L’éducation interculturelle bilingue : opportunités, enjeux et défis autour de la revitalisation des langues autochtones au Nunavut et dans les Andes péruviennes
Bibliographic record
Abstract
Cet article discute de la manière dont la mise en place d’une éducation bilingue et interculturelle permet de préserver et de revitaliser les langues autochtones à l’échelle mondiale. De nombreux pays d’Amérique latine, dont le Pérou, ont fait de l’éducation interculturelle bilingue (EIB) un droit pour les populations des communautés paysannes et autochtones depuis la fin des années 1970. Au Canada, le gouvernement du Nunavut avait annoncé la volonté de rendre toutes les écoles du territoire bilingues pour 2020. Il expose les avantages et les bénéfices d’un enseignement interculturel bilingue, mais également, il met en évidence les défis et les problèmes récurrents auxquels font face les professeurs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".