Déviations lexicales de forme et de sens chez les apprenants de français langue étrangère
Bibliographic record
Abstract
A l’issue d’une étude empirique, cet article traite d’un type particulier d’erreurs dans l’acquisition du vocabulaire en français langue étrangère : la confusion lexicale intralinguale. 480 sujets anglophones et hellénophones de niveaux débutant, intermédiaire et avancé ont participé à une tâche de traduction de mots français, vers leur L1, l’anglais ou le grec. Une grande proportion des erreurs obtenues a révélé des confusions occasionnées par la similarité de forme et/ou de sens des mots cibles avec d’autres mots français connus par les apprenants. L’examen du rapport formel et/ou sémantique entre le mot erroné et le mot cible a permis une description plus nuancée de la confusion lexicale intranlinguale mettant ainsi en évidence des sous-catégories précises de ce que nous appellerons “les confusibles lexicaux”.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".