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Syntax research at Stanford is focused on the development of theoretical models that yield insight into the complexity of word and sentence structure in human language.

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This approach unearths otherwise hidden and sometimes surprising connections, and it encourages us to consider how our investigations must ultimately fit into a consistent framework of understanding. 

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Research Article

Syntax at Hand: Common Syntactic Structures for Actions and Language

* E-mail: [email protected]

Affiliations L2C2- Institut des Sciences Cognitives, CNRS UMR 5304, Bron, France, Université Claude Bernard Lyon I, Lyon, France

Affiliations L2C2- Institut des Sciences Cognitives, CNRS UMR 5304, Bron, France, Centre de Référence «Déficiences Intellectuelles de Causes Rares» Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France, Université de Lyon, Faculté de Médecine Lyon Sud - Charles Mérieux, Lyon, France

Affiliations L2C2- Institut des Sciences Cognitives, CNRS UMR 5304, Bron, France, Université Claude Bernard Lyon I, Lyon, France, Centre de Référence «Déficiences Intellectuelles de Causes Rares» Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France, Université de Lyon, Faculté de Médecine Lyon Sud - Charles Mérieux, Lyon, France

Affiliations L2C2- Institut des Sciences Cognitives, CNRS UMR 5304, Bron, France, Université Claude Bernard Lyon I, Lyon, France, Service de Psychopathologie du Développement- Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France, Université de Lyon, Faculté de Médecine Lyon Sud - Charles Mérieux, Lyon, France

• Alice C. Roy, 
• Aurore Curie, 
• Tatjana Nazir, 
• Yves Paulignan, 
• Vincent des Portes, 
• Pierre Fourneret, 
• Viviane Deprez

• Published: August 22, 2013
• https://doi.org/10.1371/journal.pone.0072677
• Reader Comments

Evidence that the motor and the linguistic systems share common syntactic representations would open new perspectives on language evolution. Here, crossing disciplinary boundaries, we explore potential parallels between the structure of simple actions and that of sentences. First, examining Typically Developing (TD) children displacing a bottle with or without knowledge of its weight prior to movement onset, we provide kinematic evidence that the sub-phases of this displacing action (reaching + moving the bottle) manifest a structure akin to linguistic embedded dependencies. Then, using the same motor task, we reveal that children suffering from specific language impairment (SLI), whose core deficit affects syntactic embedding and dependencies, manifest specific structural motor anomalies parallel to their linguistic deficits. In contrast to TD children, SLI children performed the displacing-action as if its sub-phases were juxtaposed rather than embedded. The specificity of SLI’s structural motor deficit was confirmed by testing an additional control group: Fragile-X Syndrome patients, whose language capacity, though delayed, comparatively spares embedded dependencies, displayed slower but structurally normal motor performances. By identifying the presence of structural representations and dependency computations in the motor system and by showing their selective deficit in SLI patients, these findings point to a potential motor origin for language syntax.

Citation: Roy AC, Curie A, Nazir T, Paulignan Y, des Portes V, Fourneret P, et al. (2013) Syntax at Hand: Common Syntactic Structures for Actions and Language. PLoS ONE 8(8): e72677. https://doi.org/10.1371/journal.pone.0072677

Editor: Corrado Sinigaglia, University of Milan, Italy

Received: November 29, 2012; Accepted: July 18, 2013; Published: August 22, 2013

Copyright: © 2013 Roy 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.

Funding: This work has been supported by the Centre National de la Recherche Scientifique and ACR and PF were additionally supported by Centre National de la Recherche Scientifique and Agence Nationale pour la Recherche Samenta (ANR-12-SAMA-015-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

The nature of the relationships between language and motor control is currently the object of growing attention [ 1 ]. Up to now, however, empirical research has largely centered on the meaning of action words and their representation in our sensory and motor systems [2 for a review]. With their focus on the lexico-semantic domain, these studies have rarely addressed other core aspects of language such as its structural aspects and its syntax. Yet, the common involvement of Broca’s area in syntax and in the sensori-motor system points to possible convergence between these domains [ 3 , 4 ]. Positive evidence that syntax-based representations could be partially common to the motor and the linguistic systems would suggest that linguistic syntax could have exploited and built upon parts of a pre-existing “syntax” used by the motor system [ 5 – 7 ]. The present study provides support for this assumption.

Like verbs in spoken language, actions arguably manifest a comparable argument structure relating agents and objects [ 8 ]. Accordingly, they are commonly branded as ‘transitive’ when performed with or towards objects [ 9 ]. Knott [ 10 ] for instance, proposes that "the Logical Form" of a sentence reporting a cup-grabbing episode can be understood as a description of the sensorimotor processes involved in experiencing the episode. He argues that the LF of the sentence can be given a detailed sensorimotor characterization, and that many of the syntactic principles are actually sensorimotor in origin.

Similarly, drawing on modeling studies of motor planning, Jackendoff [ 11 , 12 ] suggested that actions are recursively structured in ways quite analogous to the hierarchical embedding that characterizes language syntax and further conjectured that the structure of certain sub-events within goal-oriented actions (e.g. preparing coffee) could even have "the flavor of variable binding and long distance dependencies" [12 p597] like those at play in the syntactic structures of questions or relative clauses. Jackendoff [12 p597] describes one such dependencies in the complex routine action of making coffee as follows: "For instance, suppose you go to take the coffee out of the freezer and discover you’re out of coffee. Then you may append to the [making coffee] structure a giant preparation of buying coffee, which involves finding your car keys, driving to the store, going into the store (…) and driving home. The crucial thing is that in this deeply embedded head (i.e. the buying action), what you take off the shelf (...is...) the same thing you need in the larger structure this action is embedded in".

Consider now in some detail the syntactic structure of a relative clause dependency in language. In a simple sentence like [ John grasped the bottle ], the complement of a transitive verb like “ grasped ”, i.e the nominal phrase [ the bottle ], generally occurs after the verb. In contrast, in a relative clause like ‘ [ This is the bottle (which) John grasped ] the nominal phrase [ the bottle ] is syntactically displaced to the front of the clause, so that it no longer appears after the verb. Yet, despite this displacement, the nominal phrase remains interpreted as the complement of the verb “ grasped ”. In syntactic theory, the link between the displaced position of a fronted nominal phrase and the position in which it is interpreted (i.e. here as a complement of the verb grasp) is modeled as a ‘distant dependency’ between the two syntactic positions of the nominal phrase. Syntacticians propose that a relative clause is a transform of a basic sentence in which the nominal complement of a verb has been displaced to the front of a clause leaving a silent copy in the position in which it originated and is interpreted e.g. [ This is the bottle (which) John grasped the bottle ]. Schematically, the abstract structure of a relative clause is as in Figure 1 : Here, S’ represents the relative clause, S, the original sentence, the arrow indicates the displacement i.e. the distant dependency between the nominal phrase (NP) and its silent copy represented here as the crossed NP : the bottle .

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The noun phrase "the bottle" appears twice, once when it is pronounced at the beginning of the main clause and as a trace in the position it is interpreted in i.e. as the object complement of the verb grasp of the relative clause. Note that this structure is characteristically asymmetric.

https://doi.org/10.1371/journal.pone.0072677.g001

‘Distant dependencies’ are also known in linguistics as filler-gap dependencies or operator-variable dependencies. All these dependencies involve relations akin to that between a noun and a pronoun that is two representations of the same element as in: (John thinks he will win, where ‘he’ = john) but where the pronoun is silent. ‘Distant dependencies’ have played a central role in linguistic theory in probing the hierarchical nature of sentence embedding [ 13 ]. As Ross [ 14 ] showed indeed, these dependencies are tightly constrained. In particular, although the distance between the displaced nominal phrase and its silent copy can span over several clauses if these are embedded, the dependency fails to be properly interpreted if the intervening clauses are coordinated or juxtaposed instead. Compare the following examples:

• (a). This is the heavy bottle (which) [John realized] (that) [Mary knows] (that) [he grasped [the bottle]]

(b). * This is the heavy bottle (which) [John smiled] (and) [Mary stretched] and [he grasped [the bottle]]

Please note that the asterisk in front of the sentence indicates that the sentence in (b) is ungrammatical and that the elements in parenthesis are optional in English. They can remain unpronounced so that respectively the two sentences can be realized as:

This is the heavy bottle John realized Mary knows he grasped vs. This is the heavy bottle John smiled Mary stretched and he grasped. In (a), the dependency between the fronted nominal phrase, the bottle and the position in which it is interpreted (e.g. as a complement of the verb grasp) spans over three embedded clauses, but the sentence is still natural. In (b) -though formed from the perfectly accep It should be noted that we are not claiming that motor syntax is as complex as linguistic syntax, nor that it shares all of its crucial aspects, but we are arguing that some rudimentary, but fundamental aspect of linguistic syntax could be traced back to relatively complex motor actions. sentence "John smiled and Mary stretched and he grasped the heavy bottle"- it is rather difficult to understand the fronted nominal phrase [ the bottle ] as the complement of the verb grasp and still obtain a fully natural sentence. Note that the actual linear distance between the fronted noun phrase and the silent copy [ the bottle ] after the verb grasp is the same in (a) and (b). What differs is the nature of the syntactic relationship that the intervening clauses entertain: embedded vs. coordinated. That is, what matters is the nature of the abstract structural relation that connects the components that intervene between the two pieces of the distant dependency, the nominal phrase and its silent copy. Hence, the break down of the distance dependency in (b) vs. (a) serves to reveal a fundamental distinction in the syntax of these two sentences that would otherwise not be immediately obvious from the simple sequential ordering of their components. The distinction in the structural relations between the component constituents is schematized in Figure 2 .

A: An embedded structure is essentially asymmetric and accepts distance dependency as in the example given in (a). By contrast a symmetric coordinated structure does not accept distance dependency.

https://doi.org/10.1371/journal.pone.0072677.g002

As the arrows indicate, a linguistic distant dependency can succeed when the intervening components are embedded, but it breaks down when they are coordinated or juxtaposed. This structural constraint, dubbed the "Coordinated Structure Constraint" in the linguistic literature, provides evidence of the fundamentally hierarchical and embedded nature of certain linguistic structures.

Following Jackendoff’s conjecture that comparable distant dependencies are found in the motor domain, we sought to use these to experimentally probe the nature of the abstract structural relations that connect the motor components of a transitive action.

Endeavoring to construct an analogous motor distant dependency, we used a basic goal-directed displacing-action task that consisted in reaching a bottle and moving it to another target location while manipulating the participant’s knowledge of its weight. Our task was designed, first, to build on existing evidence that a displacing motor action can be divided in two component sub-phases [ 15 ], a first sub-phase of [reach+grip] that unfolds before object contact, dubbed here the Reach sub-phase, and a second sub-phase of [lift+move] that unfolds after object contact, dubbed here the Move sub-phase ( Figure S1 ). Second, we chose to manipulate the weight of an opaque bottle because, in contrast to features such as shape, size or location, which are visually perceived and hence can come to affect the kinematics of a reach and grasp action before any object contact [ 16 ], weight is a somatosensory perception that affects movement kinematics only after object contact [ 17 – 19 ] as long as there are no visual (or other) cues to it. That is, weight information, is normally "encapsulated" in the second phase of a displace action, i.e. dubbed here the Move sub-phase. Yet, weight information could become accessible prior to object contact [e.g. 20-22], if the weight of a given object is experienced or known before critical movement onset. When known, weight information could be so to speak ‘raised out’ of the Move sub-phase where it is normally encapsulated, and become accessible to potentially affect kinematic parameters already in the Reach sub-phase. Such a displaced weight effect in the Reach sub-phase would form the motor equivalent of a ‘distant dependency’ between the point in the Reach sub-phase where the mental representation of object weight is integrated in movement kinematics and the point of object contact in the Move sub-phase where the object weight is physically accessed. Note that at this second point in the action structure i.e. at the point of contact, the pertinent object weight better matches the representation integrated earlier in the Reach component, or else a mismatch would occur. This implies that a representation of object weight must be part of the motor computation to allow a backward feedback similar to the relation posited in linguistics between a displaced nominal phrase and its silent copy.

Although there is a rather broad consensus in the motor literature that a simple object displacing action of the type we used can be subdivided into two distinctive sub-components [ 15 ], the nature of the structural relation between these two components has at this point not been investigated empirically. A priori, the two sub-phases of a displacing action could be structurally related in either of two ways: they could be merely sequentially juxtaposed in analogy with the coordinated linguistic structures in Figures 2 and 3A-B or entertain a complex hierarchical relation, a form of syntactic embedding, analogous to the embedded structure in Figures 2 and 3C-D . This subtle but key distinction is essential for comparing motor with linguistic structure because in language, as illustrated in Figure 2 , the two types of structural relations have characteristically distinct effects on distant dependencies. While juxtaposed constituents are largely independent from one another, i.e. there have no domination or inclusion relation, embedded constituents are hierarchically related and thus asymmetrically dependent with domination or inclusion relations. Manipulating access to object weight information, during or prior to action execution, by creating a distant dependency, allows us to probe the structural relation entertained by the two component sub-phases of a displacing action. When the weight of an object is unknown to the subject, the kinematic parameters should always adjust to weight after object contact, that is, in the Move sub-phase only: such cases, then do not afford the possibility to uncover a distinction between the two potential structural models for our displacing action depicted in Figure 3 . However, when the object-weight is known in advance, so that a potential distant dependency now arises between a motor weight representation before object contact and the point of object contact where weight is physically felt, the two models make different predictions. If the displacing-action has a juxtaposed structure (with two relatively independent and parallel sub-components), weight effects could be distributed over and affect the kinematic parameters of both sub-components symmetrically (red line in Figure 3 ) in analogy with what happens in a linguistic coordinated structure as the following (e.g. the heavy/light bottle, I reach it AND I move it) where the fronted nominal complement ‘[the heavy/light bottle] is resumed by an overt pronoun (it) in both constituents of the coordinated structure. That is, if the structure of the displacing action is as in Figure 3B , we expect weight to affect both the Reach sub-phase as the weight representation is accessible to affect the kinematic computation, and the Move sub-phase as this is where the object weight is actually felt. By contrast, if the two components of the displacing action are embedded and object properties computation is akin to a linguistic distant dependency, as we conjecture, prior weight knowledge could result in an asymmetric transfer of the weight effects to the topmost level of the hierarchical structure, i.e., to the ‘Reach sub-phase’ with a consequent reduction or absence of weight effects in the ‘Move sub-phase’ in analogy with the silent copy that a linguistic dependency leaves in the original complement position when a nominal phrase is displaced (e.g. the heavy/light bottle which I reach to move [the bottle]). In similarity with linguistic displacement, object weight effects could be so to speak ‘raised out’ of the Move sub-phase and be displaced to affect the Reach sub-phase, leaving in turn the kinematics parameters of the lower Move sub-component unaffected by weight, in analogy with the linguistic silent copy left after fronting in relative clauses [ 23 ].

AB: Sequential juxtaposition, analogous to [I reach-grip a bottle AND lift-move it]. When object weight is unknown prior to object contact (A), kinematic parameters adapt to object weight in the ‘Move sub-phase’ (schematically indicated by the red line). No effect of object weight is expected in the ‘Reach sub-phase’. By contrast, when object weight is known in advance (B), movement kinematics could differ for heavy and light objects conjointly in the ‘Reach sub-phase’ and the Move sub-phase i.e. [This heavy bottle, I reached-griped it AND lift-moved it]. CD: Syntactic embedding, analogous to [I reach-grip a bottle TO lift-move it]. When object weight is unknown kinematic parameters adapt to object weight in the ‘Move sub-phase’ only (C). When known prior to movement onset object weight effects could be front-moved from the Move sub-phase to the reach sub-phase(D), following this displacement the Move sub-phase kinematics would remain immune to object weight effects (i.e., [The heavy bottle that I reached-griped TO lift-move]).

https://doi.org/10.1371/journal.pone.0072677.g003

To test this hypothesis and probe the structural relation of the motor components of a simple structured action, we compared the behavior of Typically Developing (TD) children with that of children diagnosed with Specific Language Impairment (SLI). SLI refers to a deficit in language acquisition that occurs in children who are otherwise developing normal cognitive abilities (absence of mental retardation, no diagnosed motor deficit, no hearing loss, or identifiable neurological disease). We reasoned that if the two sub-components of our displacing action presented a hierarchical structure rather than a mere juxtaposition, SLI patients whose core deficit has been shown to affect among other complex hierarchical sentences and, even more specifically, relative clause structures [ 24 – 27 ] may present a parallel deficit in performing a structured motor action. Such evidence would support the hypothesis that motor control and syntax could share analog mechanisms, possibly grounded in common neural structures. Both groups of children were asked to displace one of two identically looking opaque bottles with a significant weight difference (50g vs. 500g). The bottle was placed at a fixed distance from the participants’ hand, under two weight-knowledge conditions: one in which the weight was unknown prior to movement execution (Unknown condition) and one in which weight was known in advance (Known condition). Participants were first familiarized with the two object weights to ensure they had acquired sensorimotor knowledge of each before kinematic acquisition. In the unknown condition, the bottles were presented with a random alternation in weight unbeknownst to the participants, so that they did not get information about the object weight until object contact in the Move sub-phase. In the known condition, in contrast, participants were provided with the relevant information about the object weight before movement execution, and trials with a specified weight were presented consecutively. TD’s behavior enabled us to uncover the structural representation of the displacing-action, while the behavior of the language impaired population allowed us to trace potential parallels between motor and linguistic impairment.

The distinction between the two structures depicted in Figure 3 rests on modulations of the effect of physical object weight as a function of prior weight-knowledge. Our analysis therefore focused on interactions between the factors Weight and Knowledge in each of the two sub-phases of the displacing-action. Whenever this interaction was significant, planned comparisons between heavy and light objects were performed. Additional statistics are given in Table S1 in File S1 .

TD children (n=7, 4 males, mean age 10 years and 6 months). Figure 4 in the left panel plots peak latencies for the analyzed kinematic parameters ( Figure S1 ). The critical interaction between Weight x Knowledge was observed for 4 parameters in the Reach- and 3 parameters in the Move sub-phases. Additionally the interaction between Weight x Knowledge was found on the whole action time (the time elapsed from the beginning of the Reach sub-phase to the very end of the Move sub-phase when the hand left the bottle). Planned comparison between heavy and light objects in the Known and Unknown conditions revealed that:

Horizontal line with (*) indicates significant planned comparison between heavy and light objects. Vertical line with (*) indicates significant main effects of Knowledge (all p<= .05).

https://doi.org/10.1371/journal.pone.0072677.g004

in the Unknown condition , when the weight was unknown prior to object contact, its effects were absent from the Reach sub-phase, and present only in the Move sub-phase. In this Move sub-phase, we found that heavy objects gave rise to delayed wrist acceleration peaks (F 1,6 =27.09; p=.002), velocity peaks (F 1,6 =27.64; p=.001), and deceleration peaks (F 1,6 =11.40; p=.01) as compared to light objects ( Figure 4 ). The amplitude of the acceleration peak and of the velocity peak were also smaller when displacing the heavy compared to the light objects, however, the interaction between Weight x Knowledge remained marginally significant (Table S1 in File S1 ). In sum, displacing the heavy object as opposed to the light one had a cost (delayed and decreased peaks) that translated in an overall longer whole action time (F 1,6 =6.68; p=.041).

In contrast, in the Known condition , when the object-weight was known in advance, the kinematic parameters adapted to the weight already in the Reach sub-phase. Reaching for the heavy objects yielded anticipated wrist acceleration peaks and maximum grip aperture (latency of first acceleration peak F 1,6 =12.24; p=.01; latency of second acceleration peak F 1,6 =7.89; p=.03; latency of maximum grip aperture F 1,6 =23.72; p=.003). Even more noticeably, weight effects failed to be evident in the Move sub-phase ( Figure 4 ); the light and heavy objects gave rise to equivalent profiles for the relevant kinematic parameters, even though direct contact with the object occurred only in this second sub-phase. Characteristically, in the Known condition, TD children exhibited a comparable whole action time for the two object weights, as if the cost of displacing a heavier object had been counterbalanced during the Reach sub-phase by an anticipation of its kinematics consequences. Note that the object weight effects in the Move sub-phase of the Unknown condition were the inverse of the object weight effects observed in the Reach sub-phase of the Known condition. That is, heavy objects gave rise to later and smaller peaks in the Move sub-phase of the Unknown condition, while expected heavy objects gave rise to earlier peaks in the Reach sub-phase of the Known condition. These anticipated peaks are readily understandable as a motor strategy to compensate the added cost of moving the heavy object on the whole action time, which was observed in the Unknown condition.

SLI children (n=7, 4 males, mean age 11 years, p = ns with respect to TD children age). None of the measured motor parameters (latencies or amplitudes) showed an interaction between Weight x Knowledge ( Figure 4 right panel; Table S1 in File S1 ).

In the Unknown and Known conditions , object weight effects were strictly confined to the Move sub-phase (that is after direct contact with the bottle had occurred). Moving the heavy object as compared to the lighter one resulted in later and smaller peaks (main effect of Weight on latencies of acceleration F 1,6 =29.93; p=.002, velocity F 1,6 =31.60; p=.001, and deceleration peaks F 1,6 =14.73; p=.009; main effect of Weight on amplitudes of acceleration F 1,6 =14.48; p=.009 and velocity F 1,6 =16.84; p=.006). The cost of object weight in the Move sub-phases was such that it impacted the whole action time in both the Unknown and known conditions (main effect of Weight on whole action time F 1,6 =42.92; p=.001).

Additionally in the Known condition , a symmetric main effect of Knowledge was observed in both the Reach and the Move sub-phases, consisting in shorter latencies (for both light and heavy objects alike) when object weight was known in advance by SLI children (In the Reach sub-phase: Time to second acceleration F 1,6 =10.39; p=.018, velocity F 1,6 =10.88; p=.016 and deceleration peaks F 1,6 =9.81; p=.02; In the Move sub-phase: Time to acceleration F 1,6 =5.88; p=.051, velocity F 1,6 =10.38; p=.016, and deceleration peaks F 1,6 =13.17; p=.011). Finally, the whole action time was overall shorter in the Known condition than in the Unknown condition (Main effect of Knowledge on whole action time F 1,6 =8.37; p=.028). These kinematic effects (i.e shorter latencies and whole action time in the Known condition) crucially testify that SLI children did not simply ignore weight information. In the Known condition, they clearly integrated the weight information of the object, but for them this information affected both subcomponents symmetrically. That is, knowing that the object was heavy/light did not translate into knowing how to shift the weight effects to the Reach component to adapt kinematic parameters appropriately.

Importantly, our results for the Unknown condition also provide evidence that SLI children did not otherwise show any gross motor impairment nor specific problem in dealing with object weight; when the object weight was unknown, SLI performance did not differ from those of TD children. Accordingly, an omnibus non parametric MANOVA performed with Group (TD, SLI) as a between-subject factor and Weight (heavy, light) and Knowledge (known, unknown) as within-subject factors revealed no main effect of Group (F=11.87; p = ns), but a significant three way interaction (F=38.49; p=.018). A non parametric MANOVA performed for each group separately, further confirmed that the within-subject factors Weight and Knowledge interacted in TD children movements (F=45.73; p=.01) but not in SLI children movements (F=11.32; p = ns).

Specificity of the syntactic motor deficit

To ascertain the specificity of SLI motor deficit we examined the performance of a group of Fragile X Syndrome (FXS) patients on the same motor task. FXS is the most common cause of inherited intellectual disabilities and the most common single gene cause of autism (90% of FXS patients present autistic-like behavior [ 28 ]). FXS offer an appropriate control for potential confounding factors coming from reduced cognitive resources or autistic traits as the border between SLI and autistic disorder is blurred [ 29 ]. Most importantly language acquisition in FXS is delayedm with first words appearing at 26,4 months instead of 11 for TD and 23 for SLI [ 30 , 31 ], however, the profile of FXS’ linguistic impairment differs from that of SLI subjects, as it centrally concerns speech rate, articulation, and pragmatic aspects of language. Crucially, the syntactic level of FXS subjects is thought to be delayed rather than deviant [ 30 , 32 , 33 ], and complex structures and distant dependencies have been observed to be spared [ 34 ]. We therefore asked FXS patients and age-matched healthy adults to perform the very same structured motor tasks.

FXS adults (n=7, mean age 25 years). For FXS adults, like for TD children, the critical interaction between Weight x Knowledge was observed for peak latencies of several parameters in the Reach- and Move sub-phases and for the whole action time ( Figure 5 left panel; Table S2 in File S1 ). Planned comparison between heavy and light objects in the Known and Unknown conditions revealed that:

Same conventions as in Figure 4.

https://doi.org/10.1371/journal.pone.0072677.g005

in the Unknown condition when the object weight was unknown prior to contact, effects of weight were absent from the Reach sub-phase and present in the Move sub-phase only (latencies of acceleration F 1,6 =74.75; p<.001, velocity F 1,6 =37.95; p<.001, and deceleration peaks F 1,6 =28.73; p=.001) affecting nevertheless the whole action time (F 1,6 =14.21; p=.009). By contrast, in the Known condition the kinematic parameters adapted to weight in the Reach sub-phase (latency of deceleration peak F 1,6 =7.42; p=.03; latency of maximum grip aperture F 1,6 =17.5; p=.006) enabling the whole action time to be immune to the effects of object weight.

Healthy Adults (n=7, mean age 25,4 years, p = ns with respect to FXS age). . For healthy adults effects of object weight were generally small as further witnessed by the absence of weight effects on whole action time. Yet, like for FXS adults and TD children, the critical interaction between Weight x Knowledge was observed on peak latencies and amplitudes ( Figure 5 right panel; Table S2 in File S1 ). Planned comparison between heavy and light objects in the Known and Unknown conditions revealed that:

in the Unknown condition , the effects of weight were absent from the Reach sub-phase and present in the Move sub-phase (planned comparison between heavy and light objects: acceleration peak latency F 1,6 =8.24; p=.02 and amplitude F 1,6 =18.54; p=.005). In contrast, in the Known condition when the object weight was known in advance, these effects were observed in the Reach sub-phase (planned comparison between heavy and light objects: deceleration peak latency F 1,6 =6.88; p=.039) but no longer in the Move sub-phase.

An Omnibus non parametric MANOVA with [Group (FXS, HA) as a between-subject factor and Weight (heavy, light) and Knowledge (known, unknown) as within-subject factors] revealed 1) a main effect of the factor Group (F=72.06; p=.004), FXS patients showing reduced amplitudes and delayed latencies with respect to healthy individuals ( Figure 5 , Table S2 in File S1 ); 2) an interaction between Group x Weight x Knowledge (F=33.40; p=.03). The non parametric MANOVA performed for each group separately confirmed that the within factors Weight and Knowledge interacted in FXS (F=44.44; p=.015), a similar result was found in healthy individuals though it did not reach significance (F=27.84; p=.078).

In sum, while movement kinematic parameters of SLI and TD children occurred in the same latency range and exhibited comparable amplitudes, SLI children differed from their control group in the ability to modulate kinematic parameters as a function of action structure. FXS patients, in contrast, differed from their control group with respect to their general movement amplitudes and latencies, but did not display deficits in their ability to modulate kinematic parameters as a function of action structure.

Crossing disciplinary boundaries, we explored whether the structure of simple actions could manifest a hierarchical embedding revealed by distant dependencies. We provided experimental evidence that the two sub-phases of a displacing action are asymmetrically structured in ways that owes more to embedding than to mere temporal juxtaposition. By manipulating when participants access object weight information, we devised a way to build a motor distant dependency in order to probe the nature of the structural relation that the two sub-phases of a displacing action entertain. When the weight of a displaced object is unknown, accessibility to weight information is governed by object contact. Consequently, weight can have an impact on kinematics only in the second component of the displace action, i.e. our Move sub-phase, and this, independently of how the two sub-phases are structured (Fig. 3AB). However, when weight information is available prior to object contact, so that participants are able to form a motor representation of the object weight prior to the onset of movement, only an embedded structure predicts that the impact of object weight on kinematics could asymmetrically transfer to the topmost action sub-phase, i.e. our Reach sub-phase, and leave the subordinate sub-phase almost unaffected. This transfer of the weight impact to the kinematic parameters of the Reach sub-phase, attests of a link between the two subcomponents that goes beyond mere juxtaposition.

As predicted, in the unknown weight condition, our results show that for all groups of participants alike, the object weight affected the kinematic parameters of the Move sub-phase, that is only after object contact: thus, the object weight information and the object weight kinematic impact were entirely encapsulated within the Move sub-phase. In contrast, when object weight was known in advance, our kinematic results crucially revealed that for TD children, HA and FXS patients, the kinematic impact of object weight shifted to the Reach sub-phase and was no longer encapsulated in the Move sub-phase. More strikingly and more significantly, this weight effect transfer was further accompanied by an almost complete disappearance of the weight effects from the Move sub-phase, despite the fact this sub-component is where direct contact with the objet and the weight somatosensory feedback takes place. It is thus as if the kinematic impact of the object weight had been entirely relocated from the Move sub-phase to the Reach sub-phase, leaving only a silent motor copy for feedback checking. We argue that only an embedding structure, as illustrated in Figure 3D , accurately models this observed pattern because, although an anticipated weight effect on the first sub-component could also be expected in a juxtaposed structure, this symmetric structure neither predicts nor explains the here observed weight effect disappearance from the second sub-component. Juxtaposed components are understood to be such, because they do not entertain relations beyond that of sequential, temporal or spatial, ordering. Given that the disappearance of kinematic weight effects from the Move sub-phase is a consequence of their anticipated impact on the Reach sub-phase, this weight effect transfer clearly suggests that the two components entertain relations that go beyond mere sequential ordering.

The relation between the point of object weight integration in the movement kinematic of the Reach sub-component and the point of object contact in the Move sub-component (where the weight is felt) presents a strong analogy to a syntactic operation of relative clause displacement in linguistic syntax. When known, the weight of an object is integrated into motor programming and execution prior to direct sensory contact with the object. Likewise, in a relative clause, a nominal phrase is pronounced, i.e. integrated in the speech computation before the position in which it is semantically interpreted. Furthermore, in motor embedding, the early integration of weight effects in the dominating Reach sub-component licenses a ‘silent’ motor copy of object weight in the Move sub-phase, quite analogous to the ‘silent’ copy of a displaced nominal phrase that linguistic theory posits after noun-phrase displacement [ 13 ]. That is, although the object weight is accessed via somatosensation after object contact, it no longer impacts the kinematic parameter at that point because weight effects were integrated earlier at a higher level of the action structure. Finally, recall that characteristically in language, ‘distant dependencies’ have been observed to lead acceptable sentences only across clauses that are embedded (This is the heavy bottle [John realized (which) Mary knows [he grasped]]), but not across clauses that are coordinated or juxtaposed (* ‘This is the heavy bottle (which) John smiled and Mary stretched and he grasped’). This linguistic hierarchical constraint dubbed “The Coordinate Structure Constraint” [ 14 ] seems here to be echoed in the motor system.

To further investigate whether the uncovered motor syntactic mechanisms at play in our displacing action displayed some fundamental aspects typical of linguistic syntax, we tested the movement structure of children with SLI. SLI children suffer from a disorder known to disrupt the development of a full-blown linguistic syntax. In particular, as it has been repeatedly observed, children with SLI commonly fail to produce and understand complex embedding and distant dependencies, particularly in relative clauses [24,25,35,36 but see 37 for an alternative statistical learning deficit hypothesis]. Furthermore, when prompted to do so, they have been observed to produce juxtaposition of matrix clauses instead. The sentence “I did it with my teacher, he’s called Doris” (the English rendering of a sentence produced by a French SLI patient, taken from 25) is a characteristic example of such failed attempts for the embedded relative clause: I did it with my teacher who is called Doris. In SLI, this deficient relative clause rendering has been taken to evidence a failure in the ability to construct appropriately embedded syntactic structures [ 24 , 25 , 35 , 36 ]. Though future studies are needed to establish intra-subjects correlation between motor and linguistic deficits, our findings on the distinctions between TD and SLI in the motor domain highlight an intriguingly striking parallel with the typical linguistic syntactic deficits SLI children have been observed to exhibit. With weight knowledge available prior to movement onset, SLI children were the only group that failed to transfer the motor computation of kinematic object weight adjustment from the Move to the Reach sub-phase. That is, despite prior weight knowledge, kinematic adjustments to weight for SLI children continued to take place only after object contact, i.e. still in the Move sub-phase. Thus, no displacement of weight effects was observed for this group. Yet, weight information was not ignored: As witnessed by the overall shortening of the latencies in the known condition both in the Reach and in the Move sub-phase alike, SLI patients benefited from weight knowledge. However, while for TD children, prior weight knowledge caused the appearance of an asymmetric shift in how weight effects impacted the two sub-components of our structured displacing action, for SLI children in contrast, advanced weight knowledge affected the two subcomponents symmetrically. This is as if the structure of the SLI children displacing sub-phases were juxtaposed, rather than embedded, provoking a distributed effect of advanced weight knowledge as if the expected normal execution of a motor distant dependency was disrupted. This, we suggest, echoes the Coordinate Structure Constraint at play in language syntax.

The rather striking analogy here observed for SLI patients between specific known language difficulties with relative clauses and hitherto unnoticed fine-grained structural motor abnormalities, highlights the possibility of common syntactic mechanisms in language and motor domain with renewed vigor.

Within the framework of the mirror system, an analogous motor impairment has been reported for autistic children by Cattaneo and colleagues ([ 38 ], see also 39 ). The study investigated the ability of autistic children to understand the motor intentions of others. In their study the authors compared the electro-myographic activity of the mouth opening muscle of TD with that of high functioning autistic children. These subjects were observing and executing two action chains; 1) reaching and bringing to the mouth a piece of food, 2) reaching and putting in a container a piece of paper. Characteristically, in the bringing to the mouth action, for both observation and execution, TD children exhibited an anticipatory activity of the mouth-opening muscle that started during the reaching sub-phase until the end of the movement. In contrast, autistic children failed to exhibit a comparable anticipatory muscle activity. Mouth muscle activation was confined to the bringing phase. Although our results also report an analogous failure in SLI children to kinematically anticipate weight effects, the putative resemblance between the two types of motor execution failure may only be superficial. In Cattaneo et al.’s study the task involved the anticipation of the goal of an action and the impact of knowing this goal on motor parameters. In contrast, our task investigated how knowing the weight of an object allows participants to transfer and invert the effects of object weight from the Move to the Reach sub-phase. This transfer is independent of the goal (i.e. the displacement of the object), which in our case remains the same. Hence, Cattaneo and colleagues observed a delay of the onset of the mouth opening muscles activity in autistic population, compared to their controls. In our case, however, the qualitative shift of the way motor parameters adapt to weight knowledge from the “Move-“ to the “Reach-“ phase, which characterizes the performance of our control groups, is never seen in the population of SLI children. Most importantly, FXS patients, who suffer from language deficits observed to spare syntactic embedding and distant dependencies [ 34 ], displayed a preserved ability to adjust their motor parameters as a function of action structure requirements. Despite a profound alteration of their motor performance, as witnessed by the overall delay in their movement parameters and the relative sluggishness of their motor performance, FXS patients produced what we could call a structurally correct motor distant dependency.

To date, only few studies have empirically probed the nature of motor syntax [see, for a review, 7]. Hoen and colleagues showed that agrammatic patients trained with non-linguistic sequences could improve their performance with relative clause comprehension [ 40 ]. In the motor domain, Fazio and coworkers [ 41 ] documented the inability of agrammatic brain-damaged patients to correctly reorder frames taken from a video-clip showing a human action, while their ability to reorder physical events was preserved. Using repetitive Transcranial Magnetic Stimulation (rTMS) in a paradigm similar to the one used by Fazio et colleagues, Clerget and colleagues [ 42 ] suggested that Broca’s area played a role in understanding complex transitive actions. In an Electro-Encephalogram study [ 43 ], healthy participants presented with videos containing expectancy violations of common real-world actions (i.e. an electric iron used in an ongoing bread cutting action) displayed two event related potentials (ERP), one negative peaking around 400ms and one positive peaking around 600ms and centered over the parietal lobes. These ERPs recall respectively the N400 elicited by semantic violation and the syntactic positive shift (the P600) argued to index syntactic integration difficulties [ 44 , 45 ] Kaan and Swaab 2003; Osterhout et al. 1994). While all these studies support the existence of syntactic mechanisms at work in complex action understanding, the present study critically adds to our knowledge by indicating that the motor production system could share rather specific structural representations and processes with language as well as, possibly, some of its constraints, namely, perhaps constraints akin to the linguistic Coordinate Structure constraint.

In conclusion, supporting Jackendoff’s theoretical conjecture, we provide experimental evidence for a motor structure that is in many ways analogous to the linguistically characterized distant dependency at hand in relative clauses. Our study is also the first to make use of a task simple enough to be performed by young patients, but whose structure is sufficiently complex to probe fine motor skills. Our task uses a fixed set of material (objects properties and movement goals) and manipulates only one feature of the target action, namely prior knowledge of object weight. Moreover, this task enables a direct access to the structural properties of simple actions without the potential confounds of semantic or cultural factors. Our findings, that a developmental linguistic deficit affecting (among other) the ability to construct complex embeddings and dependencies, is mirrored by a structural deficit in building the motor analogue of a distant dependency strongly restate the principled motivation for investigating common motor and linguistic structural mechanisms, and the existence of a possible motor precursor for language syntax.

Ethics Statement

All participants were naïve as to the purpose of the study and all participants as well as their parents or guardians (for children), gave a written informed consent to participate to the study, which was approved by the local ethics committee (CPP Sud Est II), and were tested in observance of the Declaration of Helsinki.

Participants

SLI children were diagnosed by a trained multidisciplinary team of specialists working at the national reference center for learning and communications disorders of the Lyon hospitals. IQ evaluation revealed a difference of at least 20 points between IQv and IQp (mean score 91.6 and 116.5, respectively), which represents more than 1.5 standard deviations. Patients were between 9 years and 13 years and 4 months, mean age was 11 years. All patients, except one, were right handed. Four patients were diagnosed with a dysphasia affecting the phonological and syntactic aspects of their language, and three patients were diagnosed with a dysphasia affecting the lexical and syntactic aspects. All patients have been undergoing intensive speech reeducation for several years (six years and a half on average). At the time of testing, children had at least partially recovered from phonological and lexical deficits, but remained dramatically impaired at the syntactic level, expressing themselves using simple sentences only. Language production rather than comprehension was affected: For 6 out of the 7 patients syntactic comprehension as assessed with the ECOSSE test (Evaluation de la Compréhension Syntaxico-Sémantique, P. Lecocq, 1996) met the expected age-dependent level of performance. On the production side, 4 out of 7 patients exhibited a delay of, on average, 36.3 months with respect to their chronological age (for syntax and morpho-syntax; TGC-R: Test of Grammatical Closure, Deltour, 1992, 2002). In the remaining 3 patients, the developmental age of syntactic abilities was not quantifiable: Despite a chronological age of 9 years and 1 month, 9 and 13 years, no complex sentences were produced, and the present tense was the only one used.

FXS patients were recruited through the Rare Causes of Intellectual Disability National Center of the Lyon hospitals. They were between 20 and 31 years-old. All but one were right-handed. FXS was confirmed by more than 200 CGG repeats or a positive cytogenetic test and a family history of FXS. Mental age varied from 4,5 to 7,5 years as evaluated with nonverbal reasoning test (Raven’s Colored Progressive Matrices). Language comprehension, assessed with the ECOSSE test, revealed a developmental age of 5 years and 5 months. On the production side the mean length of utterance was 5,39 words and the mean age of grammatical development was 4,92 as evaluated with the TGC-R.

Typically developing children and healthy adults (all right-handed) were recruited out of patient’s relatives.

Stimuli and procedure

Two visually identical white opaque bottles (250ml containers) were used as stimuli, one weighting 50g (termed hereafter ‘light’) and one weighting 500g (termed hereafter ‘heavy’). Prior to starting the experiment, participants were asked to manually familiarize themselves with the bottle and the experimenter reinforced their perception by saying “You feel how this bottle is heavy/light, now feel this one; isn’t it much lighter/heavier?”.

Participants were required to keep their hand, held in a pinch grip position, on a fixed starting point on a table along their sagittal axis. Upon hearing a go-signal they were instructed to reach and grasp for the bottle (placed 20cm in front of the starting point) and to displace it to a pre-defined position 15cm to the right of the initial position. Once the bottle was displaced to its final position, participants replaced his/her hand back on the starting point and waited for the next go-signal. Participants were instructed to grasp the bottle on its cap to ensure a uniformly sized grasp surface. Participants performed a total of 40 trials. In the first 20 trials, relevant information about object weight (i.e., light vs. heavy) was provided prior to movement onset and participants perform a block of 10 successive trials with the heavy object, and a block of 10 successive trials with the light object, or vice versa. In the remaining 20 trials, object weight was unknown and heavy and light trials were proposed in a pseudo random order. To ensure that participants were oblivious of object weight, experimenter’s manipulation of the bottles was concealed.

Movement recordings and data processing (analysis)

Movement kinematics were recorded via an Optotrak 3020 system (Northern Digital Inc). One active infrared marker (sampling rate set at 300Hz) was placed on the wrist, two respectively on the index and thumb fingers, and two on the bottles. A second-order Butterworth dual pass filter (cutoff frequency, 10Hz) was used for raw data processing. Individual movements were then visualized and analyzed using Optodisp software (Optodisp copyright UCBL-CNRS, Marc Thevenet et Yves Paulignan, 2001). For each Reach sub-phase latency and amplitude of the first and second acceleration peaks, velocity peaks, deceleration peaks and grip aperture were measured. For the Move sub-phase latency and amplitude of the highest acceleration peaks, velocity peaks, and deceleration peaks were measured ( Figure S1 ). The whole action time, as defined as the time elapsed between the beginning of the movement when participants left the starting point and movement end when participants had displaced the bottle in its final position.

To reduce noise, the first two movements of each of the four experimental conditions were discarded from subsequent analysis. For each participant, mean values for the different kinematic parameter were computed separately for each condition. Data normality and homoscedasticity were controlled with Shapiro-Wilk and Levene tests, respectively. Mean values for each participant were entered into a repeated measures ANOVA with Weight (light, heavy) and Knowledge (known, unknown) as within-subject factors. To further test the combined effect of all measured parameters of the movement a multivariate approach was applied. Since the requirement of a parametric MANOVA, i.e., to have more observations than parameters, is not fulfilled in our case, a resampling-based non parametric MANOVA with Fisher combination of the p-values was used [ 46 , 47 ].

Supporting Information

Wrist velocity and acceleration profile for the Displace action task.

Here are represented the wrist velocity (left panel) and acceleration profile (right panel) pertaining to an individual representative movement and the collected parameters. The Reach sub-phase (green ground) is characteristically composed of two acceleration peaks followed by a velocity peak (red marks) and a deceleration peak (green mark); the ensuing Move Object phase (orange ground) is in turn characterized by an acceleration peak, a velocity peak (red marks) and a deceleration peak (green mark). Please note that more than one deceleration peak may occur for each movement sub-phase (or acceleration for the second sub-phase); in those cases, the lowest deceleration or on the contrary the highest acceleration peak was collected for subsequent analyses.

https://doi.org/10.1371/journal.pone.0072677.s001

Tables S1 & S2.

https://doi.org/10.1371/journal.pone.0072677.s002

Acknowledgments

We wish to thank all the participants and their families, L. Finos for his support with statistical analyses and A. Brun for her help during data acquisitions.

Author Contributions

Conceived and designed the experiments: ACR AC TAN YP VdP PF VD. Performed the experiments: ACR AC PF. Analyzed the data: ACR VD. Wrote the manuscript: ACR AC TAN YP VdP PF VD.

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Convenor: Dr James Baker

This seminar focuses on generative syntactic approaches to agreement and (particularly) case. We consider a range of empirical phenomena (such as structural vs. non-structural case, alignment and ergativity,) in relation to a range of theoretical approaches, surveying a broad range of primary literature on these topics from the last several decades of generative research up to the present day. The seminars will be structured around interactive discussion of the topics with a focus on critical analysis and argumentation.   

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Three open questions in experimental syntax

This article presents a review of current research in experimental syntax, with a focus on three open questions and the (methodo)logical tools that have been developed to explore them. The three questions are: (1) Are the published data underlying syntactic theories valid?, (2) How can we determine the source of acceptability judgment differences?, and (3) What do gradient judgments tell us about the architecture of the grammar? The hope is that these three questions will illustrate the fundamental connection between experimental syntax and theoretical syntax, provide concrete demonstrations of the value of the tools of experimental syntax (e.g., random sampling, factorial logic, and gradient judgments), and point to new directions for future research.

1 Introduction

The use of formal experimental methods for the collection of acceptability judgments has grown in popularity over the past 15 to 20 years, thanks in no small part to Schütze’s ( 1996 ) treatise on the empirical base of linguistics, and Cowart’s ( 1997 ) textbook on acceptability judgment collection methods. Today the use of formal methods are so widespread that it is not uncommon to describe studies using such methods as part of a “field of experimental syntax”, following the title of Cowart’s textbook. In this article I would like to review three open questions in experimental syntax, with a particular focus on the logical and methodological tools that have proven useful in exploring these questions. Although this may seem like straightforward review material, there is one aspect of experimental syntax that makes selecting open questions a bit tricky: experimental syntax really isn’t a distinct field. Experimental syntax is a set of methods for collecting data in service of theoretical syntax . In other words, to the extent that there is a field of experimental syntax, it simply inherits its questions directly from the field theoretical syntax. Complicating the picture even further, the field of theoretical syntax already has a set of experimental methods: the traditional, informal judgment collection methods that have been deployed in nearly every theoretical syntax investigation since (at least) the 1950s (for the logic of using judgments, see Chomsky 1965 and Newmeyer 1983 ). The informal methods of theoretical syntax and the formal methods of experimental syntax share many properties (such as the creation of tightly controlled experimental conditions, and the testing of the same behavioral response), and tend to differ as a matter of degree (such as the number of items tested, or the number of participants recruited), not category (the one categorical difference being the background knowledge of participants; see Section 2 ). So when one asks the question What are the driving questions of experimental syntax? , it seems to me that the meaning behind the question must be something closer to What are the new (or important) theoretical syntax questions that become (more) tractable when the traditional informal judgment collection methods are formalized using experimental syntax techniques? The latter is a mouthful, so the shorthand is understandable. But I believe it is important to keep the relationship between theoretical syntax and experimental syntax in mind while evaluating the role of experimental syntax in modern theoretical syntax, and its potential moving forward.

Are the published data underlying syntactic theories valid?

How can we determine the source of acceptability judgment differences?

What do gradient judgments tell us about the architecture of the grammar?

As with any review, the choices here reflect a bit of an editorial bias on my part. For example, I have chosen to focus on acceptability judgment methods over other methods (such as reaction times and EEG). This is partly for practical reasons, as there isn’t enough space to do justice to more than one method in a short review article. This is also partly scientific, as the (relatively more complex) linking hypothesis between these other data types and syntactic theories are only just beginning to be explored. I have also chosen to focus on three questions that have figured prominently in my own research. Editorial bias aside, I believe these three questions have properties that make them ideal for a review of this sort: each has important consequences for theories of syntax, each has brought several logical and methodological tools into focus that are likely to be of use as the fields of theoretical and experimental syntax move forward, and each is still currently open for debate and future research.

2 Are the published data underlying syntactic theories valid?

Given the central role that acceptability judgments play in the theoretical syntax literature, it is perhaps not surprising that the single most frequent question in the methodological literature is to what extent linguists can trust the acceptability judgments reported in the literature. This question has arisen in one form or another since the earliest days of generative grammar (e.g., Hill 1961 ; Spencer 1973 ), it has played a central role in the two books that ushered in the modern approach to experimental syntax ( Schütze 1996 ; Cowart 1997 ), and it has led to several high-profile discussions in the past decade (see Ferreira 2005 ; Wasow and Arnold 2005 ; Featherston 2007 ; Gibson and Fedorenko 2010 , 2013 for some criticisms of informal methods, and Marantz 2005 and Phillips 2009 for some rebuttals). The fundamental concern is that informal judgment collection methods may give rise to spurious results. If the results are spurious, it would follow that the syntactic theories themselves are also spurious (with domino effects for fields that build on syntactic theories, such as language acquisition and sentence processing). This is a serious concern, and perhaps fortuitously, also a concern that experimental syntax is well-positioned to address. As such, it is perhaps unsurprising that this has been a lively topic in the experimental syntax literature (see also Myers 2009 for a review of concerns about judgment collection methods, along with recommendations about how many concerns can be alleviated with relatively small experiments).

When it comes to assessing experimentally collected data, we must first confront a fundamental fact about experimental science: we can never know whether our experiments are yielding measurements that are true reflections of the universe. To know that would require independent knowledge of the universe, thus circumventing the need for measurements in the first place. In lieu of certainty, we attempt to build confidence in our measurements. This usually revolves around two dimensions: the validity of the measurement, which is its ability to measure the property of interest, and the reliability of the measurement, which is its ability to consistently measure the property of interest. [1] To increase confidence in validity, we often look for consistency between two distinct methods intended to measure the same construct, look for consistency between our measurements and the predictions of uncontroversial theories, and look for consistency between the measurement methodology and the best practices agreed upon by the research community. To increase confidence in reliability, we often repeat measurements under unchanged conditions ( replication ). In the case of informal judgment collection, many of these markers of confidence are either covert or missing altogether. In addition, many (if not all) informally collected judgments come from professional linguists rather than linguistically-naïve participants. Professional linguists may be aware of the syntactic theories under investigation, leading to a type of cognitive bias that may impact their judgments (an issue raised in nearly every previous discussion of syntactic methods). As such, it is not surprising that some researchers have expressed skepticism in the validity (and perhaps reliability) of informal methods.

There is a straightforward method for determining whether this lack of confidence in informal methods is justified: compare the results of informal methods with formal experimental methods. The results that converge between the two methods will benefit from the increase in confidence. The results that diverge can then be further investigated to determine which method is more likely giving the valid result (i.e., by manipulating the factors that give rise to concern in each method, such as the linguistic knowledge of the participants). The tools of experimental syntax make such studies eminently possible. However, there are at least two issues that require careful consideration. The first is how to select phenomena to be tested. It is not uncommon for discussions of this topic to present a few phenomena from the literature, along with formal experiments showing results that diverge from the informally collected results (e.g., Gibson and Fedorenko 2013 ). The concern with these sorts of studies is that the phenomena weren’t selected randomly, or in statistical terms, were selected with bias . A biased sample of phenomena cannot be used to statistically generalize to a larger population of phenomena; instead, we either need to test the entire population of phenomena (exhaustive testing), which would reveal the exact number of divergent results, or randomly sample from the population, which would allow us to statistically estimate the number of divergent results within a margin of error.

The second issue is a practical one: at some point, a decision must be made as to whether the informal method is valid and reliable, or not. There are real costs to advocating a complete switch to formal methods (in terms of time and money). If informal methods are invalid and unreliable, the cost will be justified and the field will need to adjust accordingly. However, if informal methods are valid and reliable, then formal experiments can be reserved for the questions where they provide unique information (such as the questions in Sections 3 and 4 ). In null hypothesis significance testing (of the Neyman-Pearson variety), this question is often framed in terms of Type I errors , also known as false positives or false rejections of the null hypothesis , which are the errors that arise when a theorist acts as if there is a significant difference between one or more conditions when constructing a theory, but in fact no such difference is true of the world. It is common to talk about maximum Type I error rates, which is the rate of Type I errors (false positives) that would occur if a statistical test were repeated an infinite number of times. The same question arises in syntax: what is the maximum number of false positive results that we are willing to tolerate from informal methods? It is tempting to answer zero, but every experimental result carries a risk of error. For example, the conventionally agreed upon maximum Type I error rate in experimental psychology is 5% (which arises because the threshold for behaving as if a result issignificant, called the alpha-criterion by Neyman-Pearson, has been conventionally set at p < 0.05). The question facing the field of syntax is whether we also want to adopt the same or a different criterion.

Crucially, once that criterion is decided, we can easily evaluate the convergence/divergence between informal and formal methods to determine if the extra cost of formal methods should be imposed on the field or not. Under the assumption that convergent results are very likely to be true positives (an assumption that can certainly be questioned), it follows that the divergence rate becomes a maximum Type I error rate for informal methods (the error rate would be zero if follow-up studies show that the informal method was always correct, and the error rate becomes the divergence rate if follow-up studies show that the formal method was always correct). There are currently two studies that take both of these issues (phenomena selection and divergence rate) into consideration. First, Sprouse and Almeida (2013 ) exhaustively tested every English phenomenon in a recent syntax textbook ( Adger 2003 ) that could be tested in a simple acceptability judgment survey. Using the best practices of experimental syntax (multiple items, pseudorandomized surveys, large samples of naïve participants), and several statistical methods, they found a convergence rate of 98%, and therefore a divergence rate of 2%. Second, Sprouse et al. 2013 randomly sampled English phenomenon from 10 years of syntax articles published in Linguistic Inquiry . Again, using the best practices of experimental syntax, and based on the number of phenomena randomly sampled, they found a convergence estimate of 95% ± 5, and therefore a divergence estimate of 5% ± 5 ( Figure 1 ).

Convergent and divergent phenomena in Linguistic Inquiry 2001–2010 and Adger (2003 )

Both of these rates are at or below the criterion set by experimental psychology, so depending on what the field decides should be the conventional criterion in syntax, it may be the case that informal methods will ultimately be considered a valid and reliable method for phenomena that do not require the extra information provided by formal methods. However, a note is in order about the scope of these results. In the case of the Adger textbook study, the selection method was exhaustive, therefore the results are a great estimate of the convergence for the data in Adger (2003 ), but we don’t know how well they extend to other populations of phenomena. For the LI study, the selection method was random, which allows for generalization to the full population (10 years of LI articles), but we again restricted that selection process to English phenomena that could be tested in a standard acceptability judgment survey ( Figure 2 ).

The distribution of types of data in Linguistic Inquiry 2001–2010

This means that in both cases, there is much work to be done examining divergence rates for other types of phenomena, and for languages other than English. Experimental syntax is well-positioned to provide these future studies, but it will require participation from a diverse array of linguists. It may be the case that other data types and other languages will reveal substantially different divergence rates, in which case the validity and reliability of informal methods will be a more nuanced issue.

3 How can we determine the source of acceptability judgment differences?

The second big question in experimental syntax arises because of the fundamental problem of cognitive science: we cannot directly observe cognitive operations. To get around this, we use data types that we can observe to make inferences about the underlying cognitive operations. In the syntax literature, acceptability judgments are used to identify differences in acceptability between two (or more) minimally differing sentences types (in experimental syntax we can call each sentence type a condition of the experiment). When a difference in acceptability is detected between conditions, syntacticians attempt to explain that difference as a consequence of the functioning of the grammar (e.g., as a violation of a syntactic constraint). However, acceptability judgments are a behavioral response that occurs as a by-product of sentence processing. This means that, in principle, every cognitive system that contributes to sentence processing contributes to acceptability judgments. This in turn means that any difference in acceptability that is detected between conditions could be explained as a consequence of these other cognitive systems. Given the sheer number of cognitive systems at work during sentence processing (syntax, semantics, pragmatics, ambiguity resolution, working memory, etc.), it is often nearly impossible to create conditions that manipulate syntactic properties without also manipulating properties of these other cognitive systems. From the point of view of syntactic theory these differences from other systems would be considered confounds, but from the point of view isolating the source of acceptability judgment effects, these differences in other cognitive systems are potential non-syntactic explanations for the observed effects. The question then is whether we can use experimental syntax to help tease apart explanations that require syntactic constraints ( syntactic explanations ) from explanations that reduce the effect to consequences of other cognitive systems ( reductionist explanations ).

In principle, the method for assessing the likelihood of a reductionist explanation is straightforward: manipulate the properties of the critical non-syntactic system(s) while holding the syntactic properties constant, and look for changes in the observable acceptability difference. However, in practice, it is often difficult to disentangle reductionist explanations from syntactic explanations. We can use island effects as a concrete example. Island effects, as a phenomenon, can be defined as the decrease in acceptability that occurs when a long-distance dependency originates within certain structures, which we can call island structures (in the examples below, the island structure is indicated with square brackets, the head of the dependency by italics, and the tail of the dependency by an underscore):

What do you wonder [whether John bought __]?

What did you make [the claim that John bought __]?

What do you think [the rumor about __] prompted the congressional hearing?

What do you worry [if John forgets __ at the office]?

In the syntax literature, island effects tend to be analyzed as the consequence of one or more syntactic constraints, often descriptively called island constraints, that make this specific configuration ungrammatical (e.g., Ross 1967 ; Chomsky 1986 ). However, Kluender and Kutas (1993 ) observe that sentences containing island effects always contain two properties that could potentially decrease acceptability due to processing difficulty without any contribution from a syntactic constraint: (i) the presence of a long distance dependency, and (ii) the presence of complex structure (i.e., the island structure). These two properties are always part of the structural description of an island effect, so both syntactic and reductionist explanations can explain the acceptability decrease in (1).

In principle, experimental syntax provides a number of methods for attempting to tease apart syntactic and reductionist explanations. One possibility is to look for secondary differences in the judgments to different types of unacceptable sentences, such as the fact that some unacceptable sentences appear to increase in acceptability after repeated exposure. This effect is often called satiation in the syntactic literature, and has been studied extensively for island effects (as well as other phenomena). In principle, the idea is that if two phenomena differ in the source of the effect (e.g., syntax vs reductionism), their satiation properties (either the presence of satiation, or the rate of satiation) may also differ. In practice, however, satiation studies have yielded conflicting results (e.g., Snyder 2000 ; Hiramatsu 2000 ; Sprouse 2009 ; Francom 2009 ). Another possibility is to use the real time behavior of the parser to test predictions of reductionist theories. For example, Phillips (2006) argues that some reductionist theories might predict that the parser cannot actively complete dependencies when the gap is inside an island. He then shows reaction time evidence that the parser actively attempts to complete dependencies when the gap is inside certain subject islands, despite the fact that those sentences are judged to be unacceptable in offline studies. This suggests that the source of the unacceptability cannot be due to reductionist theories that predict that dependency completion is impossible. In a similar vein, Yoshida et al. (2013 ) argue that some reductionist theories might predict that all dependencies that involve working memory costs should respect island constraints. They then show that the parser does not respect island constraints for “backward” binding dependencies in which a pronoun appears at the beginning of a sentence and the antecedent appears inside of an island later in the sentence (but crucially the parser does respect island effects for wh-dependencies). This selectivity of island effects runs counter to the prediction of some reductionist theories.

Because satiation studies are currently inconclusive, and reaction time studies depend upon questions about how the parser works in real time, in the rest of this subsection I would like to review two additional tools that can be used to help tease apart syntactic and reductionist theories in more traditional offline acceptability judgment experiments. The first is the concept of (fully-crossed) factorial designs. In experimental design, a factor is a property that can be manipulated, such as the length of a dependency, or the presence or absence of an island structure. Each value that a factor can take is called a level . By choosing factors and levels that instantiate the components of a reductionist explanation, it is possible to isolate the contributions of each component. Again using island effects as a concrete example, we can quantify the effect of a long distance dependency with a factor called length , and two levels, short and long , as in (2a) and (2b), such that the subtraction [(2a)–(2b)] yields a measure of the effect of dependency length. We can quantify the effect of island structures with a factor called structure , and two levels, non-island and island , as in (2a) and (2c), such that the subtraction [(2a)–(2c)] yields a measure of the effect of island structures.

To make this a fully crossed design, we add (2d) which is a sentence that combines both the long level of length , and the island level of structure , and is also the critical island-violating sentence. Because we’ve isolated the effects of length and structure in the first three sentences, we can make a prediction for the fourth: if the acceptability of island effects is completely explainable by the effects of long distance dependencies and island structures, then the acceptability of (2d) will be the sum of those two effects. In mathematical terms: [(2a)–(2d)] = [(2a)–(2b)] + [(2a)–(2c)]. In graphical terms, if the island effect is the sum of those two effects, a graph of the four conditions will yield two parallel lines as in the left panel of Figure 3 . On the other hand, if there is more to island effects than just the sum of the length effect and the structure effect, then the acceptability of (2d) will be lower than predicted by the other three conditions. This will yield non-parallel lines in a graph as in the right panel of Figure 3 . In mathematical terms: [(2a)–(2d)] > [(2a)–(2b)] + [(2a)–(2c)]. This is also called a superadditive effect, or superadditive interaction, in experimental studies.

Examples of linear additivity (left) and superadditivity (right)

Factorial designs like the one above provide a first test for reductionist theories: if the critical effect can be captured by the sum of reductionist components, then the reductionist theory is likely true. However, if a superadditive effect is observed, the results are ambiguous. It could either be that there is a syntactic constraint causing the superadditive effect, or it could be that the two reductionist components interact in a complex way to yield a superadditve effect. In other words, superadditivity is a necessary condition for a syntactic constraint, but not a sufficient one. Once superadditivity is identified, it becomes the effect in need of an explanation: syntactic theories explain it with a syntactic constraint, while reductionist theories likely explain it with a complex interaction of non-syntactic effects. To resolve this ambiguity, we must use the second tool that experimental syntax makes available: correlating diverse data types. Although syntactic theories primarily use acceptability judgments as evidence, reductionist theories are predicated upon non-syntactic cognitive systems, which are likely to be amenable to investigation using other types of behavioral responses. If one can identify the cognitive system that is thought to give rise to the acceptability effect in question, and then identify a behavioral response that is also affected by that specific cognitive system, it may be possible to use the formal results of experimental syntax studies to look for statistical correlations between the superadditive effect observed in acceptability judgments and the other behavioral response in order to assess the likelihood of the reductionist theory.

As a concrete example, Sprouse et al. (2012 ) found that four island types in English all show superadditive patterns using a factorial design as in Figure 4 .

Island effects in English using the factorial design ( Sprouse et al. 2012 ). The p -values are reported for the interaction term in a two-way linear mixed-effects model

This suggests either a syntactic explanation, or a complex reductionist explanation. Kluender and Kutas (1993) provide one such complex reductionist explanation. They suggest that both long distance dependencies and island structures might draw on the same set of working memory resources in order to be successfully parsed. If true, this would predict that attempting to parse both, as in island effects, might result in a larger-than-expected effect (a superadditive interaction). Sprouse et al. argue that one plausible prediction of this theory is that individual differences in working memory capacity will lead to differences in the size of the superadditive effect that individuals report using acceptability judgments. To test this, they asked a large number of participants to complete both a series of working memory tests and an acceptability judgment experiment, and looked for correlations between the results of the two experiments.

Although Sprouse et al. (2012) observe no significant correlations, casting some doubt on the complex reductionist explanation they tested, the more interesting result is the proof of concept that two of the tools made available by experimental syntax, factorial design and data correlation, can be used to explore the source of acceptability judgment effects. These tools have only just begun to be explored in the experimental syntax literature, but they promise to be useful for any number of phenomena, such as other dependency constraints, that are potentially amenable to reductionist theories (see also Sprouse etal. 2011 for island effects in Japanese, Hofmeister, Culicover, and Winkler in press for freezing effects in English, and Sprouse et al . in press for island effects with relative-clause formation in English and Italian).

4 What do gradient judgments tell us about the architecture of the grammar?

The third question concerns a fact about acceptability judgments that is simultaneously the most obvious to observe and perhaps the most difficult to explore: acceptability judgments appear to be continuous. Figure 5 plots the acceptability of the 300 sentence types tested by Sprouse et al. (2013 ) in order of increasing acceptability (the y-axis is mean z-score transformed ratings, the x-axis is simply ascending order of acceptability).

Acceptability for 300 sentence types randomly sampled from Linguistic Inquiry 2001–2010 plotted in ascending order ( Sprouse et al. 2013 ). Red dots indicate sentence types that were given a diacritic (*,?, or a combination) in LI. Blue dots indicate sentence types that were given no diacritic

As Figure 5 demonstrates, with a large enough random sample of sentence types, the acceptability of the sentences is fairly evenly distributed across the (non-countably infinite) range of possible acceptability levels. This continuity, sometimes called gradience, appears to be a fact of acceptability judgments. This fact has long been acknowledged in the syntax literature (e.g., Chomsky 1964 ), and has even been leveraged as evidence to distinguish different types of syntactic constraints (e.g., Subjacency violations vs. Empty Category Principle violations in Chomsky 1986 ). What has changed with experimental syntax is that formal judgment experiments, especially those that use a continuous response scale (e.g., magnitude estimation), or approximate a continuous scale (e.g., z-score-transformed Likert scales), bring the gradience of acceptability judgments into sharp focus. The question, then, is what does this gradience tell us about the architecture of the grammar?

In principle syntactic architectures can be divided into two broad classes: binary-categorical theories and weighted-constraint theories. Binary-categorical theories are the most common, and likely the most familiar. In binary-categorical theories the grammar either generates a sentence or does not generate a sentence. Since the syntax only yields two values, this means that the gradience of judgments must derive from non-syntactic cognitive systems (pragmatics, real-world plausibility, parsing difficulty, etc.). In contrast, in weighted-constraint theories the syntax plays a larger role in accounting for gradient judgments. In weighted-constraint theories each constraint in the syntax is associated with a value, such that combining these values leads to a large range of possible levels of grammaticality (2 N levels, where N is the number of constraints). Weighted-constraint theories still assume that non-syntactic cognitive systems contribute to acceptability, but the relative contribution of syntax is higher. There are at least three prominent weighted-constraint theories in the experimental syntax literature: Keller’s ( 2000 ) Linear Optimality Theory (see also Sorace and Keller 2005 ), Bresnan’s ( 2007 ) Stochastic Optimality Theory, and Faetherston’s ( 2005a ) Decathlon Model (see also Featherston (2005b ) for an example of a previously undetected Superiority effect in German that is potentially due to a syntactic constraint). There are also several instances in the literature where weighted-constraints were inserted in otherwise binary-categorical theories, such as the distinction between Subjacency violations and ECP violations (e.g., Chomsky 1986 ), or the distinction between strong and weak island effects (e.g., Szabolcsi 2006 ). For space reasons I won’t review the details of specific theories here, but instead focus on the empirical facts that have been revealed by experimental syntax, and that must be addressed by both classes of theories.

The first fact is variation in effect sizes across phenomena. Syntacticians define an effect as a difference in acceptability. Experimental syntax has brought into focus the fact that different phenomena lead to different sizes of acceptability differences. This can again be illustrated with the large, random sample of phenomena tested from Linguistic Inquiry in Sprouse et al. (2013 ). Figure 6 plots the size of the acceptability effect for each of the 150 phenomena investigated.

Effect sizes in ascending order for 150 (two-condition) phenomena randomly sampled from Linguistic Inquiry 2001–2010 . Color indicates the category of effect size: red indicates “small” effect sizes, green indicates “medium” effect sizes, and blue indicates “large” effect sizes

Binary-categorical syntactic theories must account for these differences in effect size across phenomena based on non-syntactic factors impacting the acceptability of each of the sentences. The simplest theory would posit a single effect size for ungrammaticality (e.g., 0.5 z-score units), and then explain the variation through the linear addition of other factors, such as difficulty parsing, or even the ease of parsing in the case of effects that are smaller than the ungrammaticality effect. A more complex theory could postulate interactions (super- or sub-additive effects) among the non-syntactic factors. In either case, the explanatory burden is to find a set of factors that can capture the effect size variability within a binary-categorical grammar, and that will make predictions about the acceptability of future sentence types. Weighted-constraint theories can in principle capture the different effect sizes by postulating a set of constraints and values that give rise to the different effect sizes. In this case, the explanatory burden is to provide an account that goes deeper than just capturing the acceptability effects. This can be accomplished by tying the weights to an independent property (e.g., probability of occurrence), or by associating this property with units that are smaller than the sentence, which can then make predictions for future sentence types that can be empirically tested. For both grammatical architectures, once the predictions are worked out, experimental syntax methods can be used to assess the success of the predictions.

The second fact is variation in effect sizes between phenomena that appear to involve the same, or at least closely related, constraints. For example, if one takes the superadditive component of the factorial design for island effects as a measure of effect size (see Section 3 ), then we can compare the size of island effects across island types, across dependency types, and even across languages. Any variation in effect sizes must be explained. As a concrete example we can compare the sizes of island effects for whether, complex NP, subject, and adjunct islands in English with bare wh-word dependencies, and complex which -phrase dependencies (see Sprouse et al. in press ).

A comparison of the size of whether and complex NP island effects (in terms of the superadditive effect size) for bare wh-words and complex which -phrases

The results suggest that both whether and complex NP island effects are substantially smaller with complex which -phrases ( Figure 7 ), corroborating claims in the literature that complex which -phrases tend to ameliorate certain island effects. For binary-categorical theories, this fact must be explained with non-syntactic factors that happen to differ across islands, dependencies, or languages. For weighted-constraint theories, this fact can be explained either as two distinct constraints with distinct weights (one for each dependency type), or different weights for the same constraint in the two dependency environments.

The field is still in the first stages of collecting facts about gradience, with very few definitive analyses. Progress will require both a concerted effort to collect facts across constructions, constraints, and languages, and a strong push to fully elaborate both classes of theories. Experimental syntax provides tools for at least two stages of this exploration: quantifying the gradience facts, and exploring the predictions of novel theories. However, the theorizing will require good old fashioned logical (and creative) thinking.

5 Conclusion

Experimental syntax provides a set of formal data collection methods to further explore the central questions of theoretical syntax. Current research in experimental syntax is focused on exploring questions that would not otherwise be answerable with traditional informal data collection methods, such as investigating the validity of traditional methods themselves, investigating the source of acceptability judgment effects, and investigating the source of gradient acceptability judgment effect sizes. Although there have been several tantalizing initial results in these explorations, we have only begun to scratch the surface of the potential of experimental syntax to shed light on these questions. A concerted effort to apply experimental syntax methods to a larger selection of constructions and languages will likely lead to a rapid expansion in the number of mysteries in need of explanation, and presumably, new avenues for exploring the architecture of the grammar.

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The following links will take you to online encyclopedias and reference manuals that you can search to help you get started on your research. Here you can find general background information, definitions, and history on many linguistic terms and concepts. 

• Dictionary of Linguistics and Phonetics David Crystal's A Dictionary of Linguistics and Phonetics has long been the standard single-volume reference for its field. Now available in its sixth edition, it has been revised and updated to reflect the latest terms in the field.
• The Cambridge Encyclopedia of the Language Sciences The volume is aimed at readers who have an interest in some aspect of language science but wish to learn more about the broad range of ideas, findings, practices, and prospects that constitute this rapidly expanding field, a field arguably at the center of current research on the human mind and human society.

Print Encyclopedias and Reference

The library also has a number of  print encyclopedias  that can be found in the  Reference section on the  second floor  of the library . Reference books cannot be checked out of the library but there are scanners available on the second floor that can be used to scan information from these texts into a PDF which you can email to yourself. More background and reference information on grammar, syntax, and related topics can be found under the Featured Books tab.

Good Starting Databases for Grammar and Syntax

Th e following databases are good places to go to start researching your topic. Each database has a slightly different focu s, so you might need to try out a couple of  databases before finding one that returns the sort of results you are looking for. 

Good Starting Journals for Grammar and Syntax

The following are links to specific academic journals which are published and peer-reviewed by experts in the field. If you want to narrow your search  to a specific topic or issue, finding a journal that publishes in that area can help. 

• Journal of Phonetics The Journal of Phonetics publishes papers of an experimental or theoretical nature that deal with phonetic aspects of language and linguistic communication processes.
• Morphology Morphology publishes articles on morphology proper, as well as articles on the interaction of morphology with phonology, syntax, and semantics, the acquisition and processing of morphological information, the nature of the mental lexicon, and morphological variation and change. Its main focus is on formal models of morphological knowledge, morphological typology (the range and limits of variation in natural languages), the position of morphology in the architecture of the human language faculty, and the evolution and change of language.
• Style Style addresses questions of style, stylistics, and poetics including research and theory in discourse analysis, literary and nonliterary genres, narrative, figuration, metrics, rhetorical analysis, and the pedagogy of style. Contributions may draw from such fields as literary criticism, critical theory, computational linguistics, cognitive linguistics, philosophy of language, and rhetoric and writing studies.
• Syntax Syntax publishes a wide range of articles on the syntax of natural languages and closely related fields. The journal promotes work on formal syntactic theory and theoretically-oriented descriptive work on particular languages and comparative grammar. Syntax also publishes research on the interfaces between syntax and related fields such as semantics, morphology, and phonology, as well as theoretical and experimental studies in sentence processing, language acquisition, and other areas of psycholinguistics that bear on syntactic theories.

Search the entire library catalog  here .

Materials on Linguistics topics are found under the "P" category on the  3rd floor  of the Chester Fritz Library.  

Currently, the featured books section highlights some of the library's best h andbooks & companions for grammar and syntax, which typically offer the reader an opportunity to survey and learn about a broad field of scholarship in a comprehensive way.    They give a snap shop of the discipline covered at the time the book is published.    Unlike a retrospective collection of articles, these guides are written or edited as a planned and intentional effort, with chapters and sections interrelating and complimenting one another and thereby tend to be more readable and integrated research works.

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• Last Updated: May 6, 2024 8:29 AM
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Integrating topics and syntax

Research output : Chapter in Book/Report/Conference proceeding › Conference contribution

Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative model that uses both kinds of dependencies, and can be used to simultaneously find syntactic classes and semantic topics despite having no representation of syntax or semantics beyond statistical dependency. This model is competitive on tasks like part-of-speech tagging and document classification with models that exclusively use short- And long-range dependencies respectively.

Publication series

All science journal classification (asjc) codes.

• Computer Networks and Communications
• Information Systems
• Signal Processing

Other files and links

• Link to publication in Scopus
• Link to the citations in Scopus

Fingerprint

• Syntactics Engineering & Materials Science 100%
• Semantics Engineering & Materials Science 99%

T1 - Integrating topics and syntax

AU - Griffiths, Thomas L.

AU - Steyvers, Mark

AU - Blei, David M.

AU - Tenenbaum, Joshua B.

N2 - Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative model that uses both kinds of dependencies, and can be used to simultaneously find syntactic classes and semantic topics despite having no representation of syntax or semantics beyond statistical dependency. This model is competitive on tasks like part-of-speech tagging and document classification with models that exclusively use short- And long-range dependencies respectively.

AB - Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative model that uses both kinds of dependencies, and can be used to simultaneously find syntactic classes and semantic topics despite having no representation of syntax or semantics beyond statistical dependency. This model is competitive on tasks like part-of-speech tagging and document classification with models that exclusively use short- And long-range dependencies respectively.

UR - http://www.scopus.com/inward/record.url?scp=84898936438&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84898936438&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84898936438

SN - 0262195348

SN - 9780262195348

T3 - Advances in Neural Information Processing Systems

BT - Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004

PB - Neural information processing systems foundation

T2 - 18th Annual Conference on Neural Information Processing Systems, NIPS 2004

Y2 - 13 December 2004 through 16 December 2004

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211 Research Topics in Linguistics To Get Top Grades

Many people find it hard to decide on their linguistics research topics because of the assumed complexities involved. They struggle to choose easy research paper topics for English language too because they think it could be too simple for a university or college level certificate.

All that you need to learn about Linguistics and English is sprawled across syntax, phonetics, morphology, phonology, semantics, grammar, vocabulary, and a few others. To easily create a top-notch essay or conduct a research study, you can consider this list of research topics in English language below for your university or college use. Note that you can fine-tune these to suit your interests.

Linguistics Research Paper Topics

If you want to study how language is applied and its importance in the world, you can consider these Linguistics topics for your research paper. They are:

• An analysis of romantic ideas and their expression amongst French people
• An overview of the hate language in the course against religion
• Identify the determinants of hate language and the means of propagation
• Evaluate a literature and examine how Linguistics is applied to the understanding of minor languages
• Consider the impact of social media in the development of slangs
• An overview of political slang and its use amongst New York teenagers
• Examine the relevance of Linguistics in a digitalized world
• Analyze foul language and how it’s used to oppress minors
• Identify the role of language in the national identity of a socially dynamic society
• Attempt an explanation to how the language barrier could affect the social life of an individual in a new society
• Discuss the means through which language can enrich cultural identities
• Examine the concept of bilingualism and how it applies in the real world
• Analyze the possible strategies for teaching a foreign language
• Discuss the priority of teachers in the teaching of grammar to non-native speakers
• Choose a school of your choice and observe the slang used by its students: analyze how it affects their social lives
• Attempt a critical overview of racist languages
• What does endangered language means and how does it apply in the real world?
• A critical overview of your second language and why it is a second language
• What are the motivators of speech and why are they relevant?
• Analyze the difference between the different types of communications and their significance to specially-abled persons
• Give a critical overview of five literature on sign language
• Evaluate the distinction between the means of language comprehension between an adult and a teenager
• Consider a native American group and evaluate how cultural diversity has influenced their language
• Analyze the complexities involved in code-switching and code-mixing
• Give a critical overview of the importance of language to a teenager
• Attempt a forensic overview of language accessibility and what it means
• What do you believe are the means of communications and what are their uniqueness?
• Attempt a study of Islamic poetry and its role in language development
• Attempt a study on the role of Literature in language development
• Evaluate the Influence of metaphors and other literary devices in the depth of each sentence
• Identify the role of literary devices in the development of proverbs in any African country
• Cognitive Linguistics: analyze two pieces of Literature that offers a critical view of perception
• Identify and analyze the complexities in unspoken words
• Expression is another kind of language: discuss
• Identify the significance of symbols in the evolution of language
• Discuss how learning more than a single language promote cross-cultural developments
• Analyze how the loss of a mother tongue affect the language Efficiency of a community
• Critically examine how sign language works
• Using literature from the medieval era, attempt a study of the evolution of language
• Identify how wars have led to the reduction in the popularity of a language of your choice across any country of the world
• Critically examine five Literature on why accent changes based on environment
• What are the forces that compel the comprehension of language in a child
• Identify and explain the difference between the listening and speaking skills and their significance in the understanding of language
• Give a critical overview of how natural language is processed
• Examine the influence of language on culture and vice versa
• It is possible to understand a language even without living in that society: discuss
• Identify the arguments regarding speech defects
• Discuss how the familiarity of language informs the creation of slangs
• Explain the significance of religious phrases and sacred languages
• Explore the roots and evolution of incantations in Africa

Sociolinguistic Research Topics

You may as well need interesting Linguistics topics based on sociolinguistic purposes for your research. Sociolinguistics is the study and recording of natural speech. It’s primarily the casual status of most informal conversations. You can consider the following Sociolinguistic research topics for your research:

• What makes language exceptional to a particular person?
• How does language form a unique means of expression to writers?
• Examine the kind of speech used in health and emergencies
• Analyze the language theory explored by family members during dinner
• Evaluate the possible variation of language based on class
• Evaluate the language of racism, social tension, and sexism
• Discuss how Language promotes social and cultural familiarities
• Give an overview of identity and language
• Examine why some language speakers enjoy listening to foreigners who speak their native language
• Give a forensic analysis of his the language of entertainment is different to the language in professional settings
• Give an understanding of how Language changes
• Examine the Sociolinguistics of the Caribbeans
• Consider an overview of metaphor in France
• Explain why the direct translation of written words is incomprehensible in Linguistics
• Discuss the use of language in marginalizing a community
• Analyze the history of Arabic and the culture that enhanced it
• Discuss the growth of French and the influences of other languages
• Examine how the English language developed and its interdependence on other languages
• Give an overview of cultural diversity and Linguistics in teaching
• Challenge the attachment of speech defect with disability of language listening and speaking abilities
• Explore the uniqueness of language between siblings
• Explore the means of making requests between a teenager and his parents
• Observe and comment on how students relate with their teachers through language
• Observe and comment on the communication of strategy of parents and teachers
• Examine the connection of understanding first language with academic excellence

Language Research Topics

Numerous languages exist in different societies. This is why you may seek to understand the motivations behind language through these Linguistics project ideas. You can consider the following interesting Linguistics topics and their application to language:

• What does language shift mean?
• Discuss the stages of English language development?
• Examine the position of ambiguity in a romantic Language of your choice
• Why are some languages called romantic languages?
• Observe the strategies of persuasion through Language
• Discuss the connection between symbols and words
• Identify the language of political speeches
• Discuss the effectiveness of language in an indigenous cultural revolution
• Trace the motivators for spoken language
• What does language acquisition mean to you?
• Examine three pieces of literature on language translation and its role in multilingual accessibility
• Identify the science involved in language reception
• Interrogate with the context of language disorders
• Examine how psychotherapy applies to victims of language disorders
• Study the growth of Hindi despite colonialism
• Critically appraise the term, language erasure
• Examine how colonialism and war is responsible for the loss of language
• Give an overview of the difference between sounds and letters and how they apply to the German language
• Explain why the placement of verb and preposition is different in German and English languages
• Choose two languages of your choice and examine their historical relationship
• Discuss the strategies employed by people while learning new languages
• Discuss the role of all the figures of speech in the advancement of language
• Analyze the complexities of autism and its victims
• Offer a linguist approach to language uniqueness between a Down Syndrome child and an autist
• Express dance as a language
• Express music as a language
• Express language as a form of language
• Evaluate the role of cultural diversity in the decline of languages in South Africa
• Discuss the development of the Greek language
• Critically review two literary texts, one from the medieval era and another published a decade ago, and examine the language shifts

Linguistics Essay Topics

You may also need Linguistics research topics for your Linguistics essays. As a linguist in the making, these can help you consider controversies in Linguistics as a discipline and address them through your study. You can consider:

• The connection of sociolinguistics in comprehending interests in multilingualism
• Write on your belief of how language encourages sexism
• What do you understand about the differences between British and American English?
• Discuss how slangs grew and how they started
• Consider how age leads to loss of language
• Review how language is used in formal and informal conversation
• Discuss what you understand by polite language
• Discuss what you know by hate language
• Evaluate how language has remained flexible throughout history
• Mimicking a teacher is a form of exercising hate Language: discuss
• Body Language and verbal speech are different things: discuss
• Language can be exploitative: discuss
• Do you think language is responsible for inciting aggression against the state?
• Can you justify the structural representation of any symbol of your choice?
• Religious symbols are not ordinary Language: what are your perspective on day-to-day languages and sacred ones?
• Consider the usage of language by an English man and someone of another culture
• Discuss the essence of code-mixing and code-switching
• Attempt a psychological assessment on the role of language in academic development
• How does language pose a challenge to studying?
• Choose a multicultural society of your choice and explain the problem they face
• What forms does Language use in expression?
• Identify the reasons behind unspoken words and actions
• Why do universal languages exist as a means of easy communication?
• Examine the role of the English language in the world
• Examine the role of Arabic in the world
• Examine the role of romantic languages in the world
• Evaluate the significance of each teaching Resources in a language classroom
• Consider an assessment of language analysis
• Why do people comprehend beyond what is written or expressed?
• What is the impact of hate speech on a woman?
• Do you believe that grammatical errors are how everyone’s comprehension of language is determined?
• Observe the Influence of technology in language learning and development
• Which parts of the body are responsible for understanding new languages
• How has language informed development?
• Would you say language has improved human relations or worsened it considering it as a tool for violence?
• Would you say language in a black populous state is different from its social culture in white populous states?
• Give an overview of the English language in Nigeria
• Give an overview of the English language in Uganda
• Give an overview of the English language in India
• Give an overview of Russian in Europe
• Give a conceptual analysis on stress and how it works
• Consider the means of vocabulary development and its role in cultural relationships
• Examine the effects of Linguistics in language
• Present your understanding of sign language
• What do you understand about descriptive language and prescriptive Language?

List of Research Topics in English Language

You may need English research topics for your next research. These are topics that are socially crafted for you as a student of language in any institution. You can consider the following for in-depth analysis:

• Examine the travail of women in any feminist text of your choice
• Examine the movement of feminist literature in the Industrial period
• Give an overview of five Gothic literature and what you understand from them
• Examine rock music and how it emerged as a genre
• Evaluate the cultural association with Nina Simone’s music
• What is the relevance of Shakespeare in English literature?
• How has literature promoted the English language?
• Identify the effect of spelling errors in the academic performance of students in an institution of your choice
• Critically survey a university and give rationalize the literary texts offered as Significant
• Examine the use of feminist literature in advancing the course against patriarchy
• Give an overview of the themes in William Shakespeare’s “Julius Caesar”
• Express the significance of Ernest Hemingway’s diction in contemporary literature
• Examine the predominant devices in the works of William Shakespeare
• Explain the predominant devices in the works of Christopher Marlowe
• Charles Dickens and his works: express the dominating themes in his Literature
• Why is Literature described as the mirror of society?
• Examine the issues of feminism in Sefi Atta’s “Everything Good Will Come” and Bernadine Evaristos’s “Girl, Woman, Other”
• Give an overview of the stylistics employed in the writing of “Girl, Woman, Other” by Bernadine Evaristo
• Describe the language of advertisement in social media and newspapers
• Describe what poetic Language means
• Examine the use of code-switching and code-mixing on Mexican Americans
• Examine the use of code-switching and code-mixing in Indian Americans
• Discuss the influence of George Orwell’s “Animal Farm” on satirical literature
• Examine the Linguistics features of “Native Son” by Richard Wright
• What is the role of indigenous literature in promoting cultural identities
• How has literature informed cultural consciousness?
• Analyze five literature on semantics and their Influence on the study
• Assess the role of grammar in day to day communications
• Observe the role of multidisciplinary approaches in understanding the English language
• What does stylistics mean while analyzing medieval literary texts?
• Analyze the views of philosophers on language, society, and culture

English Research Paper Topics for College Students

For your college work, you may need to undergo a study of any phenomenon in the world. Note that they could be Linguistics essay topics or mainly a research study of an idea of your choice. Thus, you can choose your research ideas from any of the following:

• The concept of fairness in a democratic Government
• The capacity of a leader isn’t in his or her academic degrees
• The concept of discrimination in education
• The theory of discrimination in Islamic states
• The idea of school policing
• A study on grade inflation and its consequences
• A study of taxation and Its importance to the economy from a citizen’s perspectives
• A study on how eloquence lead to discrimination amongst high school students
• A study of the influence of the music industry in teens
• An Evaluation of pornography and its impacts on College students
• A descriptive study of how the FBI works according to Hollywood
• A critical consideration of the cons and pros of vaccination
• The health effect of sleep disorders
• An overview of three literary texts across three genres of Literature and how they connect to you
• A critical overview of “King Oedipus”: the role of the supernatural in day to day life
• Examine the novel “12 Years a Slave” as a reflection of servitude and brutality exerted by white slave owners
• Rationalize the emergence of racist Literature with concrete examples
• A study of the limits of literature in accessing rural readers
• Analyze the perspectives of modern authors on the Influence of medieval Literature on their craft
• What do you understand by the mortality of a literary text?
• A study of controversial Literature and its role in shaping the discussion
• A critical overview of three literary texts that dealt with domestic abuse and their role in changing the narratives about domestic violence
• Choose three contemporary poets and analyze the themes of their works
• Do you believe that contemporary American literature is the repetition of unnecessary themes already treated in the past?
• A study of the evolution of Literature and its styles
• The use of sexual innuendos in literature
• The use of sexist languages in literature and its effect on the public
• The disaster associated with media reports of fake news
• Conduct a study on how language is used as a tool for manipulation
• Attempt a criticism of a controversial Literary text and why it shouldn’t be studied or sold in the first place

Finding Linguistics Hard To Write About?

With these topics, you can commence your research with ease. However, if you need professional writing help for any part of the research, you can scout here online for the best research paper writing service.

There are several expert writers on ENL hosted on our website that you can consider for a fast response on your research study at a cheap price.

As students, you may be unable to cover every part of your research on your own. This inability is the reason you should consider expert writers for custom research topics in Linguistics approved by your professor for high grades.

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Sat / act prep online guides and tips, 113 great research paper topics.

General Education

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

• Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
• Analyze the impact a famous artist had on the world.
• How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
• How has the music of slaves brought over from Africa shaped modern American music?
• How has rap music evolved in the past decade?
• How has the portrayal of minorities in the media changed?

Current Events

• What have been the impacts of China's one child policy?
• How have the goals of feminists changed over the decades?
• How has the Trump presidency changed international relations?
• Analyze the history of the relationship between the United States and North Korea.
• What factors contributed to the current decline in the rate of unemployment?
• What have been the impacts of states which have increased their minimum wage?
• How do US immigration laws compare to immigration laws of other countries?
• How have the US's immigration laws changed in the past few years/decades?
• How has the Black Lives Matter movement affected discussions and view about racism in the US?
• What impact has the Affordable Care Act had on healthcare in the US?
• What factors contributed to the UK deciding to leave the EU (Brexit)?
• What factors contributed to China becoming an economic power?
• Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
• Do students in schools that eliminate grades do better in college and their careers?
• Do students from wealthier backgrounds score higher on standardized tests?
• Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
• Do students who attend charter schools score higher on standardized tests than students in public schools?
• Do students learn better in same-sex classrooms?
• How does giving each student access to an iPad or laptop affect their studies?
• What are the benefits and drawbacks of the Montessori Method ?
• Do children who attend preschool do better in school later on?
• What was the impact of the No Child Left Behind act?
• How does the US education system compare to education systems in other countries?
• What impact does mandatory physical education classes have on students' health?
• Which methods are most effective at reducing bullying in schools?
• Do homeschoolers who attend college do as well as students who attended traditional schools?
• Does offering tenure increase or decrease quality of teaching?
• How does college debt affect future life choices of students?
• Should graduate students be able to form unions?

• What are different ways to lower gun-related deaths in the US?
• How and why have divorce rates changed over time?
• Is affirmative action still necessary in education and/or the workplace?
• Should physician-assisted suicide be legal?
• How has stem cell research impacted the medical field?
• How can human trafficking be reduced in the United States/world?
• Should people be able to donate organs in exchange for money?
• Which types of juvenile punishment have proven most effective at preventing future crimes?
• Has the increase in US airport security made passengers safer?
• Analyze the immigration policies of certain countries and how they are similar and different from one another.
• Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
• Do tariffs increase the number of domestic jobs?
• Which prison reforms have proven most effective?
• Should governments be able to censor certain information on the internet?
• Which methods/programs have been most effective at reducing teen pregnancy?
• What are the benefits and drawbacks of the Keto diet?
• How effective are different exercise regimes for losing weight and maintaining weight loss?
• How do the healthcare plans of various countries differ from each other?
• What are the most effective ways to treat depression ?
• What are the pros and cons of genetically modified foods?
• Which methods are most effective for improving memory?
• What can be done to lower healthcare costs in the US?
• What factors contributed to the current opioid crisis?
• Analyze the history and impact of the HIV/AIDS epidemic .
• Are low-carbohydrate or low-fat diets more effective for weight loss?
• How much exercise should the average adult be getting each week?
• Which methods are most effective to get parents to vaccinate their children?
• What are the pros and cons of clean needle programs?
• How does stress affect the body?
• Discuss the history of the conflict between Israel and the Palestinians.
• What were the causes and effects of the Salem Witch Trials?
• Who was responsible for the Iran-Contra situation?
• How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
• What events led to the fall of the Roman Empire?
• What were the impacts of British rule in India ?
• Was the atomic bombing of Hiroshima and Nagasaki necessary?
• What were the successes and failures of the women's suffrage movement in the United States?
• What were the causes of the Civil War?
• How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
• Which factors contributed to the colonies winning the American Revolution?
• What caused Hitler's rise to power?
• Discuss how a specific invention impacted history.
• What led to Cleopatra's fall as ruler of Egypt?
• How has Japan changed and evolved over the centuries?
• What were the causes of the Rwandan genocide ?

• Why did Martin Luther decide to split with the Catholic Church?
• Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
• How did the sexual abuse scandal impact how people view the Catholic Church?
• How has the Catholic church's power changed over the past decades/centuries?
• What are the causes behind the rise in atheism/ agnosticism in the United States?
• What were the influences in Siddhartha's life resulted in him becoming the Buddha?
• How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

• How has the earth's climate changed in the past few decades?
• How has the use and elimination of DDT affected bird populations in the US?
• Analyze how the number and severity of natural disasters have increased in the past few decades.
• Analyze deforestation rates in a certain area or globally over a period of time.
• How have past oil spills changed regulations and cleanup methods?
• How has the Flint water crisis changed water regulation safety?
• What are the pros and cons of fracking?
• What impact has the Paris Climate Agreement had so far?
• What have NASA's biggest successes and failures been?
• How can we improve access to clean water around the world?
• Does ecotourism actually have a positive impact on the environment?
• Should the US rely on nuclear energy more?
• What can be done to save amphibian species currently at risk of extinction?
• What impact has climate change had on coral reefs?
• How are black holes created?
• Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
• How will the loss of net neutrality affect internet users?
• Analyze the history and progress of self-driving vehicles.
• How has the use of drones changed surveillance and warfare methods?
• Has social media made people more or less connected?
• What progress has currently been made with artificial intelligence ?
• Do smartphones increase or decrease workplace productivity?
• What are the most effective ways to use technology in the classroom?
• How is Google search affecting our intelligence?
• When is the best age for a child to begin owning a smartphone?
• Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

Are you also learning about dynamic equilibrium in your science class? We break this sometimes tricky concept down so it's easy to understand in our complete guide to dynamic equilibrium .

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Want to know the fastest and easiest ways to convert between Fahrenheit and Celsius? We've got you covered! Check out our guide to the best ways to convert Celsius to Fahrenheit (or vice versa).

These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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Research Topic FAQs

What (exactly) is a research topic.

A research topic is the subject of a research project or study – for example, a dissertation or thesis. A research topic typically takes the form of a problem to be solved, or a question to be answered.

A good research topic should be specific enough to allow for focused research and analysis. For example, if you are interested in studying the effects of climate change on agriculture, your research topic could focus on how rising temperatures have impacted crop yields in certain regions over time.

To learn more about the basics of developing a research topic, consider our free research topic ideation webinar.

What constitutes a good research topic?

A strong research topic comprises three important qualities : originality, value and feasibility.

• Originality – a good topic explores an original area or takes a novel angle on an existing area of study.
• Value – a strong research topic provides value and makes a contribution, either academically or practically.
• Feasibility – a good research topic needs to be practical and manageable, given the resource constraints you face.

To learn more about what makes for a high-quality research topic, check out this post .

What's the difference between a research topic and research problem?

A research topic and a research problem are two distinct concepts that are often confused. A research topic is a broader label that indicates the focus of the study , while a research problem is an issue or gap in knowledge within the broader field that needs to be addressed.

To illustrate this distinction, consider a student who has chosen “teenage pregnancy in the United Kingdom” as their research topic. This research topic could encompass any number of issues related to teenage pregnancy such as causes, prevention strategies, health outcomes for mothers and babies, etc.

Within this broad category (the research topic) lies potential areas of inquiry that can be explored further – these become the research problems . For example:

• What factors contribute to higher rates of teenage pregnancy in certain communities?
• How do different types of parenting styles affect teen pregnancy rates?
• What interventions have been successful in reducing teenage pregnancies?

Simply put, a key difference between a research topic and a research problem is scope ; the research topic provides an umbrella under which multiple questions can be asked, while the research problem focuses on one specific question or set of questions within that larger context.

How can I find potential research topics for my project?

There are many steps involved in the process of finding and choosing a high-quality research topic for a dissertation or thesis. We cover these steps in detail in this video (also accessible below).

How can I find quality sources for my research topic?

Finding quality sources is an essential step in the topic ideation process. To do this, you should start by researching scholarly journals, books, and other academic publications related to your topic. These sources can provide reliable information on a wide range of topics. Additionally, they may contain data or statistics that can help support your argument or conclusions.

Identifying Relevant Sources

When searching for relevant sources, it’s important to look beyond just published material; try using online databases such as Google Scholar or JSTOR to find articles from reputable journals that have been peer-reviewed by experts in the field.

You can also use search engines like Google or Bing to locate websites with useful information about your topic. However, be sure to evaluate any website before citing it as a source—look for evidence of authorship (such as an “About Us” page) and make sure the content is up-to-date and accurate before relying on it.

Evaluating Sources

Once you’ve identified potential sources for your research project, take some time to evaluate them thoroughly before deciding which ones will best serve your purpose. Consider factors such as author credibility (are they an expert in their field?), publication date (is the source current?), objectivity (does the author present both sides of an issue?) and relevance (how closely does this source relate to my specific topic?).

By researching the current literature on your topic, you can identify potential sources that will help to provide quality information. Once you’ve identified these sources, it’s time to look for a gap in the research and determine what new knowledge could be gained from further study.

How can I find a good research gap?

Finding a strong gap in the literature is an essential step when looking for potential research topics. We explain what research gaps are and how to find them in this post.

How should I evaluate potential research topics/ideas?

When evaluating potential research topics, it is important to consider the factors that make for a strong topic (we discussed these earlier). Specifically:

• Originality
• Feasibility

So, when you have a list of potential topics or ideas, assess each of them in terms of these three criteria. A good topic should take a unique angle, provide value (either to academia or practitioners), and be practical enough for you to pull off, given your limited resources.

Finally, you should also assess whether this project could lead to potential career opportunities such as internships or job offers down the line. Make sure that you are researching something that is relevant enough so that it can benefit your professional development in some way. Additionally, consider how each research topic aligns with your career goals and interests; researching something that you are passionate about can help keep motivation high throughout the process.

How can I assess the feasibility of a research topic?

When evaluating the feasibility and practicality of a research topic, it is important to consider several factors.

First, you should assess whether or not the research topic is within your area of competence. Of course, when you start out, you are not expected to be the world’s leading expert, but do should at least have some foundational knowledge.

Time commitment

When considering a research topic, you should think about how much time will be required for completion. Depending on your field of study, some topics may require more time than others due to their complexity or scope.

Additionally, if you plan on collaborating with other researchers or institutions in order to complete your project, additional considerations must be taken into account such as coordinating schedules and ensuring that all parties involved have adequate resources available.

Resources needed

It’s also critically important to consider what type of resources are necessary in order to conduct the research successfully. This includes physical materials such as lab equipment and chemicals but can also include intangible items like access to certain databases or software programs which may be necessary depending on the nature of your work. Additionally, if there are costs associated with obtaining these materials then this must also be factored into your evaluation process.

Potential risks

It’s important to consider the inherent potential risks for each potential research topic. These can include ethical risks (challenges getting ethical approval), data risks (not being able to access the data you’ll need), technical risks relating to the equipment you’ll use and funding risks (not securing the necessary financial back to undertake the research).

If you’re looking for more information about how to find, evaluate and select research topics for your dissertation or thesis, check out our free webinar here . Alternatively, if you’d like 1:1 help with the topic ideation process, consider our private coaching services .

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Research Topics – Ideas and Examples

Table of Contents

Research Topic

Definition:

Research topic is a specific subject or area of interest that a researcher wants to investigate or explore in-depth through research. It is the overarching theme or question that guides a research project and helps to focus the research activities towards a clear objective.

How to Choose Research Topic

You can Choose a Research Topic by following the below guide:

Identify your Interests

One of the most important factors to consider when choosing a research topic is your personal interest. This is because you will be spending a considerable amount of time researching and writing about the topic, so it’s essential that you are genuinely interested and passionate about it. Start by brainstorming a list of potential research topics based on your interests, hobbies, or areas of expertise. You can also consider the courses that you’ve enjoyed the most or the topics that have stood out to you in your readings.

Review the Literature

Before deciding on a research topic, you need to understand what has already been written about it. Conducting a preliminary review of the existing literature in your field can help you identify gaps in knowledge, inconsistencies in findings, or unanswered questions that you can explore further. You can do this by reading academic articles, books, and other relevant sources in your field. Make notes of the themes or topics that emerge and use this information to guide your research question.

Consult with your Advisor

Your academic advisor or a mentor in your field can provide you with valuable insights and guidance on choosing a research topic. They can help you identify areas of interest, suggest potential research questions, and provide feedback on the feasibility of your research proposal. They can also direct you towards relevant literature and resources that can help you develop your research further.

Consider the Scope and Feasibility

The research topic you choose should be manageable within the time and resource constraints of your project. Be mindful of the scope of your research and ensure that you are not trying to tackle a topic that is too broad or too narrow. If your topic is too broad, you may find it challenging to conduct a comprehensive analysis, while if it’s too narrow, you may struggle to find enough material to support your research.

Brainstorm with Peers

Discussing potential research topics with your peers or colleagues can help you generate new ideas and perspectives. They may have insights or expertise that you haven’t considered, and their feedback can help you refine your research question. You can also join academic groups or attend conferences in your field to network with other researchers and get inspiration for your research.

Consider the Relevance

Choose a research topic that is relevant to your field of study and has the potential to contribute to the existing knowledge. You can consider the latest trends and emerging issues in your field to identify topics that are both relevant and interesting. Conducting research on a topic that is timely and relevant can also increase the likelihood of getting published or presenting your research at conferences.

Keep an Open Mind

While it’s essential to choose a research topic that aligns with your interests and expertise, you should also be open to exploring new ideas or topics that may be outside of your comfort zone. Consider researching a topic that challenges your assumptions or introduces new perspectives that you haven’t considered before. You may discover new insights or perspectives that can enrich your research and contribute to your growth as a researcher.

Components of Research Topic

A research topic typically consists of several components that help to define and clarify the subject matter of the research project. These components include:

• Research problem or question: This is the central issue or inquiry that the research seeks to address. It should be well-defined and focused, with clear boundaries that limit the scope of the research.
• Background and context: This component provides the necessary background information and context for the research topic. It explains why the research problem or question is important, relevant, and timely. It may also include a literature review that summarizes the existing research on the topic.
• Objectives or goals : This component outlines the specific objectives or goals that the research seeks to achieve. It should be clear and concise, and should align with the research problem or question.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It should be detailed enough to provide a clear understanding of how the research will be conducted, including the sampling method, data collection tools, and statistical analyses.
• Significance or contribution : This component explains the significance or contribution of the research topic. It should demonstrate how the research will add to the existing knowledge in the field, and how it will benefit practitioners, policymakers, or society at large.
• Limitations: This component outlines the limitations of the research, including any potential biases, assumptions, or constraints. It should be transparent and honest about the potential shortcomings of the research, and how these limitations will be addressed.
• Expected outcomes or findings : This component provides an overview of the expected outcomes or findings of the research project. It should be realistic and based on the research objectives and methodology.

Purpose of Research Topic

The purpose of a research topic is to identify a specific area of inquiry that the researcher wants to explore and investigate. A research topic is typically a broad area of interest that requires further exploration and refinement through the research process. It provides a clear focus and direction for the research project, and helps to define the research questions and objectives. A well-defined research topic also helps to ensure that the research is relevant and useful, and can contribute to the existing body of knowledge in the field. Ultimately, the purpose of a research topic is to generate new insights, knowledge, and understanding about a particular phenomenon, issue, or problem.

Characteristics of Research Topic

some common characteristics of a well-defined research topic include:

• Relevance : A research topic should be relevant and significant to the field of study and address a current issue, problem, or gap in knowledge.
• Specificity : A research topic should be specific enough to allow for a focused investigation and clear understanding of the research question.
• Feasibility : A research topic should be feasible, meaning it should be possible to carry out the research within the given constraints of time, resources, and expertise.
• Novelty : A research topic should add to the existing body of knowledge by introducing new ideas, concepts, or theories.
• Clarity : A research topic should be clearly articulated and easy to understand, both for the researcher and for potential readers of the research.
• Importance : A research topic should be important and have practical implications for the field or society as a whole.
• Significance : A research topic should be significant and have the potential to generate new insights and understanding in the field.

Examples of Research Topics

Here are some examples of research topics that are currently relevant and in-demand in various fields:

• The impact of social media on mental health: With the rise of social media use, this topic has gained significant attention in recent years. Researchers could investigate how social media affects self-esteem, body image, and other mental health concerns.
• The use of artificial intelligence in healthcare: As healthcare becomes increasingly digitalized, researchers could explore the use of AI algorithms to predict and prevent disease, optimize treatment plans, and improve patient outcomes.
• Renewable energy and sustainable development: As the world seeks to reduce its carbon footprint, researchers could investigate the potential of renewable energy sources such as wind and solar power, and how these technologies can be integrated into existing infrastructure.
• The impact of workplace diversity and inclusion on employee productivity: With an increasing focus on diversity and inclusion in the workplace, researchers could investigate how these factors affect employee morale, productivity, and retention.
• Cybersecurity and data privacy: As data breaches and cyber attacks become more common, researchers could explore new methods of protecting sensitive information and preventing malicious attacks.
• T he impact of mindfulness and meditation on stress reduction: As stress-related health issues become more prevalent, researchers could investigate the effectiveness of mindfulness and meditation practices on reducing stress and improving overall well-being.

Research Topics Ideas

Here are some Research Topics Ideas from different fields:

• The impact of social media on mental health and well-being.
• The effectiveness of various teaching methods in improving academic performance in high schools.
• The role of AI and machine learning in healthcare: current applications and future potentials.
• The impact of climate change on wildlife habitats and conservation efforts.
• The effects of video game violence on aggressive behavior in young adults.
• The effectiveness of mindfulness-based stress reduction techniques in reducing anxiety and depression.
• The impact of technology on human relationships and social interactions.
• The role of exercise in promoting physical and mental health in older adults.
• The causes and consequences of income inequality in developed and developing countries.
• The effects of cultural diversity in the workplace on job satisfaction and productivity.
• The impact of remote work on employee productivity and work-life balance.
• The relationship between sleep patterns and cognitive functioning.
• The effectiveness of online learning versus traditional classroom learning.
• The role of government policies in promoting renewable energy adoption.
• The effects of childhood trauma on mental health in adulthood.
• The impact of social media on political participation and civic engagement.
• The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
• The relationship between nutrition and cognitive functioning.
• The impact of gentrification on urban communities.
• The effects of music on mood and emotional regulation.
• The impact of microplastics on marine ecosystems and food webs.
• The role of artificial intelligence in detecting and preventing cyberattacks.
• The effectiveness of mindfulness-based interventions in managing chronic pain.
• The relationship between personality traits and job satisfaction.
• The effects of social isolation on mental and physical health in older adults.
• The impact of cultural and linguistic diversity on healthcare access and outcomes.
• The effectiveness of psychotherapy in treating depression and anxiety in adolescents.
• The relationship between exercise and cognitive aging.
• The effects of social media on body image and self-esteem.
• The role of corporate social responsibility in promoting sustainable business practices.
• The impact of mindfulness meditation on attention and focus in children.
• The relationship between political polarization and media consumption habits.
• The effects of urbanization on mental health and well-being.
• The role of social support in managing chronic illness.
• The impact of social media on romantic relationships and dating behaviors.
• The effectiveness of behavioral interventions in promoting physical activity in sedentary adults.
• The relationship between sleep quality and immune function.
• The effects of workplace diversity and inclusion programs on employee retention.
• The impact of climate change on global food security.
• The role of music therapy in improving communication and social skills in individuals with autism spectrum disorder.
• The impact of cultural values on the development of mental health stigma.
• The effectiveness of mindfulness-based stress reduction techniques in reducing burnout in healthcare professionals.
• The relationship between social media use and body dissatisfaction among adolescents.
• The effects of nature exposure on cognitive functioning and well-being.
• The role of peer mentoring in promoting academic success in underrepresented student populations.
• The impact of neighborhood characteristics on physical activity and obesity.
• The effectiveness of cognitive rehabilitation interventions in improving cognitive functioning in individuals with traumatic brain injury.
• The relationship between organizational culture and employee job satisfaction.
• The effects of cultural immersion experiences on intercultural competence development.
• The role of assistive technology in promoting independence and quality of life for individuals with disabilities.
• The impact of workplace design on employee productivity and well-being.
• The impact of digital technologies on the music industry and artist revenues.
• The effectiveness of cognitive behavioral therapy in treating insomnia.
• The relationship between social media use and body weight perception among young adults.
• The effects of green spaces on mental health and well-being in urban areas.
• The role of mindfulness-based interventions in reducing substance use disorders.
• The impact of workplace bullying on employee turnover and job satisfaction.
• The effectiveness of animal-assisted therapy in treating mental health disorders.
• The relationship between teacher-student relationships and academic achievement.
• The effects of social support on resilience in individuals experiencing adversity.
• The role of cognitive aging in driving safety and mobility.
• The effectiveness of psychotherapy in treating post-traumatic stress disorder (PTSD).
• The relationship between social media use and sleep quality.
• The effects of cultural competency training on healthcare providers’ attitudes and behaviors towards diverse patient populations.
• The role of exercise in preventing chronic diseases such as type 2 diabetes and cardiovascular disease.
• The impact of the gig economy on job security and worker rights.
• The effectiveness of art therapy in promoting emotional regulation and coping skills in children and adolescents.
• The relationship between parenting styles and child academic achievement.
• The effects of social comparison on well-being and self-esteem.
• The role of nutrition in promoting healthy aging and longevity.
• The impact of gender diversity in leadership on organizational performance.
• The effectiveness of family-based interventions in treating eating disorders.
• The relationship between social media use and perceived loneliness among older adults.
• The effects of mindfulness-based interventions on pain management in chronic pain patients.
• The role of physical activity in preventing and treating depression.
• The impact of cultural differences on communication and conflict resolution in international business.
• The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating anxiety disorders.
• The relationship between student engagement and academic success in higher education.
• The effects of discrimination on mental health outcomes in minority populations.
• The role of virtual reality in enhancing learning experiences.
• The impact of social media influencers on consumer behavior and brand loyalty.
• The effectiveness of acceptance and commitment therapy (ACT) in treating chronic pain.
• The relationship between social media use and body image dissatisfaction among men.
• The effects of exposure to nature on cognitive functioning and creativity.
• The role of spirituality in coping with illness and disability.
• The impact of automation on employment and job displacement.
• The effectiveness of dialectical behavior therapy (DBT) in treating borderline personality disorder.
• The relationship between teacher-student relationships and school attendance.
• The effects of mindfulness-based interventions on workplace stress and burnout.
• The role of exercise in promoting cognitive functioning and brain health in older adults.
• The impact of diversity and inclusion initiatives on organizational innovation and creativity.
• The effectiveness of cognitive remediation therapy in treating schizophrenia.
• The relationship between social media use and body dissatisfaction among women.
• The effects of exposure to natural light on mood and sleep quality.
• The role of spirituality in enhancing well-being and resilience in military personnel.
• The impact of artificial intelligence on job training and skill development.
• The effectiveness of interpersonal therapy (IPT) in treating depression.
• The relationship between parental involvement and academic achievement among low-income students.
• The effects of mindfulness-based interventions on emotional regulation and coping skills in trauma survivors.
• The role of nutrition in preventing and treating mental health disorders.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Creating a Successful Research Topic Statement (PSY)

In this tutorial, we will identify what makes for a successful research topic.

Most research topics start out as a general and often vague idea that a researcher has an interest in investigating.

Inexperienced researchers, including most doctoral learners, frequently think of topics that are quite interesting, but not narrowly enough focused for a dissertation.

This tutorial will guide you through a set of steps designed to help you come up with a topic, first of all, and secondly to focus it more tightly so that you can begin a meaningful and successful search of the existing literature to discover whether your topic is actually researchable.

This tutorial's primary objective is to prepare you to create a successful research topic that may become the topic of your dissertation. To do that, we'll work through the following issues:

• First, what are the characteristics of a well-formed research topic?
• Second, how are research topics evaluated?
• Third, how can the key concepts and the population be narrowed and focused so that they are researchable?
• Fourth, how can the relationship among concepts be named so that the appropriate methodological literature can be accessed in the literature review?

Obviously, in Track 1 you are at the beginning of your studies toward the doctorate, and perhaps your dissertation is far from your thoughts. We are starting the process now, however, because our experience has been that when learners wait to start searching for their topics, it often creates a serious problem for them when they actually start the dissertation. That problem can take many forms, but the most common one is that they have not had sufficient time (and training) in exhaustively searching the relevant literature to discover whether the topic they are interested in is even viable—and without a good topic statement, a good literature search is impossible. So let's begin.

What Is a Research Topic?

A research topic is an area of interest to a researcher that is first of all, researchable. It is focused narrowly enough that its key concepts are quite plain and well integrated. It is a topic or subject that can be found in the existing literature of the researcher's field, which shows that it is of some interest or importance to that field, and has some important characteristics.

Characteristics of a Well-formed Research Topic

The first mark of a well-formed topic is that it clearly states the key concepts to be investigated. Sometimes, only one concept is named—those studies often turn out to be qualitative, but not always. More often, two or more key concepts are named. Next, it identifies the relationship or relationships among those concepts that the researcher intends to explore. Obviously, if only one concept was named, there won't be a relationship, but in that case a word like "describes" or "experiences" will give a clue to the kind of information desired. Third, a research topic specifies the population of interest to be investigated. Finally, a research topic is just a phrase. That is, it is not a full sentence with a verb. However, the well-formed topic statement will embed the actual topic in a complete sentence. Let's look at some examples.

Some Examples of Topic Statements

Here are a few topic statements that eventually lead to successful dissertations:

• Elementary age students' needs for family-based counseling services.
• Indigenous people's responses to encounters with law enforcement.
• Impact of mother's death on daughters in poor, middle class, and wealthy families.
• The relationship between assignment strategies to prevent burnout used by managers of first responders and the occurrence of burnout.
• Employees' productivity as a function of their managers' management styles.
• Strategies used by mainstream classroom teachers to manage children with behavior problems who do not receive special education.

You can see immediately that all six examples, taken from the four schools in Capella University, are phrases, not complete sentences. So far, so good. The first mark of a successful topic statement is that it identifies the key concepts to be investigated, right? Let's see how the examples do that.

Evaluating the Form of the Examples: Key Concepts

In the first example, we seem to have two key concepts: "needs" and "family-based counseling services." Are they stated clearly? Probably not clearly enough: what is meant by "needs" and "family-based counseling services" is not immediately transparent. This topic will need some work, but most topics start out this way.

Let's try another: Indigenous people’s responses to encounters with law enforcement. Here, there seem to be two key concepts: "responses" and "encounters with law enforcement." These concepts are quite broad and will have to be narrowed considerably to support a researchable topic, but they provide a good start.

Let's do one more: Employees' productivity as a function of their managers' management styles.

Here, there are two key concepts, right? Productivity and management styles.

Evaluating the Form of Topics: Relationship(s) among the Key Concepts

The second mark of a successful topic is that it identifies any relationship to be investigated between or among the key concepts. Let's look at the third example to see about this.

This topic meets our criterion of being a phrase. It seems to state at least two concepts (but with multiple levels): "death" and "socio-economic status of daughters." What about the relationship? Well, it is captured in that word "impact."

An "impact" in research jargon means the effect that one concept—death—has on another concept, in this case, the daughters. One can, in fact, replace the word impact with the word effect without changing the meaning at all. So the topic is proposing a cause-and-effect kind of relationship.

Let's look at another example: The relationship between assignment strategies to prevent burnout used by managers of first responders and the occurrence of burnout

This seems complicated, but it really isn't. First, let's check the key concepts: "Assignment strategies to prevent burnout" would seem to be one key concept, and "occurrence of burnout" would be the other. These are reasonably clear, or probably would be to someone in the human resources or management worlds. No doubt they will be further clarified as the researcher works on the topic's wording. But what about the relationship? It is in the word "relationship," obviously. And in research jargon, a "relationship" between A and B is a particular kind of relationship, called a correlation.

Now, play with the other topics to see if you can identify the relationship—if any.

Evaluating the Form of Topics: Target Population

The third sign of a successful topic is that it names the target population, the group of people or organizations or groups that the researcher is interested in. Let's evaluate some of our examples on this point.

• Elementary age students' needs for family-based counseling services : The population here is stated: Students of elementary school age.
• Indigenous people's responses to encounters with law enforcement: Here as well, the population is indigenous people.
• Impact of mother's death on daughters in poor, middle class, and wealthy families: The population is daughters in three socio-economic groups.
• The relationship between assignment strategies to prevent burnout used by managers of first responders and the occurrence of burnout: You determine who the population is in this one.

Is It Managers or Is It First Responders?

The population is managers of first responders. Or is it? The awkward wording of the topic makes this a bit hard to digest. The burnout occurs in the first responders, so maybe they are the population. But the first responders' managers are the ones using the management strategies, so are they the population?

Well, the two key concepts are management strategies (used by managers) and rate of burnout (in first responders), so the researcher will have to get information from both groups of people, so both are the target population: first responders and their managers.

Take a minute and try to figure out the rest of our examples.

Summing Up the Characteristics of a Successful Topic

We've seen in action the three chief marks of a successful research topic.

• The topic states the key concepts to be investigated.
• It states what relationship between or among the concepts will be explored. Remember, if there is only one concept (which often is the case in qualitative studies), there won't be a relationship. But if there are two or more key concepts, look for the relationship between or among them.
• The successful topic names the population of interest for the study.

A well-formed research topic will have these characteristics, but simply having them is not sufficient. The elements also need to be well-focused and narrowed down to a point where the research becomes feasible. Let's take a look at a simple method for doing this.

Narrowing the Focus

Take a look at this grid. You'll see that one of our topics has been broken out into the first column. The population is first—indigenous people—followed by two concepts: responses and law enforcement. Now look at the central column, labeled "Narrower term." Notice how the very broad population has been narrowed. Similarly, "law enforcement" has been narrowed to police (there are many other types of law enforcement, such as FBI, Homeland Security, TSA, Customs and Immigration, sheriff's departments, and so on). Similarly, there are many kinds of behaviors and experiences that could be considered "responses," but the researcher is most interested in emotional responses. Now move to the third column. Can you see how each term is being narrowed yet again?

If we restated the topic now, after having narrowed it down a bit, it would look like this: Cherokee Indians' tolerance for stress when meeting traffic officers.

Let's work through another example, this time using the topic "Employees' productivity as a function of their managers' management styles."

You can see the key terms lined up in the first column. The other two columns are blank.

What would you ask yourself, if this were your topic, in order to narrow this down?

Questions to Ask for Narrowing a Topic

There are many questions you can ask yourself when you are narrowing your topic. A good opener is "So what do I really want to know about the concept?"

Another quite good question is to ask about your real interest or passion is about the concept or the population.

You can also find helpful terms by performing controlled vocabulary searches in library databases. You can find a nice tutorial on that method of searching in the Capella library at but whatever you ask yourself, keep your focus on what you truly most want to know and care about regarding the concept.

Now, let's get back to our example.

When the researcher asked herself what sort of employees and managers she was actually interested in, she realized it was service employees and managers. The more she pondered, and was helped by a quick check of the literature in her specialization, she realized that she was most interested in call center personnel. Then she tackled productivity . From her courses in management measurement, she knew that one way to think about productivity was days at work. But that seemed too dependent on factors outside the manager-employee relationship. She wanted a more fine-grained way to look at productivity, so she narrowed it to a specific measure, calls completed times minutes per call.

Then she took on management styl e. Knowing that there are many types, her first attempt at focusing this term was authoritarian style. That didn't satisfy her, and when she looked again at her topic, she realized that that word "function" was important. It implied to her that she was really interested in knowing how different management styles related to different degrees of productivity. At first, she put together a list of known management styles, but that felt intimidating. She decided to narrow it down to just two: authoritarian vs. flexible management style.

After all this, her topic now looked like this: Productivity as measured by calls completed times minutes per call in call center employees supervised by authoritarian managers compared to productivity in call center employees supervised by flexible managers.

She knew the wording was clunky and would need to be crafted better, but she had a much more focused topic. So far, we've been looking at two things about good research topics: what they should contain (concepts, relationships, and population), and how to narrow each element. In these narrowing exercises, we've focused on the concepts and the population. Now, let's turn our attention to the relationship . This is a very important element, because it offers an important clue about the nature of the study that might ensue.

Evaluating the Relationship Named in the Topic

Research asks all kinds of questions, and the relationship named in the research topic clues us into what kind of question the ensuing study will likely ask. Here are some questions you might ask in order to choose the right word to describe the relationship you're looking for.

What do you envision really doing?

• Looking at comparisons between variables or groups of people?
• Looking at relationships between two or more concepts?
• Looking at effects of one or more concept on another concept or group?
• Looking at outcomes of some process or treatment or condition?
• Looking at experiences?
• Developing a theory to explain some phenomenon?

For each of these (and there are other sorts of questions you can ask yourself), specific words can specify the relationship. Let's look at them.

If your topic compares two or more things compared with or some similar phrase indicates the relationship you want to know about. For instance, student retention rates in large urban school districts compared with small rural districts.

If your interest is about relationships between two or more concepts, try using words like relationship, in relation to, or other similar constructions. Here's an example: the frequency of church attendance in relation to socioeconomic status.

Suppose your interest is to see if one thing has an effect on something else. In that case, you can use that word, effect, or other words such as influence, impact, cause, predict, and the like. For example, the influence of tax policy on employment patterns in Midwestern communities.

An outcome is another version of a cause-and-effect relationship, specifically when you are interested in the final condition after some kind of process. For instance, the outcome of a training program. That word is excellent to use for the relationship, as in the outcome of training program A as measured by employee comprehension of corporate policies.

Are you interested in describing a certain experience, such as falling in love or being laid off work or having a baby or starting a new company? Having experiences is a very subjective thing, and the actual experience is a single thing—not one of a few variables. So there is no relationship to specify in such a topic, but the only way to learn about people's experiences is to ask them to describe them. So, words like descriptions of, accounts of, reports of, and the like can be very helpful. For instance, men's descriptions of their spiritual transformations when recovering from alcoholism.

Okay, we've covered the basics of how to craft a well-formed research topic. We've seen the marks of a good topic. They are:

• The key concepts are clearly stated and well-focused so that they can be profitably found in the literature.
• Second, the relationship, if any, between or among them is clearly stated. Even if there is no relationship, what you're really looking for (descriptions? accounts? reports?) can be seen in the wording.
• Third, the people you want to study, your population, is clearly stated and narrowed down to a workable point. You have all these points covered in a single phrase, and if after narrowing it down that phrase is awkward, you will work on crafting it into a more graceful form.

In a minute, you'll get to work crafting your own research topic, but first I want to show you why we emphasize the importance of narrowing and focusing the key concepts, relationships, and populations.

What Do You Do With the Research Topic?

The research topic is step 1 in the sequential process of research design. Once you have your topic in hand, step 2 is to take it to the library and begin searching for existing research and theory on the topic. Here's where your key concepts need to be well-defined and narrowly focused. You will be looking for all the existing research on those key concepts when you start.

At first, you'll investigate each of your key concepts individually, to find out what the existing literature has to say about them in and of themselves. Later, after you have developed a good working knowledge of the background concepts, you'll dig deeper into research linking the key concepts together.

At the third level, you'll follow the "breadcrumbs" all the way back to the earliest studies on your topic so that you will, ultimately, master that literature fully.

So your topic statement is the foundation. It organizes your various literature reviews. Searching on the key concepts (translated into various key words) will help you organize the content of your study.

Searching on the existing methodological literature about the relationship named in your topic will prepare you for your methodological decisions in later steps of research design.

There is an old Chinese proverb found in the I Ching and many other places: “Patience in the beginning brings success.” If you are careful and attentive, and work patiently to write your research topic, then rewrite it, then rewrite it again and again, you will have a solid foundation on which to start building your literature review. The topic is your beginning.

Remain patient and steady, and you will succeed.

Doc. reference: phd_t1_u04s1_mpsuccess.html

How Much Research Is Being Written by Large Language Models?

New studies show a marked spike in LLM usage in academia, especially in computer science. What does this mean for researchers and reviewers?

In March of this year, a  tweet about an academic paper went viral for all the wrong reasons. The introduction section of the paper, published in  Elsevier’s  Surfaces and Interfaces , began with this line:  Certainly, here is a possible introduction for your topic. 

Look familiar? 

It should, if you are a user of ChatGPT and have applied its talents for the purpose of content generation. LLMs are being increasingly used to assist with writing tasks, but examples like this in academia are largely anecdotal and had not been quantified before now. 

“While this is an egregious example,” says  James Zou , associate professor of biomedical data science and, by courtesy, of computer science and of electrical engineering at Stanford, “in many cases, it’s less obvious, and that’s why we need to develop more granular and robust statistical methods to estimate the frequency and magnitude of LLM usage. At this particular moment, people want to know what content around us is written by AI. This is especially important in the context of research, for the papers we author and read and the reviews we get on our papers. That’s why we wanted to study how much of those have been written with the help of AI.”

In two papers looking at LLM use in scientific publishings, Zou and his team* found that 17.5% of computer science papers and 16.9% of peer review text had at least some content drafted by AI. The paper on LLM usage in peer reviews will be presented at the International Conference on Machine Learning.

Read  Mapping the Increasing Use of LLMs in Scientific Papers and  Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews  

Here Zou discusses the findings and implications of this work, which was supported through a Stanford HAI Hoffman Yee Research Grant . 

How did you determine whether AI wrote sections of a paper or a review?

We first saw that there are these specific worlds – like commendable, innovative, meticulous, pivotal, intricate, realm, and showcasing – whose frequency in reviews sharply spiked, coinciding with the release of ChatGPT. Additionally, we know that these words are much more likely to be used by LLMs than by humans. The reason we know this is that we actually did an experiment where we took many papers, used LLMs to write reviews of them, and compared those reviews to reviews written by human reviewers on the same papers. Then we quantified which words are more likely to be used by LLMs vs. humans, and those are exactly the words listed. The fact that they are more likely to be used by an LLM and that they have also seen a sharp spike coinciding with the release of LLMs is strong evidence.

Some journals permit the use of LLMs in academic writing, as long as it’s noted, while others, including  Science and the ICML conference, prohibit it. How are the ethics perceived in academia?

This is an important and timely topic because the policies of various journals are changing very quickly. For example,  Science said in the beginning that they would not allow authors to use language models in their submissions, but they later changed their policy and said that people could use language models, but authors have to explicitly note where the language model is being used. All the journals are struggling with how to define this and what’s the right way going forward.

You observed an increase in usage of LLMs in academic writing, particularly in computer science papers (up to 17.5%). Math and  Nature family papers, meanwhile, used AI text about 6.3% of the time. What do you think accounts for the discrepancy between these disciplines? 

Artificial intelligence and computer science disciplines have seen an explosion in the number of papers submitted to conferences like ICLR and NeurIPS. And I think that’s really caused a strong burden, in many ways, to reviewers and to authors. So now it’s increasingly difficult to find qualified reviewers who have time to review all these papers. And some authors may feel more competition that they need to keep up and keep writing more and faster. 

You analyzed close to a million papers on arXiv, bioRxiv, and  Nature from January 2020 to February 2024. Do any of these journals include humanities papers or anything in the social sciences?  

We mostly wanted to focus more on CS and engineering and biomedical areas and interdisciplinary areas, like  Nature family journals, which also publish some social science papers. Availability mattered in this case. So, it’s relatively easy for us to get data from arXiv, bioRxiv, and  Nature . A lot of AI conferences also make reviews publicly available. That’s not the case for humanities journals.

Did any results surprise you?

A few months after ChatGPT’s launch, we started to see a rapid, linear increase in the usage pattern in academic writing. This tells us how quickly these LLM technologies diffuse into the community and become adopted by researchers. The most surprising finding is the magnitude and speed of the increase in language model usage. Nearly a fifth of papers and peer review text use LLM modification. We also found that peer reviews submitted closer to the deadline and those less likely to engage with author rebuttal were more likely to use LLMs. 

This suggests a couple of things. Perhaps some of these reviewers are not as engaged with reviewing these papers, and that’s why they are offloading some of the work to AI to help. This could be problematic if reviewers are not fully involved. As one of the pillars of the scientific process, it is still necessary to have human experts providing objective and rigorous evaluations. If this is being diluted, that’s not great for the scientific community.

What do your findings mean for the broader research community?

LLMs are transforming how we do research. It’s clear from our work that many papers we read are written with the help of LLMs. There needs to be more transparency, and people should state explicitly how LLMs are used and if they are used substantially. I don’t think it’s always a bad thing for people to use LLMs. In many areas, this can be very useful. For someone who is not a native English speaker, having the model polish their writing can be helpful. There are constructive ways for people to use LLMs in the research process; for example, in earlier stages of their draft. You could get useful feedback from a LLM in real time instead of waiting weeks or months to get external feedback. 

But I think it’s still very important for the human researchers to be accountable for everything that is submitted and presented. They should be able to say, “Yes, I will stand behind the statements that are written in this paper.”

*Collaborators include:  Weixin Liang ,  Yaohui Zhang ,  Zhengxuan Wu ,  Haley Lepp ,  Wenlong Ji ,  Xuandong Zhao ,  Hancheng Cao ,  Sheng Liu ,  Siyu He ,  Zhi Huang ,  Diyi Yang ,  Christopher Potts ,  Christopher D. Manning ,  Zachary Izzo ,  Yaohui Zhang ,  Lingjiao Chen ,  Haotian Ye , and Daniel A. McFarland .

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition.  Learn more . 

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Defining the Question: Background and Foreground Questions

Background questions can help you develop foundational knowledge about whatever topic interests you..

Topic example:   mindfulness training and chronic pain management in patients with fibromyalgia

Here are some examples of background questions related to the topic:

• What populations of people are most impacted by fibromyalgia?
• What types of therapies are most commonly used to treat pain in fibromyalgia patients?
• How is mindfulness defined? Are there different types of mindfulness training? If so, what are they?
• What are the core principles underlying mindfulness and mindfulness training?
• How does one measure chronic pain?

The Find Background Information section of this guide lists useful sources for answering background questions.

Foreground questions are specific. They often deal with a particular therapy or intervention of interest.

A research question framework can help you organize the concepts in your foreground question. There are a number of different frameworks. The one you choose should correspond to the type of question you are asking.

• PICO ( P roblem/Population, I ntervention, C omparison, O utcome): The most common clinical question framework. Useful for clinical questions addressing the effect of an intervention, therapy, or treatment. 
• ECLIPSe (E xpectation, C lient Group, L ocation, I mpact, P rofessionals, Se rvice) : Useful for questions about policy and services.
• PCC ( P opulation/Problem, C oncept, C ontext): Useful for broad scoping questions.
• PEO ( P opulation, E xposure, O utcome): Useful for describing association between exposures/risk factors and outcomes.
• SPICE ( S etting, P erspective, I ntervention/phenomenon of Interest, C omparison, E valuation): Useful for evaluating the outcomes of a service, project, or intervention.
• SPIDER (S ample, P henomenon of I nterest, D esign, E valuation, R esearch Type): Useful for questions of experience or perspectives (questions that may be addressed by qualitative or mixed methods research).

PICO Framework Example

P (Population/Problem of Interest) = People with fibromyalgia

I (Intervention) = Aquatic therapy

C (Comparison Intervention) = No aquatic therapy

O (Outcome) = Reduction in pain

ECLIPSe Framework Example

E (Expectation) = To increase access to physical therapy services

C  (Client Group) = People with osteoarthritis living in rural communities

L  (Location of service or policy) = Hospitals

I  (Impact of service or policy) = Increased utilization of physical therapy services by people with osteoarthritis living in rural areas

P  (Professionals involved in offering the service or policy) = Physical therapists, Hospital administrators

Se  (Service) = Physical therapy services

PCC Framework Example

P  (Population characteristics or Problem focus) = Graduate students

C  (Concept being examined) = Technological literacy

C  (Context for the question - could include geographic location, setting of interest, etc.) = Physical therapy programs

PEO Example

P  (Population) = Novice physical therapists

E  (Exposure)=Mentoring programs

O  (Outcome)=Professional confidence

SPICE Example

S  (Setting) = Physical therapy graduate programs

P  (Perspective) = New physical therapy graduate students

I  (Intervention/Interest/Exposure) = Mindfulness training

C  (Comparison) = No mindfulness training

E  (Evaluation) = Reduced stress levels

SPIDER Example

S  (Sample, i.e. the group being studied) = Physical therapy interns

PI  Phenomenon of Interest, i.e., the reason for the behavior or decisions) = Clinical placements in extended care facilities

D  (Design, i.e. how the research was collected) = Surveys and interviews

E  (Evaluation, i.e. the outcome being impacted) = Experiences and attitudes

R  (Research type) = Qualitative, quantitative, or mixed methods

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• Last Updated: May 15, 2024 11:39 AM
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AI-assisted writing is quietly booming in academic journals—here's why that's OK

by Julian Koplin, The Conversation

If you search Google Scholar for the phrase " as an AI language model ," you'll find plenty of AI research literature and also some rather suspicious results. For example, one paper on agricultural technology says,

"As an AI language model, I don't have direct access to current research articles or studies. However, I can provide you with an overview of some recent trends and advancements …"

Obvious gaffes like this aren't the only signs that researchers are increasingly turning to generative AI tools when writing up their research. A recent study examined the frequency of certain words in academic writing (such as "commendable," "meticulously" and "intricate"), and found they became far more common after the launch of ChatGPT—so much so that 1% of all journal articles published in 2023 may have contained AI-generated text.

(Why do AI models overuse these words? There is speculation it's because they are more common in English as spoken in Nigeria, where key elements of model training often occur.)

The aforementioned study also looks at preliminary data from 2024, which indicates that AI writing assistance is only becoming more common. Is this a crisis for modern scholarship, or a boon for academic productivity?

Who should take credit for AI writing?

Many people are worried by the use of AI in academic papers. Indeed, the practice has been described as " contaminating " scholarly literature.

Some argue that using AI output amounts to plagiarism. If your ideas are copy-pasted from ChatGPT, it is questionable whether you really deserve credit for them.

But there are important differences between "plagiarizing" text authored by humans and text authored by AI. Those who plagiarize humans' work receive credit for ideas that ought to have gone to the original author.

By contrast, it is debatable whether AI systems like ChatGPT can have ideas, let alone deserve credit for them. An AI tool is more like your phone's autocomplete function than a human researcher.

The question of bias

Another worry is that AI outputs might be biased in ways that could seep into the scholarly record. Infamously, older language models tended to portray people who are female, black and/or gay in distinctly unflattering ways, compared with people who are male, white and/or straight.

This kind of bias is less pronounced in the current version of ChatGPT.

However, other studies have found a different kind of bias in ChatGPT and other large language models : a tendency to reflect a left-liberal political ideology.

Any such bias could subtly distort scholarly writing produced using these tools.

The hallucination problem

The most serious worry relates to a well-known limitation of generative AI systems: that they often make serious mistakes.

For example, when I asked ChatGPT-4 to generate an ASCII image of a mushroom, it provided me with the following output.

It then confidently told me I could use this image of a "mushroom" for my own purposes.

These kinds of overconfident mistakes have been referred to as "AI hallucinations" and " AI bullshit ." While it is easy to spot that the above ASCII image looks nothing like a mushroom (and quite a bit like a snail), it may be much harder to identify any mistakes ChatGPT makes when surveying scientific literature or describing the state of a philosophical debate.

Unlike (most) humans, AI systems are fundamentally unconcerned with the truth of what they say. If used carelessly, their hallucinations could corrupt the scholarly record.

Should AI-produced text be banned?

One response to the rise of text generators has been to ban them outright. For example, Science—one of the world's most influential academic journals—disallows any use of AI-generated text .

I see two problems with this approach.

The first problem is a practical one: current tools for detecting AI-generated text are highly unreliable. This includes the detector created by ChatGPT's own developers, which was taken offline after it was found to have only a 26% accuracy rate (and a 9% false positive rate ). Humans also make mistakes when assessing whether something was written by AI.

It is also possible to circumvent AI text detectors. Online communities are actively exploring how to prompt ChatGPT in ways that allow the user to evade detection. Human users can also superficially rewrite AI outputs, effectively scrubbing away the traces of AI (like its overuse of the words "commendable," "meticulously" and "intricate").

The second problem is that banning generative AI outright prevents us from realizing these technologies' benefits. Used well, generative AI can boost academic productivity by streamlining the writing process. In this way, it could help further human knowledge. Ideally, we should try to reap these benefits while avoiding the problems.

The problem is poor quality control, not AI

The most serious problem with AI is the risk of introducing unnoticed errors, leading to sloppy scholarship. Instead of banning AI, we should try to ensure that mistaken, implausible or biased claims cannot make it onto the academic record.

After all, humans can also produce writing with serious errors, and mechanisms such as peer review often fail to prevent its publication.

We need to get better at ensuring academic papers are free from serious mistakes, regardless of whether these mistakes are caused by careless use of AI or sloppy human scholarship. Not only is this more achievable than policing AI usage, it will improve the standards of academic research as a whole.

This would be (as ChatGPT might say) a commendable and meticulously intricate solution.

Provided by The Conversation

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Five research topics exploring the science of mental health.

Mental wellbeing is increasingly recognized as an essential aspect of our overall health. It supports our ability to handle challenges, build strong relationships, and live more fulfilling lives. The World Health Organization (WHO) emphasizes the importance of mental health by acknowledging it as a fundamental human right.

This Mental Health Awareness Week, we highlight the remarkable work of scientists driving open research that helps everyone achieve better mental health.

Here are five Research Topics that study themes including how we adapt to a changing world, the impact of loneliness on our wellbeing, and the connection between our diet and mental health.

All articles are openly available to view and download.

1 | Community Series in Mental Health Promotion and Protection, volume II

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There is no health without mental health. Thus, this Research Topic collects ideas and research related to strategies that promote mental health across all disciplines. The goal is to raise awareness about mental health promotion and protection to ensure its incorporation in national mental health policies.

This topic is of relevance given the mental health crisis being experienced across the world right now. A reality that has prompted the WHO to declare that health is a state of complete physical, mental, and social wellbeing.

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176.800 views | 11 articles

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There is a clear consensus that the quality, quantity, and even timing of our human feeding patterns directly impact how brains function. But despite the epidemiological and mechanistic links between mental health and diet-related diseases, these two are often perceived as separate medical issues.

Even more urgent, public health messaging and clinical treatments for mental health conditions place relatively little emphasis on formulating nutrition to ease the underlying drivers of mental health conditions.

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94.000 views | 15 articles

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The definition and understanding of mental health remain to be refined, partially because of a lack of cross-cultural perspectives on mental health. Also, due to the rapid internationalization taking place in the world today, a culturally aware understanding of, and interventions for mental health problems are essential.

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85.000 views | 29 articles

In this Research Topic, scientists study a wider range of variables involved in change and adaptation. They examine changes of any type or magnitude whenever the lack of adaptive response diminishes our development and well-being.

Today’s society is characterized by change, and sometimes, the constant changes are difficult to assimilate. This may be why feelings of frustration and defenselessness appear in the face of the impossibility of responding adequately to the requirements of a changing society.

Therefore, society must develop an updated notion of the processes inherent to changing developmental environments, personal skills, resources, and strategies. This know-how is crucial for achieving and maintaining balanced mental health.

5 | Mental Health Equity

29.900 views | 10 articles

The goal of this Research Topic is to move beyond a synthesis of what is already known about mental health in the context of health equity. Rather, the focus here is on transformative solutions, recommendations, and applied research that have real world implications on policy, practice, and future scholarship.

Attention in the field to upstream factors and the role of social and structural determinants of health in influencing health outcomes, combined with an influx of innovation –particularly the digitalization of healthcare—presents a unique opportunity to solve pressing issues in mental health through a health equity lens.

The topic is opportune because factors such as structural racism and climate change have disproportionately negatively impacted marginalized communities across the world, including Black, Indigenous, People of Color (BIPOC), LGBTQ+, people with disabilities, and transition-age youth and young adults. As a result, existing disparities in mental health have exacerbated.

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Broad Public Support for Legal Abortion Persists 2 Years After Dobbs

By more than 2 to 1, americans say medication abortion should be legal, table of contents.

• Other abortion attitudes
• Overall attitudes about abortion
• Americans’ views on medication abortion in their states
• How statements about abortion resonate with Americans
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand Americans’ views on the legality of abortion, as well as their perceptions of abortion access. For this analysis, we surveyed 8,709 adults from April 8 to 14, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for the report and its methodology .

Nearly two years after the Supreme Court overturned the 1973 Roe v. Wade decision guaranteeing a national right to abortion, a majority of Americans continue to express support for abortion access.

About six-in-ten (63%) say abortion should be legal in all or most cases. This share has grown 4 percentage points since 2021 – the year prior to the 2022 decision in Dobbs v. Jackson Women’s Health Organization that overturned Roe.

The new Pew Research Center survey, conducted April 8-14, 2024, among 8,709 adults, surfaces ongoing – and often partisan – divides over abortion attitudes:

• Democrats and Democratic-leaning independents (85%) overwhelmingly say abortion should be legal in all or most cases, with near unanimous support among liberal Democrats.
• By comparison, Republicans and Republican leaners (41%) are far less likely to say abortion should be legal in all or most cases. However, two-thirds of moderate and liberal Republicans still say it should be.

Since before Roe was overturned, both parties have seen a modest uptick in the share who say abortion should be legal.

As in the past, relatively few Americans (25%) say abortion should be legal in all cases, while even fewer (8%) say it should be illegal in all cases. About two-thirds of Americans do not take an absolutist view: 38% say it should be legal in most cases, and 28% say it should be illegal in most cases.

Related: Americans overwhelmingly say access to IVF is a good thing

Women’s abortion decisions

A narrow majority of Americans (54%) say the statement “the decision about whether to have an abortion should belong solely to the pregnant woman” describes their views extremely or very well. Another 19% say it describes their views somewhat well, and 26% say it does not describe their views well.

Views on an embryo’s rights

About a third of Americans (35%) say the statement “human life begins at conception, so an embryo is a person with rights” describes their views extremely or very well, while 45% say it does not describe their views well.

But many Americans are cross-pressured in their views: 32% of Americans say both statements about women’s decisions and embryos’ rights describe their views at least somewhat well.

Abortion access

About six-in-ten Americans in both parties say getting an abortion in the area where they live would be at least somewhat easy, compared with four-in-ten or fewer who say it would be difficult.

However, U.S. adults are divided over whether getting an abortion should be easier or harder:

• 31% say it should be easier for someone to get an abortion in their area, while 25% say it should be harder. Four-in-ten say the ease of access should be about what it is now.
• 48% of Democrats say that obtaining an abortion should be easier than it is now, while just 15% of Republicans say this. Instead, 40% of Republicans say it should be harder (just 11% of Democrats say this).

As was the case last year, views about abortion access vary widely between those who live in states where abortion is legal and those who live in states where it is not allowed.

For instance, 20% of adults in states where abortion is legal say it would be difficult to get an abortion where they live, but this share rises to 71% among adults in states where abortion is prohibited.

Medication abortion

Americans say medication abortion should be legal rather than illegal by a margin of more than two-to-one (54% vs. 20%). A quarter say they are not sure.

Like opinions on the legality of abortion overall, partisans differ greatly in their views of medication abortion:

• Republicans are closely split but are slightly more likely to say it should be legal (37%) than illegal (32%). Another 30% aren’t sure.
• Democrats (73%) overwhelmingly say medication abortion should be legal. Just 8% say it should be illegal, while 19% are not sure.

Across most other demographic groups, Americans are generally more supportive than not of medication abortion.

Across demographic groups, support for abortion access has changed little since this time last year.

Today, roughly six-in-ten (63%) say abortion should be legal in all (25%) or most (38%) cases. And 36% say it should be illegal in all (8%) or most (28%) cases.

While differences are only modest by gender, other groups vary more widely in their views.

Race and ethnicity

Support for legal abortion is higher among Black (73%) and Asian (76%) adults compared with White (60%) and Hispanic (59%) adults.

Compared with older Americans, adults under 30 are particularly likely to say abortion should be legal: 76% say this, versus about six-in-ten among other age groups.

Those with higher levels of formal education express greater support for legal abortion than those with lower levels of educational attainment.

About two-thirds of Americans with a bachelor’s degree or more education (68%) say abortion should be legal in all or most cases, compared with six-in-ten among those without a degree.

White evangelical Protestants are about three times as likely to say abortion should be illegal (73%) as they are to say it should be legal (25%).

By contrast, majorities of White nonevangelical Protestants (64%), Black Protestants (71%) and Catholics (59%) say abortion should be legal. And religiously unaffiliated Americans are especially likely to say abortion should be legal (86% say this).

Partisanship and ideology

Democrats (85%) are about twice as likely as Republicans (41%) to say abortion should be legal in all or most cases.

But while more conservative Republicans say abortion should be illegal (76%) than legal (27%), the reverse is true for moderate and liberal Republicans (67% say legal, 31% say illegal).

By comparison, a clear majority of conservative and moderate Democrats (76%) say abortion should be legal, with liberal Democrats (96%) overwhelmingly saying this.

Views of abortion access by state

About six-in-ten Americans (58%) say it would be easy for someone to get an abortion in the area where they live, while 39% say it would be difficult.

This marks a slight shift since last year, when 54% said obtaining an abortion would be easy. But Americans are still less likely than before the Dobbs decision to say obtaining an abortion would be easy.

Still, Americans’ views vary widely depending on whether they live in a state that has banned or restricted abortion.

In states that prohibit abortion, Americans are about three times as likely to say it would be difficult to obtain an abortion where they live as they are to say it would be easy (71% vs. 25%). The share saying it would be difficult has risen 19 points since 2019.

In states where abortion is restricted or subject to legal challenges, 51% say it would be difficult to get an abortion where they live. This is similar to the share who said so last year (55%), but higher than the share who said this before the Dobbs decision (38%).

By comparison, just 20% of adults in states where abortion is legal say it would be difficult to get one. This is little changed over the past five years.

Americans’ attitudes about whether it should be easier or harder to get an abortion in the area where they live also varies by geography.

Overall, a decreasing share of Americans say it should be harder to obtain an abortion: 33% said this in 2019, compared with 25% today.

This is particularly true of those in states where abortion is now prohibited or restricted.

In both types of states, the shares of Americans saying it should be easier to obtain an abortion have risen 12 points since before Roe was overturned, as the shares saying it should be harder have gradually declined.

By comparison, changes in views among those living in states where abortion is legal have been more modest.

While Americans overall are more supportive than not of medication abortion (54% say it should be legal, 20% say illegal), there are modest differences in support across groups:

• Younger Americans are somewhat more likely to say medication abortion should be legal than older Americans. While 59% of adults ages 18 to 49 say it should be legal, 48% of those 50 and older say the same.
• Asian adults (66%) are particularly likely to say medication abortion should be legal compared with White (55%), Black (51%) and Hispanic (47%) adults.
• White evangelical Protestants oppose medication abortion by about two-to-one (45% vs. 23%), with White nonevangelicals, Black Protestants, Catholics and religiously unaffiliated adults all being more likely than not to say medication abortion should be legal.
• Republicans are closely divided over medication abortion: 37% say it should be legal while 32% say it should be illegal. But similar to views on abortion access overall, conservative Republicans are more opposed (43% illegal, 27% legal), while moderate and liberals are more supportive (55% legal, 14% illegal).

Just over half of Americans (54%) say “the decision about whether to have an abortion should belong solely to the pregnant woman” describes their views extremely or very well, compared with 19% who say somewhat well and 26% who say not too or not at all well.

Democrats (76%) overwhelmingly say this statement describes their views extremely or very well, with just 8% saying it does not describe their views well.

Republicans are more divided: 44% say it does not describe their views well while 33% say it describes them extremely or very well. Another 22% say it describes them somewhat well.

Fewer Americans (35%) say the statement “human life begins at conception, so an embryo is a person with rights” describes their views extremely or very well. Another 19% say it describes their views somewhat well while 45% say it describes them not too or not at all well.

(The survey asks separately whether “a fetus is a person with rights.” The results are roughly similar: 37% say that statement describes their views extremely or very well.)

Republicans are about three times as likely as Democrats to say “an embryo is a person with rights” describes their views extremely or very well (53% vs. 18%). In turn, Democrats (66%) are far more likely than Republicans (25%) to say it describes their views not too or not at all well.

Some Americans are cross-pressured about abortion

When results on the two statements are combined, 41% of Americans say the statement about a pregnant woman’s right to choose describes their views at least somewhat well , but not the statement about an embryo being a person with rights. About two-in-ten (21%) say the reverse.

But for nearly a third of U.S. adults (32%), both statements describe their views at least somewhat well.

Just 4% of Americans say neither statement describes their views well.

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