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Record W4242926457 · doi:10.31234/osf.io/tjxar

Are Figurative Interpretations of Idioms Directly Retrieved, Compositionally Built, or Both? Evidence from Eye Movement Measures of Reading

2019· preprint· en· W4242926457 on OpenAlexaff
Debra Titone, Kyle Lovseth, Kristina Kasparian, Mehrgol Tiv

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsMcGill UniversityCentre for Research on Brain Language and Music
Fundersnot available
KeywordsLiteral and figurative languageComprehensionLinguisticsLiteral (mathematical logic)Interpretation (philosophy)Reading (process)Computer scienceMeaning (existential)Eye movementEye trackingReading comprehensionSemantics (computer science)Point (geometry)Natural language processingArtificial intelligencePsychology

Abstract

fetched live from OpenAlex

Idioms are part of a general class of multiword expressions where the overall interpretation cannot befully determined through a simple syntactic and semantic (i.e., compositional) analysis of theircomponent words (e.g., kick the bucket, save your skin). Idioms are thus simultaneously amenable todirect retrieval from memory, and to an on-demand compositional analysis, yet it is unclear whichprocesses lead to figurative interpretations of idioms during comprehension. In this eye-tracking study,healthy adults read sentences in their native language that contained idioms, which were followed byfigurative- or literal-biased disambiguating sentential information. The results showed that the earlieststages of comprehension are driven by direct retrieval of idiomatic forms, however, later stages ofcomprehension, after which point the intended meaning of an idiom is known, are driven by both directretrieval and compositional processing. Of note, at later stages, increased idiom decomposabilityslowed reading time, suggesting more effortful figurative comprehension. Together, these results aremost consistent with multi-determined or hybrid models of idiom processing.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.079
GPT teacher head0.357
Teacher spread0.277 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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