MétaCan
Menu
Back to cohort

Les discussions lexicales en contexte d’oral réflexif : un moyen de réduire les disparités entre les élèves à risque et leurs pairs ?

2024· article· fr· W4404272813 on OpenAlexaff
Claudine Sauvageau, Dominic Anctil

Bibliographic record

VenueEspaces Linguistiques · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Dans une perspective préventive visant à réduire les disparités lexicales entre élèves du primaire, nous avons mené une étude basée sur l’enseignement direct du vocabulaire (explication par l’enseignante de mots rencontrés en lecture, suivie d’activités de consolidation). Notre démarche méthodologique visait à comparer les apprentissages lexicaux des élèves selon diverses variables (approche de consolidation des mots, profil des élèves, type d’étayage fourni par l’enseignante). Nos résultats, issus de données quantitatives (pré/posttests) et qualitatives (journaux de bord, entretiens, vidéos) démontrent qu’une approche de consolidation des mots en oral réflexif se révèle significativement favorable en ce qui a trait à la capacité des élèves, indépendamment de leur profil, à rappeler à l’oral le sens des mots ciblés ainsi qu’à récupérer en mémoire leur forme orale. Ils ne permettent toutefois pas de conclure que l’étayage soutenu offert aux élèves à risque a contribué à réduire l’écart lexical entre ceux-ci et leurs pairs non à risque.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.061
GPT teacher head0.344
Teacher spread0.283 · 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.

Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEspaces LinguistiquesSame topicLinguistics and Discourse AnalysisFrench-language works237,207