Enseigner en contextes minoritaires de diversité ethnoculturelle : essai de conceptualisation pour une approche de formation centrée sur l’agir enseignant
Bibliographic record
Abstract
Cet article se penche sur les difficultés à prendre en compte la diversité ethnolinguistique dans l’enseignement du français en contexte minoritaire canadien. En se concentrant sur la formation des enseignants en Ontario et en Colombie-Britannique, nous observons que, malgré les variations dans le temps alloué, les programmes de formation privilégient souvent les compétences pédagogiques avec un prisme monolingue. Cette focalisation se fait au détriment d’une compréhension plus approfondie des rapports aux langues et des ressources plurilingues des élèves. S’appuyant sur le multi-agenda de Bucheton et Soulé (2009) et les approches plurielles (Candelier, 2003), nous proposons un modèle de formation des enseignants centré sur l’agir enseignant, intégrant explicitement la diversité comme un aspect fondamental de la pratique afin d’éviter l’instrumentalisation des langues et des cultures des élèves.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.060 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".