De la phraséologie à la traductologie proactive : essai de synthèse des fondements théoriques sous-tendant la recherche en phraséologie
Bibliographic record
Abstract
Le présent article a pour but d’évaluer l’apport possible de la phraséologie à la traductologie. A l’heure actuelle, malgré le nombre croissant de travaux consacrés à la phraséologie, la plupart des découvertes ne semblent pas encore avoir trouvé d’écho dans le domaine de la traduction, notamment sur le plan théorique général. En effet, la phraséologie est souvent présentée davantage comme un domaine applicatif que comme un domaine de recherche fondamentale. Cet article montre toutefois que non seulement la phraséologie est en mesure d’apporter des réponses à certains problèmes de traduction, mais aussi qu’elle doit cette capacité aux fondements mêmes qui sous-tendent toute approche phraséologique de la langue. L’article présente ainsi une vision d’ensemble des postulats sur lesquels repose la recherche en phraséologie en revisitant certains concepts fondamentaux et communs à ces deux disciplines.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.012 | 0.025 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".