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Syntactic Categorization in French‐Learning Infants

2010· article· en· W1944583518 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInfancy · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCategorizationNounVerbLinguisticsPsychologyDeterminerSubject (documents)Grammatical categoryProper nounClass (philosophy)Artificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Recent work showed that infants recognize and store function words starting from the age of 6-8 months. Using a visual fixation procedure, the present study tested whether French-learning 14-month-olds have the knowledge of syntactic categories of determiners and pronouns, respectively, and whether they can use these function words for categorizing novel words to nouns and verbs. The prosodic characteristics of novel words stimuli for noun versus verb uses were balanced. The only distinguishing cue was the preceding determiners versus subject pronouns, the former being the most common for nouns and the latter the most common for verbs, i.e., Det + Noun, Pron + Verb. We expected that noun categorization may be easier than verb categorization because the co-occurrence of determiners with nouns is more consistent than that of subject pronouns with verbs in French. The results showed that infants grouped the individual determiners as one common class, and that they appeared to use the determiners to categorize novel words into nouns. However, we found no evidence of verb categorization. Unlike determiners, pronouns were not perceived as a common syntactic class.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.996

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)0.0040.001

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 head0.007
GPT teacher head0.284
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