L’interculturel à l’épreuve de l’action : comment équiper les enseignants face au public scolaire hétérogène ?
Bibliographic record
Abstract
Cet article traite de la notion d’interculturel dans le domaine de l’éducation. Il soulève la question d’un agir enseignant qui peut se trouver pris dans la tension entre une volonté de reconnaissance de la diversité culturelle et les effets des stéréotypes produits par la catégorisation des acteurs. Dans cette réflexion, nous soulignons l’importance de développer un regard pluriel sur les pratiques éducatives dans le but d’identifier les mécanismes d’interaction qui maintiennent, voire renforcent les frontières entre les groupes, notamment dans les contextes marqués par une configuration majorité/minorité caractéristique des rapports entre populations « autochtones » et celles issues de la migration. L’apport de la sociologie de l’éducation, de l’anthropologie sociale et culturelle et de la psychologie sociale est indispensable pour offrir aux enseignants une formation solide à l’éducation interculturelle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".