Place des enjeux d’acquisition langagière dans le multi-agenda de l’enseignant de DdNL : l’exemple d’un cours d’histoire pour collégiens allophones
Bibliographic record
Abstract
Notre contribution étudie, du point de vue de son potentiel acquisitionnel, un cours d’histoire pour élèves allophones en collège. En analysant les séquences métalinguistiques de focalisation lexicale qui jalonnent ce corpus, nous montrons comment, par la conduite des échanges, se construisent et s’articulent les dimensions disciplinaires et linguistiques de l’apprentissage, dans un contexte de communication asymétrique (du point de vue des connaissances en histoire, de la maîtrise de la langue de l’échange, de la familiarité avec l’institution scolaire). Nous nous demandons quels liens de concurrence ou d’étayage se tissent entre les objectifs langagiers et disciplinaires, puis nous resituons la question de la potentialité acquisitionnelle des échanges dans l’ensemble des préoccupations et contraintes qui sous-tendent la conduite de l’interaction didactique par l’enseignant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".