Enseignements universitaires francophones en milieux bi / plurilingues : légitimations et mises en œuvre
Bibliographic record
Abstract
Le dossier thématique de ce numéro, issu des travaux de l’axe Éducation et Plurilinguismes : mises en perspective historiques et sociales du projet régional Pluri-L1 de la région des Pays de la Loire, est consacré à diverses légitimations et mises en œuvre d’enseignements universitaires francophones en milieux bi / plurilingues. À ce titre, nous souhaitons apporter des éclairages variés, tenant compte du statut des langues en présence, au sujet du développement d’une compétence bi / plurilingue à l’université, que ce soit du point de vue des acteurs concernés, des dispositifs conçus ou des difficultés rencontrées au moment de la réalisation. Une partie varia comprend deux études qui concernent l’une le niveau primaire et l’autre le niveau secondaire.
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 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".