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Record W4414695825 · doi:10.26443/mje/rsem.v59i2.9996

L’évaluation des habiletés langagières d’enfants francophones d’âge préscolaire : comparaison de l’anecdote personnelle et de la conversation lors d’un jeu symbolique

2025· article· fr· W4414695825 on OpenAlexaffvenueabout
Marianne Paul, Noémie Mercier, Stéphanie Girard, Stefano Rezzonico

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité de MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAnecdoteNarrativeContext (archaeology)ConversationIdentity (music)

Abstract

fetched live from OpenAlex

Le but de cet article est d’explorer le développement des habiletés langagières en comparant la performance lors d’une anecdote personnelle à celle de 25 énoncés en conversation lors d’un jeu symbolique. Des 28 enfants franco-québécois unilingues évalués à 3 ans, 19 ont également été évalués à 4 ans. La longueur moyenne des énoncés et la diversité lexicale des échantillons ont été calculées et le stade narratif de l’anecdote a été déterminé. Les résultats montrent un impact du contexte discursif sur les caractéristiques de l’échantillon. La longueur moyenne des énoncés est statistiquement plus élevée en narration à 3 ans seulement. Utiliser l’anecdote personnelle pour évaluer le langage d’enfants de 3 ans est envisageable, malgré une évolution très variable du stade narratif.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.201
GPT teacher head0.460
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueMcGill Journal of Education / Revue des sciences de l éducation de McGillSame topicFrench Language Learning MethodsFrench-language works237,207