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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".