Ajoutée, intégrée ou empêchée : quelle place pour la prise en compte de la diversité culturelle en classe ?
Bibliographic record
Abstract
Ajoute, intgre ou empche : quelle place pour la prise en compte de la diversit culturelle en classe ? Formation et profession 30(1) 2022 1 sum L' objectif de cet article est de comprendre les pratiques que les enseignantes dveloppent pour rpondre l'impratif de prise en compte de l'altrit. Quatorze entretiens avec des enseignantes ont t raliss puis traits suivant la logique de l'analyse de contenu. Les rsultats montrent un croisement entre des pratiques ajoutes, intgres, mais aussi empches. L'analyse met en vidence une surreprsentation des objectifs interrelationnels par rapport au traitement d' enjeux relatifs aux injustices, et une intgration des approches interculturelles dans les pratiques enseignantes. Enfin, les rsultats mettent en vidence le besoin de formation des enseignants dans le domaine des approches interculturelles.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".