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Toddlers Use the Number Feature in Determiners During Online Noun Comprehension

2012· article· en· W2146370438 on OpenAlexaff
Erin K. Robertson, Rushen Shi, Andréane Melançon

Bibliographic record

VenueChild Development · 2012
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversité du Québec à MontréalCape Breton University
Fundersnot available
KeywordsDeterminerComprehensionPsychologyNounFeature (linguistics)Object (grammar)LinguisticsCognitive psychology

Abstract

fetched live from OpenAlex

Function words support many aspects of language acquisition. This study investigated whether toddlers understand the number feature of determiners and use it for noun comprehension. French offers an ideal "test case" as number is phonetically marked in determiners but not in nouns. Twenty French-learning 24-month-olds completed a split-screen experiment. Looking times to target pictures were measured under 3 trial types varying in the degree to which the determiner matched the number displayed in the object(s). Children looked longer when the determiner matched the object(s), and were confused in trials of clear mismatch. Importantly, their processing resembled that of French adults (D. Dahan, D. Swingley, M. K. Tanenhaus, & J. S. Magnuson, 2000). Thus, children understand the determiner number feature early in acquisition and use this knowledge to constrain online 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.

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 score0.189
Threshold uncertainty score0.751

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)0.0000.001

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 head0.028
GPT teacher head0.299
Teacher spread0.271 · 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

Citations15
Published2012
Admission routes1
Has abstractyes

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