L’EXCLUSION LANGAGIÈRE DANS LES CLASSES SUPERDIVERSES EN OUTRE-MER FRANÇAIS : SILENCES, MAILLAGES ET PERSPECTIVE INCLUSIVE DANS L’OCÉAN INDIEN
Bibliographic record
Abstract
La présente contribution a pour objectif de mieux comprendre la façon dont la place des langues se négocie dans les classes superdiverses des départements français ultramarins en vue de penser autrement les politiques éducatives inclusives. Après avoir mis en perspective le concept de translanguaging avec l’interlecte et le mélangue créole, nous analyserons, en nous appuyant sur la métaphore du rhizome, les interactions verbales en classe de petite section où sont expérimentées des séances dites d’ « éveil aux langues ». L’étude permet d’identifier plusieurs stratégies d’interactions plurilingues. Les résultats montrent notamment comment s’appuyer sur le langage intérieur des élèves. En distinguant les stratégies compensatoires trahissant une vision « langue-problème » (VLP) de celles à visée de transformation sociale (VTS), nous espérons ainsi mettre en lumière les idéologies qui conditionnent l’inclusion langagière des élèves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".