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Record W2093898508 · doi:10.1515/langcog.2009.006

Episodic affordances contribute to language comprehension

2009· article· en· W2093898508 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage and Cognition · 2009
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsComprehensionAffordanceComputer scienceCompatibility (geochemistry)GermanLinguisticsNatural language processingArtificial intelligenceHuman–computer interactionEngineeringProgramming language

Abstract

fetched live from OpenAlex

Abstract We demonstrate how a particular type of knowledge about objects, their spatial locations and thus how to direct actions toward them, contributes to the comprehension of language about those objects. In four experiments, participants judged if sentences were about normal objects (e.g., “The apple has a stem”) or odd objects (e.g., “The apple has an antenna”). The Normal response key was either on the left of a response box or on the right. The named objects were themselves either on the left or the right of the response box. We demonstrate a compatibility effect in which responding Normal to the side where the object was located was faster than responding Normal to the opposite side. Furthermore, this effect was equally strong for sentences describing states of the objects (as above) and sentences describing actions (e.g., “Touch the apple at the stem”); the compatibility effect was found when the objects were removed; the effect required compatibility between actions, not just spatial locations; and the effect was found in both English and German. The results are discussed in relation to how action systems are used in language comprehension.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.291
Teacher spread0.279 · 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