Insécurité linguistique chez les enseignants non natifs de FLE : le cas des Colombiens
Bibliographic record
Abstract
Cet article s'intresse la notion d'inscurit linguistique dans les processus d'enseignement des langues trangres, notamment celle ressentie par les enseignants de franais non natifs en Colombie. Nous allons donc analyser les possibles raisons pour lesquelles les professeurs de franais langue trangre (FLE) colombiens ressentent cette inscurit, tout en abordant la notion et la reprsentation que se font ces enseignants du locuteur natif / non natif, ainsi que celles de langue maternelle ou premire (LM/L1), qui en sont trs proches. Nous prsenterons galement le statut et la place de la langue franaise en Colombie, avant d'voquer le rle jou par la formation des professeurs de FLE assure dans les universits colombiennes. Enfin, nous prsenterons quelques propositions pour tenter de remdier ce sentiment d'inscurit, et amliorer ainsi non seulement la qualit de la formation et du travail des professeurs de FLE, mais aussi leur vie en gnral.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".