Lexplication de lerreur en didactique de la traduction erreur dans le processus ou erreur dans le produit
Bibliographic record
Abstract
Introduction Linfluence emotionnelle et psychologique sur les etudiants quemanifeste lexplication de lerreur en traduction rend ce sujet tres importanta etudier en didactique de la traduction Methode cet article presenteune recherche exploratoire sur ce sujet subjective mais incluant le facteurquantitatif par lanalyse comparative des entretiens semi structures appliques adeux groupes denseignants de traduction qui appartiennent a deux universitesdistinctes lune au Canada lautre en Colombie Resultats cette recherche a misen evidence limportance de reconnaitre le processus de traduction des etudiantsafin dexpliquer leurs erreurs et linfluence du contexte academique et globaldu pays sur la didactique developpee par les enseignants etudies Discussion ces resultats ont ete mis en perspective concernant les conditions materiellesde lenseignement differentes pour chaque groupe Des hypotheses et desrecommandations didactiques sont proposees en fin darticle
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".