MétaCan
Menu
Back to cohort

French‐learning toddlers use gender information on determiners during word recognition

2009· article· en· W2167353027 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

VenueDevelopmental Science · 2009
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of TorontoUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyGrammatical genderNounAffect (linguistics)Word (group theory)Word learningGrammatical categoryLinguisticsDevelopmental psychologyCognitive psychologyCommunication

Abstract

fetched live from OpenAlex

In gender-marking languages, the gender of the noun determines the form of the preceding article. In this study, we examined whether French-learning toddlers use gender-marking information on determiners to recognize words. In a split-screen preferential looking experiment, 25-month-olds were presented with picture pairs that referred to nouns with either the same or different genders. The target word in the auditory instruction was preceded either by the correct or incorrect gender-marked definite article. Toddlers' looking times to target shortly after article onset demonstrated that target words were processed most efficiently in different-gender grammatical trials. While target processing in same-gender grammatical trials recovered in the subsequent time window, ungrammatical articles continued to affect processing efficiency until much later in the trial. These results indicate that by 25 months of age, French-learning toddlers use gender information on determiners when comprehending subsequent nouns.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.033
GPT teacher head0.274
Teacher spread0.241 · 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