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Record W4226349037 · doi:10.1371/journal.pone.0267297

Children’s and adults’ use of fictional discourse and semantic knowledge for prediction in language processing

2022· article· en· W4226349037 on OpenAlexafffund
Ruth Lee, Craig G. Chambers, Falk Huettig, Patricia A. Ganea

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsInterpretation (philosophy)Context (archaeology)Privilege (computing)SalientSemantic memorySemantics (computer science)PsychologyMoment (physics)LinguisticsCognitive psychologyComputer scienceNatural language processingArtificial intelligenceCognitionHistory

Abstract

fetched live from OpenAlex

Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of real-world events to influence the moment-by-moment interpretation of a story by 7-year-old children and adults. Seven-year-olds were less effective at bypassing stored real-world knowledge during real-time interpretation than adults. Our results suggest that children privilege stored semantic knowledge over situation-specific information presented in a fictional story context. We suggest that 7-year-olds' canonical semantic and conceptual relations are sufficiently strongly rooted in statistical patterns in language that have consolidated over time that they overwhelm new and unexpected information even when the latter is fantastical and highly salient.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.251

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)0.0000.000

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 head0.033
GPT teacher head0.283
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2022
Admission routes2
Has abstractyes

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