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Record W4392058452 · doi:10.1037/xlm0001327

On the nature of action–sentence compatibility effects.

2024· article· en· W4392058452 on OpenAlexafffund
Morgan Teskey, Kristofer Svendsen, Daniel N. Bub, Michael E. J. Masson

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2024
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCompatibility (geochemistry)SentenceEmbodied cognitionComprehensionComputer scienceCognitive psychologyPsychologySentence processingNatural language processingArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Strong versions of the embodied account of language processing propose that comprehension depends on the mental simulation of sensorimotor experiences conveyed by linguistic meaning. Primary support in favor of this view is based on demonstrations of processing advantages for compatibility between an action implied by sentence content and concurrent sensorimotor processing. Although these effects have been reported across a variety of contexts, various attempts to reproduce these results, both through direct replication and conceptual extension, have not been successful. We present a series of experiments that examine the viability of previous methods used to obtain compatibility effects and the validity of the typical interpretation of such effects as evidence for mental simulation of described actions. Our findings add to the growing body of evidence that compatibility between sentence content and sensorimotor processing does not produce robust compatibility effects. Further, our findings suggest the data obtained from some studies that have been successful in generating compatibility effects can be accounted for without appealing to the notion that these effects are due to the simulation of actions implied by the meaning of a sentence. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.393
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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