Bibliographic record
Abstract
Le discours sur la traduction est complexe et parsemé d’embuches, particulièrement lorsqu’il est question de la notion de fidélité à l’original, donc de vérité. Est-elle « fidèle » ou « trompeuse », « véridique » ou « vérité alternative », pour employer un euphémisme à la mode ? Cet article remet en question certains énoncés prescriptifs concernant la Septante ainsi que la manière dont le concept d’équivalence est employé. À la lumière des avancées récentes dans le domaine de la traductologie, il propose un regard descriptif sur la traduction, avec, comme étude de cas, la loi du lévirat en Deutéronome 25,5-6. Sans mettre de côté complètement la notion de fidélité, il devient apparent que celle-ci doit être relativisée et contextualisée, particulièrement lorsque l’objectif est de mieux comprendre son contexte de production.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".