La formation des enseignants sur la diversité et les rapports ethniques : regard comparatif France, Québec, Belgique et Suisse
Bibliographic record
Abstract
La formation et l’évaluation des compétences des enseignants pour agir en contexte de diversité interpellent autant les décideurs gouvernementaux que les milieux universitaires et scolaires. Cet article porte un regard comparatif transversal sur la formation du personnel scolaire en matière de diversité, d’équité et des rapports ethniques en éducation en France, au Québec, en Belgique francophone et en Suisse, notamment dans les politiques, référentiels de compétences, dispositifs, programmes, cours et contenus de formation. Ce regard comparatif sur quatre sociétés de la francophonie montre que chaque contexte a développé un discours, des orientations et des dispositifs de formation assez différents sur ces questions, mais quand même réunis par certaines lignes de convergence.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".