . Nonetheless, a source from elsewhere in the ORS of the Anglo-Welsh Basin was still considered likely, with an inferred collection and overland transport of the Altar Stone en route to Stonehenge from the Mynydd Preseli 1 . However, a source from the Senni Formation (Cosheston Subgroup) is inconsistent with geochemical and petrographic data, which shows that the Anglo-Welsh Basin is highly unlikely to be the source 2 . Thus, the ultimate provenance of the Altar Stone had remained an open question.

Studies of detrital mineral grains are widely deployed to address questions throughout the Earth sciences and have utility in archaeological investigations 16 , 17 . Sedimentary rocks commonly contain a detrital component derived from a crystalline igneous basement, which may reflect a simple or complex history of erosion, transport and deposition cycles. This detrital cargo can fingerprint a sedimentary rock and its hinterland. More detailed insights become evident when a multi-mineral strategy is implemented, which benefits from the varying degrees of robustness to sedimentary transportation in the different minerals 18 , 19 , 20 .

Here, we present in situ U–Pb, Lu–Hf and trace element isotopic data for zircon, apatite and rutile from two fragments of the Altar Stone collected at Stonehenge: MS3 and 2010K.240 21 , 22 . In addition, we present comparative apatite U–Pb dates for the Orcadian Basin from Caithness and Orkney. We utilize statistical tools (Fig. 3 ) to compare the obtained detrital mineral ages and chemistry (Supplementary Information  1 – 3 ) to crystalline terranes and ORS successions across Great Britain, Ireland and Europe (Fig. 4 and Extended Data Fig. 1 ).

a , Multidimensional scaling (MDS) plot of concordant zircon U–Pb ages from the Altar Stone and comparative age datasets, with ellipses at the 95% confidence level 58 . DIM 1 and DIM 2, dimensions 1 and 2. b , Cumulative probability plot of zircon U–Pb ages from crystalline terranes, the Orcadian Basin and the Altar Stone. For a cumulative probability plot of all ORS basins, see Extended Data Fig. 8 .

a , Schematic map of Britain, showing outcrops of ORS and other Devonian sedimentary rocks, basement terranes and major faults. Potential Caledonian source plutons are colour-coded on the basis of age 28 . b , Kernel density estimate diagrams displaying zircon U–Pb age (histogram) and apatite Lu–Hf age (dashed line) spectra from the Altar Stone, the Orcadian Basin 25 and plausible crystalline source terranes. The apatite age components for the Altar Stone and Orcadian Basins are shown below their respective kernel density estimates. Extended Data Fig. 3 contains kernel density estimates of other ORS and New Red Sandstone (NRS) age datasets.

Laurentian basement signatures

The crystalline basement terranes of Great Britain and Ireland, from north to south, are Laurentia, Ganderia, Megumia and East Avalonia (Fig. 4a and Extended Data Fig. 1 ). Cadomia-Armorica is south of the Rheic Suture and encompasses basement rocks in western Europe, including northern France and Spain. East Avalonia, Megumia and Ganderia are partly separated by the Menai Strait Fault System (Fig. 4a ). Each terrane has discrete age components, which have imparted palaeogeographic information into overlying sedimentary basins 13 , 14 , 23 . Laurentia was a palaeocontinent that collided with Baltica and Avalonia (a peri-Gondwanan microcontinent) during the early Palaeozoic Caledonian Orogeny to form Laurussia 14 , 24 . West Avalonia is a terrane that includes parts of eastern Canada and comprised the western margin of Avalonia (Extended Data Fig. 1 ).

Statistical comparisons, using a Kolmogorov–Smirnov test, between zircon ages from the Laurentian crystalline basement and the Altar Stone indicate that at a 95% confidence level, no distinction in provenance is evident between Altar Stone detrital zircon U–Pb ages and those from the Laurentian basement. That is, we cannot reject the null hypothesis that both samples are from the same underlying age distribution (Kolmogorov–Smirnov test: P  > 0.05) (Fig. 3a ).

Detrital zircon age components, defined by concordant analyses from at least 4 grains in the Altar Stone, include maxima at 1,047, 1,091, 1,577, 1,663 and 1,790 Ma (Extended Data Fig. 2 ), corresponding to known tectonomagmatic events and sources within Laurentia and Baltica, including the Grenville (1,095–980 Ma), Labrador (1,690–1,590 Ma), Gothian (1,660–1,520 Ma) and Svecokarellian (1,920–1,770 Ma) orogenies 25 .

Laurentian terranes are crystalline lithologies north of the Iapetus Suture Zone (which marks the collision zone between Laurentia and Avalonia) and include the Southern Uplands, Midland Valley, Grampian, Northern Highlands and Hebridean Terranes (Fig. 4a ). Together, these terranes preserve a Proterozoic to Archaean record of zircon production 24 , distinct from the southern Gondwanan-derived terranes of Britain 20 , 26 (Fig. 4a and Extended Data Fig. 3 ).

Age data from Altar Stone rutile grains also point towards an ultimate Laurentian source with several discrete age components (Extended Data Fig. 4 and Supplementary Information  1 ). Group 2 rutile U–Pb analyses from the Altar Stone include Proterozoic ages from 1,724 to 591 Ma, with 3 grains constituting an age peak at 1,607 Ma, overlapping with Laurentian magmatism, including the Labrador and Pinwarian (1,690–1,380 Ma) orogenies 24 . Southern terranes in Britain are not characterized by a large Laurentian (Mesoproterozoic) crystalline age component 25 (Fig. 4b and Extended Data Fig. 3 ). Instead, terranes south of the Iapetus Suture are defined by Neoproterozoic to early Palaeozoic components, with a minor component from around two billion years ago (Figs. 3b and  4b ).

U–Pb analyses of apatite from the Altar Stone define two distinct age groupings. Group 2 apatite U–Pb analyses define a lower intercept age of 1,018 ± 24 Ma ( n  = 9) (Extended Data Fig. 5 ), which overlaps, within uncertainty, to a zircon age component at 1,047 Ma, consistent with a Grenville source 25 . Apatite Lu–Hf dates at 1,496 and 1,151 Ma also imply distinct Laurentian sources 25 (Fig. 4b , Extended Data Fig. 6 and Supplementary Information  2 ). Ultimately, the presence of Grenvillian apatite in the Altar Stone suggests direct derivation from the Laurentian basement, given the lability of apatite during prolonged chemical weathering 20 , 27 .

Grampian Terrane detrital grains

Apatite and rutile U–Pb analyses from the Altar Stone are dominated by regressions from common Pb that yield lower intercepts of 462 ± 4 Ma ( n  = 108) and 451 ± 8 Ma ( n  = 83), respectively (Extended Data Figs. 4 and 5 ). A single concordant zircon analysis also yields an early Palaeozoic age of 498 ± 17 Ma. Hence, with uncertainty from both lower intercepts, Group 1 apatite and rutile analyses demonstrate a mid-Ordovician (443–466 Ma) age component in the Altar Stone. These mid-Ordovician ages are confirmed by in situ apatite Lu–Hf analyses, which define a lower intercept of 470 ± 29 Ma ( n  = 16) (Extended Data Fig. 6 and Supplementary Information  2 ).

Throughout the Altar Stone are sub-planar 100–200-µm bands of concentrated heavy resistive minerals. These resistive minerals are interpreted to be magmatic in origin, given internal textures (oscillatory zonation), lack of mineral overgrowths (in all dated minerals) (Fig. 2 ) and the igneous apatite trace element signatures 27 (Extended Data Fig. 7 and Supplementary Information  3 ). Moreover, there is a general absence of detrital metamorphic zircon grains, further supporting a magmatic origin for these grains.

The most appropriate source region for such mid-Ordovician grains within Laurentian basement is the Grampian Terrane of northeast Scotland (Fig. 4a ). Situated between the Great Glen Fault to the north and the Highland Boundary Fault to the south, the terrane comprises Neoproterozoic to Lower Palaeozoic metasediments termed the Dalradian Supergroup 28 , which are intruded by a compositionally diverse suite of early Palaeozoic granitoids and gabbros (Fig. 4a ). The 466–443 Ma age component from Group 1 apatite and rutile U–Pb analyses overlaps with the terminal stages of Grampian magmatism and subsequent granite pluton emplacement north of the Highland Boundary Fault 28 (Fig. 4a ).

Geochemical classification plots for the Altar Stone apatite imply a compositionally diverse source, much like the lithological diversity within the Grampian Terrane 28 , with 61% of apatite classified as coming from felsic sources, 35% from mafic sources and 4% from alkaline sources (Extended Data Fig. 7 and Supplementary Information  3 ). Specifically, igneous rocks within the Grampian Terrane are largely granitoids, thus accounting for the predominance of felsic-classified apatite grains 29 . We posit that the dominant supply of detritus from 466–443 Ma came from the numerous similarly aged granitoids formed on the Laurentian margin 28 , which are present in both the Northern Highlands and the Grampian Terranes 28 (Fig. 4a ). The alkaline to calc-alkaline suites in these terranes are volumetrically small, consistent with the scarcity of alkaline apatite grains within the Altar Stone (Extended Data Fig. 7 ). Indeed, the Glen Dessary syenite at 447 ± 3 Ma is the only age-appropriate felsic-alkaline pluton in the Northern Highlands Terrane 30 .

The Stacey and Kramers 31 model of terrestrial Pb isotopic evolution predicts a 207 Pb/ 206 Pb isotopic ratio ( 207 Pb/ 206 Pb i ) of 0.8601 for 465 Ma continental crust. Mid-Ordovician regressions through Group 1 apatite and rutile U–Pb analyses yield upper intercepts for 207 Pb/ 206 Pb i of 0.8603 ± 0.0033 and 0.8564 ± 0.0014, respectively (Extended Data Figs. 4 and 5 and Supplementary Information  1 ). The similarity between apatite and rutile 207 Pb/ 206 Pb i implies they were sourced from the same Mid-Ordovician magmatic fluids. Ultimately, the calculated 207 Pb/ 206 Pb i value is consistent with the older (Laurentian) crust north of the Iapetus Suture in Britain 32 (Fig. 4a ).

Orcadian Basin ORS

The detrital zircon age spectra confirm petrographic associations between the Altar Stone and the ORS. Furthermore, the Altar Stone cannot be a New Red Sandstone (NRS) lithology of Permo-Triassic age. The NRS, deposited from around 280–240 Ma, unconformably overlies the ORS 14 . NRS, such as that within the Wessex Basin (Extended Data Fig. 1 ), has characteristic detrital zircon age components, including Carboniferous to Permian zircon grains, which are not present in the Altar Stone 1 , 23 , 26 , 33 , 34 (Extended Data Fig. 3 ).

An ORS classification for the Altar Stone provides the basis for further interpretation of provenance (Extended Data Figs. 1 and 8 ), given that the ORS crops out in distinct areas of Great Britain and Ireland, including the Anglo-Welsh border and south Wales, the Midland Valley and northeast Scotland, reflecting former Palaeozoic depocentres 14 (Fig. 4a ).

Previously reported detrital zircon ages and petrography show that ORS outcrops of the Anglo-Welsh Basin in the Cosheston Subgroup 1 and Senni Formation 2 are unlikely to be the sources of the Altar Stone (Fig. 4a ). ORS within the Anglo-Welsh Basin is characterized by mid-Palaeozoic zircon age maxima and minor Proterozoic components (Fig. 4a ). Ultimately, the detrital zircon age spectra of the Altar Stone are statistically distinct from the Anglo-Welsh Basin (Fig. 3a ). In addition, the ORS outcrops of southwest England (that is, south of the Variscan front), including north Devon and Cornwall (Cornubian Basin) (Fig. 4a ), show characteristic facies, including marine sedimentary structures and fossils along with a metamorphic fabric 13 , 26 , inconsistent with the unmetamorphosed, terrestrial facies of the Altar Stone 1 , 11 .

Another ORS succession with published age data for comparison is the Dingle Peninsula Basin, southwest Ireland. However, the presence of late Silurian (430–420 Ma) and Devonian (400–350 Ma) apatite, zircon and muscovite from the Dingle Peninsula ORS discount a source for the Altar Stone from southern Ireland 20 . The conspicuous absence of apatite grains of less than 450 Ma in age in the Altar Stone precludes the input of Late Caledonian magmatic grains to the source sediment of the Altar Stone and demonstrates that the ORS of the Altar Stone was deposited prior to or distally from areas of Late Caledonian magmatism, unlike the ORS of the Dingle Peninsula 20 . Notably, no distinction in provenance between the Anglo-Welsh Basin and the Dingle Peninsula ORS is evident (Kolmogorov–Smirnov test: P  > 0.05), suggesting that ORS basins south of the Iapetus Suture are relatively more homogenous in terms of their detrital zircon age components (Fig. 4a ).

In Scotland, ORS predominantly crops out in the Midland Valley and Orcadian Basins (Fig. 4a ). The Midland Valley Basin is bound between the Highland Boundary Fault and the Iapetus Suture and is located within the Midland Valley and Southern Uplands Terranes. Throughout Midland Valley ORS stratigraphy, detrital zircon age spectra broadly show a bimodal age distribution between Lower Palaeozoic and Mesoproterozoic components 35 , 36 (Extended Data Fig. 3 ). Indeed, throughout 9 km of ORS stratigraphy in the Midland Valley Basin and across the Sothern Uplands Fault, no major changes in provenance are recognized 36 (Fig. 4a ). Devonian zircon, including grains as young as 402 ± 5 Ma from the northern ORS in the Midland Valley Basin 36 , further differentiates this basin from the Altar Stone (Fig. 3a and Extended Data Fig. 3 ). The scarcity of Archaean to late Palaeoproterozoic zircon grains within the Midland Valley ORS shows that the Laurentian basement was not a dominant detrital source for those rocks 35 . Instead, ORS of the Midland Valley is primarily defined by zircon from 475 Ma interpreted to represent the detrital remnants of Ordovician volcanism within the Midland Valley Terrane, with only minor and periodic input from Caledonian plutonism 35 .

The Orcadian Basin of northeast Scotland, within the Grampian and Northern Highlands terranes, contains a thick package of mostly Mid-Devonian ORS, around 4 km thick in Caithness and up to around 8 km thick in Shetland 14 (Fig. 4a ). The detrital zircon age spectra from Orcadian Basin ORS provides the closest match to the Altar Stone detrital ages 25 (Fig. 3 and Extended Data Fig. 8 ). A Kolmogorov–Smirnov test on age spectra from the Altar Stone and the Orcadian Basin fails to reject the null hypothesis that they are derived from the same underlying distribution (Kolmogorov–Smirnov test: P  > 0.05) (Fig. 3a ). To the north, ORS on the Svalbard archipelago formed on Laurentian and Baltican basement rocks 37 . Similar Kolmogorov–Smirnov test results, where each detrital zircon dataset is statistically indistinguishable, are obtained for ORS from Svalbard, the Orcadian Basin and the Altar Stone.

Apatite U–Pb age components from Orcadian Basin samples from Spittal, Caithness (AQ1) and Cruaday, Orkney (CQ1) (Fig. 4a ) match those from the Altar Stone. Group 2 apatite from the Altar Stone at 1,018 ± 24 Ma is coeval with a Grenvillian age from Spittal at 1,013 ± 35 Ma. Early Palaeozoic apatite components at 473 ± 25 Ma and 466 ± 6 Ma, from Caithness and Orkney, respectively (Extended Data Fig. 5 and Supplementary Information  1 ), are also identical, within uncertainty, to Altar Stone Group 1 (462 ± 4 Ma) apatite U–Pb analyses and a Lu–Hf component at 470 ± 28 Ma supporting a provenance from the Orcadian Basin for the Altar Stone (Extended Data Fig. 6 and Supplementary Information  2 ).

During the Palaeozoic, the Orcadian Basin was situated between Laurentia and Baltica on the Laurussian palaeocontinent 14 . Correlations between detrital zircon age components imply that both Laurentia and Baltica supplied sediment into the Orcadian Basin 25 , 36 . Detrital grains from more than 900 Ma within the Altar Stone are consistent with sediment recycling from intermediary Neoproterozoic supracrustal successions (for example, Dalradian Supergroup) within the Grampian Terrane but also from the Särv and Sparagmite successions of Baltica 25 , 36 . At around 470 Ma, the Grampian Terrane began to denude 28 . Subsequently, first-cycle detritus, such as that represented by Group 1 apatite and rutile, was shed towards the Orcadian Basin from the southeast 25 .

Thus, the resistive mineral cargo in the Altar Stone represents a complex mix of first and multi-cycle grains from multiple sources. Regardless of total input from Baltica versus Laurentia into the Orcadian Basin, crystalline terranes north of the Iapetus Suture (Fig. 4a ) have distinct age components that match the Altar Stone in contrast to Gondwanan-derived terranes to the south.

The Altar Stone and Neolithic Britain

Isotopic data for detrital zircon and rutile (U–Pb) and apatite (U–Pb, Lu–Hf and trace elements) indicate that the Altar Stone of Stonehenge has a provenance from the ORS in the Orcadian Basin of northeast Scotland (Fig. 4a ). Given this detrital mineral provenance, the Altar Stone cannot have been sourced from southern Britain (that is, south of the Iapetus Suture) (Fig. 4a ), including the Anglo-Welsh Basin 1 , 2 .

Some postulate a glacial transport mechanism for the Mynydd Preseli (Fig. 4a ) bluestones to Salisbury Plain 38 , 39 . However, such transport for the Altar Stone is difficult to reconcile with ice-sheet reconstructions that show a northwards movement of glaciers (and erratics) from the Grampian Mountains towards the Orcadian Basin during the Last Glacial Maximum and, indeed, previous Pleistocene glaciations 40 , 41 . Moreover, there is little evidence of extensive glacial deposition in central southern Britain 40 , nor are Scottish glacial erratics found at Stonehenge 42 . Sr and Pb isotopic signatures from animal and human remains from henges on Salisbury Plain demonstrate the mobility of Neolithic people within Britain 32 , 43 , 44 , 45 . Furthermore, shared architectural elements and rock art motifs between Neolithic monuments in Orkney, northern Britain, and Ireland point towards the long-distance movement of people and construction materials 46 , 47 .

Thus, we posit that the Altar Stone was anthropogenically transported to Stonehenge from northeast Scotland, consistent with evidence of Neolithic inhabitation in this region 48 , 49 . Whereas the igneous bluestones were brought around 225 km from the Mynydd Preseli to Stonehenge 50 (Fig. 4a ), a Scottish provenance for the Altar Stone demands a transport distance of at least 750 km (Fig. 4a ). Nonetheless, even with assistance from beasts of burden 51 , rivers and topographical barriers, including the Grampians, Southern Uplands and the Pennines, along with the heavily forested landscape of prehistoric Britain 52 , would have posed formidable obstacles for overland megalith transportation.

At around 5000  bc , Neolithic people introduced the common vole ( Microtus arvalis ) from continental Europe to Orkney, consistent with the long-distance marine transport of cattle and goods 53 . A Neolithic marine trade network of quarried stone tools is found throughout Britain, Ireland and continental Europe 54 . For example, a saddle quern, a large stone grinding tool, was discovered in Dorset and determined to have a provenance in central Normandy 55 , implying the shipping of stone cargo over open water during the Neolithic. Furthermore, the river transport of shaped sandstone blocks in Britain is known from at least around 1500  bc (Hanson Log Boat) 56 . In Britain and Ireland, sea levels approached present-day heights from around 4000  bc 57 , and although coastlines have shifted, the geography of Britain and Ireland would have permitted sea routes southward from the Orcadian Basin towards southern England (Fig. 4a ). A Scottish provenance for the Altar Stone implies Neolithic transport spanning the length of Great Britain.

This work analysed two 30-µm polished thin sections of the Altar Stone (MS3 and 2010K.240) and two sections of ORS from northeast Scotland (Supplementary Information  4 ). CQ1 is from Cruaday, Orkney (59° 04′ 34.2″ N, 3° 18′ 54.6″ W), and AQ1 is from near Spittal, Caithness (58° 28′ 13.8″ N, 3° 27′ 33.6″ W). Conventional optical microscopy (transmitted and reflected light) and automated mineralogy via a TESCAN Integrated Mineral Analyser gave insights into texture and mineralogy and guided spot placement during LA-ICP–MS analysis. A CLARA field emission scanning electron microscope was used for textural characterization of individual minerals (zircon, apatite and rutile) through high-resolution micrometre-scale imaging under both back-scatter electron and cathodoluminescence. The Altar Stone is a fine-grained and well-sorted sandstone with a mean grain size diameter of ≤300 µm. Quartz grains are sub-rounded and monocrystalline. Feldspars are variably altered to fine-grained white mica. MS3 and 2010K.240 have a weakly developed planar fabric and non-planar heavy mineral laminae approximately 100–200 µm thick. Resistive heavy mineral bands are dominated by zircon, rutile, and apatite, with grains typically 10–40 µm wide. The rock is mainly cemented by carbonate, with localized areas of barite and quartz cement. A detailed account of Altar Stone petrography is provided in refs. 1 , 59 .

Zircon isotopic analysis

Zircon u–pb methods.

Two zircon U–Pb analysis sessions were completed at the GeoHistory facility in the John De Laeter Centre (JdLC), Curtin University, Australia. Ablations within zircon grains were created using an excimer laser RESOlution LE193 nm ArF with a Laurin Technic S155 cell. Isotopic data was collected with an Agilent 8900 triple quadrupole mass spectrometer, with high-purity Ar as the plasma carrier gas (flow rate 1.l min −1 ). An on-sample energy of ~2.3–2.7 J cm −2 with a 5–7 Hz repetition rate was used to ablate minerals for 30–40 s (with 25–60 s of background capture). Two cleaning pulses preceded analyses, and ultra-high-purity He (0.68 ml min −1 ) and N 2 (2.8 ml min −1 ) were used to flush the sample cell. A block of reference mineral was analysed following 15–20 unknowns. The small, highly rounded target grains of the Altar Stone (usually <30 µm in width) necessitated using a spot size diameter of ~24 µm for all ablations. Isotopic data was reduced using Iolite 4 60 with the U-Pb Geochronology data reduction scheme, followed by additional calculation and plotting via IsoplotR 61 . The primary matrix-matched reference zircon 62 used to correct instrumental drift and mass fractionation was GJ-1, 601.95 ± 0.40 Ma. Secondary reference zircon included Plešovice 63 , 337.13 ± 0.37 Ma, 91500 64 , 1,063.78 ± 0.65 Ma, OG1 65 3,465.4 ± 0.6 Ma and Maniitsoq 66 3,008.7 ± 0.6 Ma. Weighted mean U–Pb ages for secondary reference materials were within 2 σ uncertainty of reported values (Supplementary Information  5 ).

Zircon U–Pb results

Across two LA-ICP–MS sessions, 83 U–Pb measurements were obtained on as many zircon grains; 41 were concordant (≤10% discordant), where discordance is defined using the concordia log distance (%) approach 67 . We report single-spot (grain) concordia ages, which have numerous benefits over conventional U–Pb/Pb–Pb ages, including providing an objective measure of discordance that is directly coupled to age and avoids the arbitrary switch between 206 Pb/ 238 U and 207 Pb/ 206 Pb. Furthermore, given the spread in ages (Early Palaeozoic to Archaean), concordia ages provide optimum use of both U–Pb/Pb–Pb ratios, offering greater precision over 206 Pb/ 238 U or 207 Pb/ 206 Pb ages alone.

Given that no direct sampling of the Altar Stone is permitted, we are limited in the amount of material available for destructive analysis, such as LA-ICP–MS. We collate our zircon age data with the U–Pb analyses 1 of FN593 (another fragment of the Altar Stone), filtered using the same concordia log distance (%) discordance filter 67 . The total concordant analyses used in this work is thus 56 over 3 thin sections, each showing no discernible provenance differences. Zircon concordia ages span from 498 to 2,812 Ma. Age maxima (peak) were calculated after Gehrels 68 , and peak ages defined by ≥4 grains include 1,047, 1,091, 1,577, 1,663 and 1,790 Ma.

For 56 concordant ages from 56 grains at >95% certainty, the largest unmissed fraction is calculated at 9% of the entire uniform detrital population 69 . In any case, the most prevalent and hence provenance important components will be sampled for any number of analyses 69 . We analysed all zircon grains within the spatial limit of the technique in the thin sections 70 . We used in situ thin-section analysis, which can mitigate against contamination and sampling biases in detrital studies 71 . Adding apatite (U–Pb and Lu–Hf) and rutile (U–Pb) analyses bolsters our confidence in provenance interpretations as these minerals will respond dissimilarly during transport.

Comparative zircon datasets

Zircon U–Pb compilations of the basement terranes of Britain and Ireland were sourced from refs. 20 , 26 . ORS detrital zircon datasets used for comparison include isotopic data from the Dingle Peninsula Basin 20 , Anglo-Welsh Basin 72 , Midland Valley Basin 35 , Svalbard ORS 37 and Orcadian Basin 25 . NRS zircon U–Pb ages were sourced from the Wessex Basin 33 . Comparative datasets were filtered for discordance as per our definition above 20 , 26 . Kernel density estimates for age populations were created within IsoplotR 61 using a kernel and histogram bandwidth of 50 Ma.

A two-sample Kolmogorov–Smirnov statistical test was implemented to compare the compiled zircon age datasets with the Altar Stone (Supplementary Information  6 ). This two-sided test compares the maximum probability difference between two cumulative density age functions, evaluating the null hypothesis that both age spectra are drawn from the same distribution based on a critical value dependent on the number of analyses and a chosen confidence level.

The number of zircon ages within the comparative datasets used varies from the Altar Stone ( n  = 56) to Laurentia ( n  = 2,469). Therefore, to address the degree of dependence on sample n , we also implemented a Monte Carlo resampling (1,000 times) procedure for the Kolmogorov–Smirnov test, including the uncertainty on each age determination to recalculate P values and standard deviations (Supplementary Information  7 ), based on the resampled distribution of each sample. The results from Kolmogorov–Smirnov tests, using Monte Carlo resampling (and multidimensional analysis), taking uncertainty due to sample n into account, also support the interpretation that at >95% certainty, no distinction in provenance can be made between the Altar Stone zircon age dataset ( n  = 56) and those from the Orcadian Basin ( n  = 212), Svalbard ORS ( n  = 619 ) and the Laurentian basement (Supplementary Information  7 ).

MDS plots for zircon datasets were created using the MATLAB script of ref.  58 . Here, we adopted a bootstrap resampling (>1,000 times) with Procrustes rotation of Kolmogorov–Smirnov values, which outputs uncertainty ellipses at a 95% confidence level (Fig. 3a ). In MDS plots, stress is a goodness of fit indicator between dissimilarities in the datasets and distances on the MDS plot. Stress values below 0.15 are desirable 58 . For the MDS plot in Fig. 3a , the value is 0.043, which indicates an “excellent” fit 58 .

Rutile isotopic analysis

Rutile u–pb methods.

One rutile U–Pb analysis session was completed at the GeoHistory facility in the JdLC, Curtin University, Australia. Rutile grains were ablated (24 µm) using a Resonetics RESOlution M-50A-LR sampling system, using a Compex 102 excimer laser, and measured using an Agilent 8900 triple quadrupole mass analyser. The analytical parameters included an on-sample energy of 2.7 J cm −2 , a repetition rate of 7 Hz for a total analysis time of 45 s, and 60 s of background data capture. The sample chamber was purged with ultrahigh purity He at a flow rate of 0.68 l min −1 and N 2 at 2.8 ml min −1 .

U–Pb data for rutile analyses was reduced against the R-10 rutile primary reference material 73 (1,091 ± 4 Ma). The secondary reference material used to monitor the accuracy of U–Pb ratios was R-19 rutile. The mean weighted 238 U/ 206 Pb age obtained for R-19 was 491 ± 10 (mean squared weighted deviation (MSWD) = 0.87, p ( χ 2 ) = 0.57) within uncertainty of the accepted age 74 of 489.5 ± 0.9 Ma.

Rutile grains with negligible Th concentrations can be corrected for common Pb using a 208 Pb correction 74 . Previously used thresholds for Th content have included 75 , 76 Th/U < 0.1 or a Th concentration >5% U. However, Th/U ratios for rutile from MS3 are typically > 1; thus, a 208 Pb correction is not applicable. Instead, we use a 207 -based common Pb correction 31 to account for the presence of common Pb. Rutile isotopic data was reduced within Iolite 4 60 using the U–Pb Geochronology reduction scheme and IsoplotR 61 .

Rutile U–Pb Results

Ninety-two rutile U–Pb analyses were obtained in a U–Pb single session, which defined two coherent age groupings on a Tera–Wasserburg plot.

Group 1 constitutes 83 U–Pb rutile analyses, forming a well-defined mixing array on a Tera-Wasserburg plot between common and radiogenic Pb components. This array yields an upper intercept of 207 Pb/ 206 Pb i  = 0.8563 ± 0.0014. The lower intercept implies an age of 451 ± 8 Ma. The scatter about the line (MSWD = 2.7) is interpreted to reflect the variable passage of rutile of diverse grain sizes through the radiogenic Pb closure temperature at ~600 °C during and after magmatic crystallization 77 .

Group 2 comprises 9 grains, with 207 Pb corrected 238 U/ 206 Pb ages ranging from 591–1,724 Ma. Three grains from Group 2 define an age peak 68 at 1,607 Ma. Given the spread in U–Pb ages, we interpret these Proterozoic grains to represent detrital rutile derived from various sources.

Apatite isotopic analysis

Apatite u–pb methods.

Two apatite U–Pb LA-ICP–MS analysis sessions were conducted at the GeoHistory facility in the JdLC, Curtin University, Australia. For both sessions, ablations were created using a RESOlution 193 nm excimer laser ablation system connected to an Agilent 8900 ICP–MS with a RESOlution LE193 nm ArF and a Laurin Technic S155 cell ICP–MS. Other analytical details include a fluence of 2 J cm 2 and a 5 Hz repetition rate. For the Altar Stone section (MS3) and the Orcadian Basin samples (Supplementary Information  4 ), 24- and 20-µm spot sizes were used, respectively.

The matrix-matched primary reference material used for apatite U–Pb analyses was the Madagascar apatite (MAD-1) 78 . A range of secondary reference apatite was analysed, including FC-1 79 (Duluth Complex) with an age of 1,099.1 ± 0.6 Ma, Mount McClure 80 , 81 526 ± 2.1 Ma, Otter Lake 82 913 ± 7 Ma and Durango 31.44 ± 0.18 83  Ma. Anchored regressions (through reported 207 Pb/ 206 Pb i values) for secondary reference material yielded lower intercept ages within 2 σ uncertainty of reported values (Supplementary Information  8 ).

Altar Stone apatite U–Pb results

This first session of apatite U–Pb of MS3 from the Altar Stone yielded 117 analyses. On a Tera–Wasserburg plot, these analyses form two discordant mixing arrays between common and radiogenic Pb components with distinct lower intercepts.

The array from Group 2 apatite, comprised of 9 analyses, yields a lower intercept equivalent to an age of 1,018 ± 24 Ma (MSWD = 1.4) with an upper intercept 207 Pb/ 206 Pb i  = 0.8910 ± 0.0251. The f 207 % (the percentage of common Pb estimated using the 207 Pb method) of apatite analyses in Group 2 ranges from 16.66–88.8%, with a mean of 55.76%.

Group 1 apatite is defined by 108 analyses yielding a lower intercept of 462 ± 4 Ma (MSWD = 2.4) with an upper intercept 207 Pb/ 206 Pb i  = 0.8603 ± 0.0033. The f 207 % of apatite analyses in Group 1 range from 10.14–99.91%, with a mean of 78.65%. The slight over-dispersion of the apatite regression line may reflect some variation in Pb closure temperature in these crystals 84 .

Orcadian basin apatite U–Pb results

The second apatite U–Pb session yielded 138 analyses from samples CQ1 and AQ1. These data form three discordant mixing arrays between radiogenic and common Pb components on a Tera–Wasserburg plot.

An unanchored regression through Group 1 apatite ( n  = 14) from the Cruaday sample (CQ1) yields a lower intercept of 473 ± 25 Ma (MSWD = 1.8) with an upper intercept of 207 Pb/ 206 Pb i  = 0.8497 ± 0.0128. The f 207 % spans 38–99%, with a mean value of 85%.

Group 1 from the Spittal sample (AQ1), comprised of 109 analyses, yields a lower intercept equal to 466 ± 6 Ma (MSWD = 1.2). The upper 207 Pb/ 206 Pb i is equal to 0.8745 ± 0.0038. f 207 % values for this group range from 6–99%, with a mean value of 83%. A regression through Group 2 analyses ( n  = 17) from the Spittal sample yields a lower intercept of 1,013 ± 35 Ma (MSWD = 1) and an upper intercept 207 Pb/ 206 Pb i of 0.9038 ± 0.0101. f 207 % values span 25–99%, with a mean of 76%. Combined U–Pb analyses from Groups 1 from CQ1 and AQ1 ( n  = 123) yield a lower intercept equivalent to 466 ± 6 Ma (MSWD = 1.4) and an upper intercept 207 Pb/ 206 Pb i of 0.8726 ± 0.0036, which is presented beneath the Orcadian Basin kernel density estimate in Fig. 4b .

Apatite Lu–Hf methods

Apatite grains were dated in thin-section by the in situ Lu–Hf method at the University of Adelaide, using a RESOlution-LR 193 nm excimer laser ablation system, coupled to an Agilent 8900 ICP–MS/MS 85 , 86 . A gas mixture of NH 3 in He was used in the mass spectrometer reaction cell to promote high-order Hf reaction products, while equivalent Lu and Yb reaction products were negligible. The mass-shifted (+82 amu) reaction products of 176+82 Hf and 178+82 Hf reached the highest sensitivity of the measurable range and were analysed free from isobaric interferences. 177 Hf was calculated from 178 Hf, assuming natural abundances. 175 Lu was measured on mass as a proxy 85 for 176 Lu. Laser ablation was conducted with a laser beam of 43 µm at 7.5 Hz repetition rate and a fluency of approximately 3.5 J cm −2 . The analysed isotopes (with dwell times in ms between brackets) are 27 Al (2), 43 Ca (2), 57 Fe (2), 88 Sr (2), 89+85 Y (2), 90+83 Zr (2), 140+15 Ce (2), 146 Nd (2), 147 Sm (2), 172 Yb (5), 175 Lu (10), 175+82 Lu (50), 176+82 Hf (200) and 178+82 Hf (150). Isotopes with short dwell times (<10 ms) were measured to confirm apatite chemistry and to monitor for inclusions. 175+82 Lu was monitored for interferences on 176+82 Hf.

Relevant isotope ratios were calculated in LADR 87 using NIST 610 as the primary reference material 88 . Subsequently, reference apatite OD-306 78 (1,597 ± 7 Ma) was used to correct the Lu–Hf isotope ratios for matrix-induced fractionation 86 , 89 . Reference apatites Bamble-1 (1,597 ± 5 Ma), HR-1 (344 ± 2 Ma) and Wallaroo (1,574 ± 6 Ma) were monitored for accuracy verification 85 , 86 , 90 . Measured Lu–Hf dates of 1,098 ± 7 Ma, 346.0 ± 3.7 Ma and 1,575 ± 12 Ma, respectively, are in agreement with published values. All reference materials have negligible initial Hf, and weighted mean Lu–Hf dates were calculated in IsoplotR 61 directly from the (matrix-corrected) 176 Hf/ 176 Lu ratios.

For the Altar Stone apatites, which have variable 177 Hf/ 176 Hf compositions, single-grain Lu–Hf dates were calculated by anchoring isochrons to an initial 177 Hf/ 176 Hf composition 90 of 3.55 ± 0.05, which spans the entire range of initial 177 Hf/ 176 Hf ratios of the terrestrial reservoir (for example, ref. 91 ). The reported uncertainties for the single-grain Lu–Hf dates are presented as 95% confidence intervals, and dates are displayed on a kernel density estimate plot.

Apatite Lu–Hf results

Forty-five apatite Lu–Hf analyses were obtained from 2010K.240. Those with radiogenic Lu ingrowth or lacking common Hf gave Lu–Hf ages, defining four coherent isochrons and age groups.

Group 1, defined by 16 grains, yields a Lu–Hf isochron with a lower intercept of 470 ± 28 Ma (MSWD = 0.16, p ( χ 2 ) = 1). A second isochron through 5 analyses (Group 2) constitutes a lower intercept equivalent to 604 ± 38 Ma (MSWD = 0.14, p ( χ 2 ) = 0.94). Twelve apatite Lu–Hf analyses define Group 3 with a lower intercept of 1,123 ± 42 Ma (MSWD = 0.75, p ( χ 2 ) = 0.68). Three grains constitute the oldest grouping, Group 4 at 1,526 ± 186 Ma (MSWD = 0.014, p ( χ 2 ) = 0.91).

Apatite trace elements methods

A separate session of apatite trace element analysis was undertaken. Instrumentation and analytical set-up were identical to that described in 4.1. NIST 610 glass was the primary reference material for apatite trace element analyses. 43 Ca was used as the internal reference isotope, assuming an apatite Ca concentration of 40 wt%. Secondary reference materials included NIST 612 and the BHVO−2g glasses 92 . Elemental abundances for secondary reference material were generally within 5–10% of accepted values. Apatite trace element data was examined using the Geochemical Data Toolkit 93 .

Apatite trace elements results

One hundred and thirty-six apatite trace element analyses were obtained from as many grains. Geochemical classification schemes for apatite were used 29 , and three compositional groupings (felsic, mafic-intermediate, and alkaline) were defined.

Felsic-classified apatite grains ( n  = 83 (61% of analyses)) are defined by La/Nd of <0.6 and (La + Ce + Pr)/ΣREE (rare earth elements) of <0.5. The median values of felsic grains show a flat to slightly negative gradient on the chondrite-normalized REE plot from light to heavy REEs 94 . Felsic apatite’s median europium anomaly (Eu/Eu*) is 0.59, a moderately negative signature.

Mafic-intermediate apatite 29 ( n  = 48 (35% of grains)) are defined by (La + Ce + Pr)/ΣREE of 0.5–0.7 and a La/Nd of 0.5–1.5. In addition, apatite grains of this group typically exhibit a chondrite-normalized Ce/Yb of >5 and ΣREEs up to 1.25 wt%. Apatite grains classified as mafic-intermediate show a negative gradient on a chondrite-normalized REE plot from light to heavy REEs. The apatite grains of this group generally show the most enrichment in REEs compared to chondrite 94 . The median europium (Eu/Eu*) of mafic-intermediate apatite is 0.62, a moderately negative anomaly.

Lastly, alkaline apatite grains 29 ( n  = 5 (4% of analyses)) are characterized by La/Nd > 1.5 and a (La + Ce + Pr)/ΣREE > 0.8. The median europium anomaly of this group is 0.45. This grouping also shows elevated chondrite-normalized Ce/Yb of >10 and >0.5 wt% for the ΣREEs.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The isotopic and chemical data supporting the findings of this study are available within the paper and its supplementary information files.

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Acknowledgements

Funding was provided by an Australian Research Council Discovery Project (DP200101881). Sample material was loaned from the Salisbury Museum and Amgueddfa Cymru–Museum Wales and sampled with permission. The authors thank A. Green for assistance in accessing the Salisbury Museum material; B. McDonald, N. Evans, K. Rankenburg and S. Gilbert for their help during isotopic analysis; and P. Sampaio for assistance with statistical analysis. Instruments in the John de Laeter Centre, Curtin University, were funded via AuScope, the Australian Education Investment Fund, the National Collaborative Research Infrastructure Strategy, and the Australian Government. R.E.B. acknowledges a Leverhulme Trust Emeritus Fellowship.

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Anthony J. I. Clarke & Christopher L. Kirkland

Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK

Richard E. Bevins & Nick J. G. Pearce

Department of Earth Sciences, The University of Adelaide, Adelaide, South Australia, Australia

Stijn Glorie

Institute of Archaeology, University College London, London, UK

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Contributions

A.J.I.C.: writing, original draft, formal analysis, investigation, visualization, project administration, conceptualization and methodology. C.L.K.: supervision, resources, formal analysis, funding acquisition, writing, review and editing, conceptualization and methodology. R.E.B.: writing, review and editing, resources and conceptualization. N.J.G.P.: writing, review and editing, resources and conceptualization. S.G.: resources, formal analysis, funding acquisition, writing, review and editing, supervision, and methodology. R.A.I.: writing, review and editing.

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Correspondence to Anthony J. I. Clarke .

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Extended data figures and tables

Extended data fig. 1 geological maps of potential source terranes for the altar stone..

a , Schematic map of the North Atlantic region with the crystalline terranes in the Caledonian-Variscan orogens depicted prior to the opening of the North Atlantic, adapted after ref.  95 . b , Schematic map of Britain and Ireland, showing outcrops of Old Red Sandstone, basement terranes, and major faults with reference to Stonehenge.

Extended Data Fig. 2 Altar Stone zircon U–Pb data.

a , Tera-Wasserburg plot for all concordant (≤10% discordant) zircon analyses reported from three samples of the Altar Stone. Discordance is defined using the concordia log % distance approach, and analytical ellipses are shown at the two-sigma uncertainty level. The ellipse colour denotes the sample. Replotted isotopic data for thin-section FN593 is from ref. 1 . b , Kernel density estimate for concordia U–Pb ages of concordant zircon from the Altar Stone, using a kernel and histogram bandwidth of 50 Ma. Fifty-six concordant analyses are shown from 113 measurements. A rug plot is given below the kernel density estimate, marking the age of each measurement.

Extended Data Fig. 3 Comparative kernel density estimates of concordant zircon concordia ages from the Altar Stone, crystalline sources terranes, and comparative sedimentary rock successions.

Each plot uses a kernel and histogram bandwidth of 50 Ma. The zircon U–Pb geochronology source for each comparative dataset is shown with their respective kernel density estimate. Zircon age data for basement terranes (right side of the plot) was sourced from refs. 20 , 26 .

Extended Data Fig. 4 Plots of rutile U–Pb ages.

a , Tera-Wasserburg plot of rutile U–Pb analyses from the Altar Stone (thin-section MS3). Isotopic data is shown at the two-sigma uncertainty level. b , Kernel density estimate for Group 2 rutile 207 Pb corrected 206 Pb/ 238 U ages, using a kernel and histogram bandwidth of 25 Ma. The rug plot below the kernel density estimate marks the age for each measurement.

Extended Data Fig. 5 Apatite Tera-Wasserburg U–Pb plots for the Altar Stone and Orcadian Basin.

a , Altar Stone apatite U–Pb analyses from thin-section MS3. b , Orcadian Basin apatite U–Pb analyses from sample AQ1, Spittal, Caithness. c , Orcadian Basin apatite U–Pb analyses from sample CQ1, Cruaday, Orkney. All data are shown as ellipses at the two-sigma uncertainty level. Regressions through U–Pb data are unanchored.

Extended Data Fig. 6 Combined kernel density estimate and histogram for apatite Lu–Hf single-grain ages from the Altar Stone.

Lu–Hf apparent ages from thin-section 2010K.240. Kernel and histogram bandwidth of 50 Ma. The rug plot below the kernel density estimate marks each calculated age. Single spot ages are calculated assuming an initial average terrestrial 177 Hf/ 176 Hf composition (see  Methods ).

Extended Data Fig. 7 Apatite trace element classification plots for the Altar Stone thin-section MS3.

Colours for all plots follow the geochemical discrimination defined in A. a , Reference 29  classification plot for apatite with an inset pie chart depicting the compositional groupings based on these geochemical ratios. b , The principal component plot of geochemical data from apatite shows the main eigenvectors of geochemical dispersion, highlighting enhanced Nd and La in the distinguishing groups. Medians for each group are denoted with a cross. c , Plot of total rare earth elements (REE) (%) versus (Ce/Yb) n with Mahalanobis ellipses around compositional classification centroids. A P = 0.5 in Mahalanobis distance analysis represents a two-sided probability, indicating that 50% of the probability mass of the chi-squared distribution for that compositional grouping is contained within the ellipse. This probability is calculated based on the cumulative distribution function of the chi-squared distribution. d , Chondrite normalized REE plot of median apatite values for each defined apatite classification type.

Extended Data Fig. 8 Cumulative probability density function plot.

Cumulative probability density function plot of comparative Old Red Sandstone detrital zircon U–Pb datasets (concordant ages) versus the Altar Stone. Proximity between cumulative density probability lines implies similar detrital zircon age populations.

Supplementary information

Supplementary information 1.

Zircon, rutile, and apatite U–Pb data for the Altar Stone and Orcadian Basin samples. A ) Zircon U–Pb data for MS3, 2010K.240, and FN593. B ) Zircon U–Pb data for secondary references. C ) Rutile U–Pb data for MS3. D ) Rutile U–Pb data for secondary references. E ) Session 1 apatite U–Pb data for MS3. F ) Session 1 apatite U–Pb data for secondary references. G ) Session 2 apatite U–Pb data for Orcadian Basin samples. H ) Session 2 apatite U–Pb data for secondary references.

Reporting Summary

Peer review file, supplementary information 2.

Apatite Lu–Hf data for the Altar Stone. A) Apatite Lu–Hf isotopic data and ages for thin-section 2010K.240. B) Apatite Lu–Hf data for secondary references.

Supplementary Information 3

Apatite trace elements for the Altar Stone. A) Apatite trace element data for MS3. B) Apatite trace element secondary reference values.

Supplementary Information 4–8

Supplementary Information 4 : Summary of analyses. Summary table of analyses undertaken in this work on samples from the Altar Stone and the Orcadian Basin. Supplementary Information 5: Summary of zircon U–Pb reference material. A summary table of analyses was obtained for zircon U–Pb secondary reference material run during this work. Supplementary Information 6: Kolmogorov–Smirnov test results. Table of D and P values for the Kolmogorov–Smirnov test on zircon ages from the Altar Stone and potential source regions. Supplementary Information 7: Kolmogorov–Smirnov test results, with Monte Carlo resampling. Table of D and P values for the Kolmogorov–Smirnov test (with Monte Carlo resampling) on zircon ages from the Altar Stone and potential source regions. Supplementary Information 8: Summary of apatite U–Pb reference material. A summary table of analyses was obtained for the apatite U–Pb secondary reference material run during this work.

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Clarke, A.J.I., Kirkland, C.L., Bevins, R.E. et al. A Scottish provenance for the Altar Stone of Stonehenge. Nature 632 , 570–575 (2024). https://doi.org/10.1038/s41586-024-07652-1

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Do cats experience grief? New research suggests they might

Joe Hernandez

Researchers found that cats showed signs of grief, such as eating and playing less, after a fellow pet had died. Getty Images hide caption

If a human or another animal close to them dies, does a cat grieve the loss?

That was the question a team of researchers from Oakland University in Michigan set out to answer when they surveyed hundreds of cat owners about their cat’s behavior after another cat or dog in the household passed away.

The data showed that cats exhibited behaviors associated with grief — such as eating and playing less — more often after the death of a fellow pet, suggesting they may in fact have been in mourning.

“It made me a little more optimistic that they are forming attachments with each other,” said Jennifer Vonk, a professor of psychology at Oakland University, who co-authored the study, published in the journal Applied Animal Behaviour Science .

“It’s not that I want the cats to be sad,” Vonk went on, “[but] there is a part of us, I think, as humans that wants to think that if something happens to us our pets would miss us.”

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Vonk acknowledged that there are some caveats to the research. An owner may have been projecting their own feelings of sadness on their surviving cat when reporting their symptoms, or the cat may have been trying to console the grief-stricken human. (Cat owners who felt more grief themselves reported more grief in their surviving cats, researchers found.)

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