Un dictionnaire de reformulation pour les apprenants du français langue seconde
Bibliographic record
Abstract
Nous présentons une recherche en lexicologie appliquée à l’enseignement du français langue seconde qui vise le développement d’un dictionnaire électronique de type particulier, appelé dictionnaire de reformulation . Ce dictionnaire devrait permettre aux étudiants de niveau intermédiaire à ceux de niveau avancé de surmonter des difficultés que présente une utilisation souple et idiomatique du lexique du français dans la production langagière. Les questions abordées sont les suivantes : les fondements théoriques et la méthodologie pour l’élaboration d’un tel dictionnaire, le concept d’erreur lexicale et la description des erreurs lexicales à l’aide d’outils formels que nous proposons, l’architecture du dictionnaire de reformulation et l’implémentation de ce dernier. Le cadre théorique dans lequel se situe notre recherche est celui de la théorie linguistique Sens-Texte.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".