Qualité et préparation de l’interprétation. Évolution des modes de préparation et rôle de l’Internet
Bibliographic record
Abstract
Pour l’interprète, la préparation est un travail d’une importance capitale destiné à assurer la qualité de l’interprétation. La durée de la préparation, qui varie en fonction de l’expérience des interprètes, dépend du degré de difficulté du thème traité et du délai dans lequel la demande d’interprétation a été formulée. Dans le présent article, nous observerons l’objet et les moyens de préparation, les variantes qui influencent la phase de préparation et les méthodes qui en découlent au fil du temps. Nous examinerons en particulier l’importance de l’utilisation de l’internet lors de la préparation, les domaines sur lesquels il convient de mettre l’accent et les moyens de gérer chaque cas, toutes choses qu’il convient de prendre en compte dans la formation des interprètes.
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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 | 0.031 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".