Regard sur le cosmopolitisme éducatif pour la formation des futurs enseignants en milieu minoritaire francophone
Bibliographic record
Abstract
Résumé Cet article porte un regard sur l’usage des fondements de l’éducation cosmopolite comme approche potentielle pour préparer les futurs enseignants à œuvrer en milieu minoritaire francophone. Par un bref survol de la discrimination culturelle que l’école francophone peut perpétrer, l’article propose une nouvelle approche de formation qui est spécifique au milieu minoritaire. Selon sa conceptualisation renouvelée, le cosmopolitisme éducatif pourrait répondre aux besoins spécifiques du milieu maintenant fortement influencé par la diversité culturelle. À travers cet article, une réflexion relative aux pratiques de formation des enseignants dans le milieu universitaire francophone est amorcée. Abstract This article builds on the foundations of cosmopolitan education as a potential approach to prepare future teachers working in a francophone community outside Québec. By a brief overview of the cultural discrimination at play in francophone schools, the article suggests the need to find a teacher training approach specific to the needs of the French minority setting. In its renewed understanding, educational cosmopolitanism could answer the specific needs of that community, one deeply altered by the transformations associated with the increasing cultural diversity in schools. Through this article, a larger reflection about the preparation of future teachers in francophone settings outside Québec is initiated.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".