Contextualiser l'éducation en milieux plurilingues et pluriculturels / Contextualising Education in Plurilingual and Pluricultural Environments
Bibliographic record
Abstract
Le plurilinguisme et le pluriculturalisme sont devenus des enjeux importants du XXIe siècle, et la contextualisation de l'apprentissage destinée à répondre aux besoins des environnements concernés par ces problématiques a pris un certain retard. Ce livre présente les résultats de recherches de terrain menées sous des angles multiples, dans et sur ces environnements. Il aborde différents aspects du plurilinguisme et de l'éducation, d'un point de vue linguistique, social et pédagogique. Selon une vision écosystémique de la contextualisation de l'éducation dans les sociétés plurilingues et pluriculturelles, l’ouvrage examine différentes démarches de contextualisations de l’enseignement en lien avec le rôle des langues, les relations des parents et des apprenants avec l'école, ainsi que d'autres phénomènes sociaux spécifiques aux environnements étudiés.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".