Bibliographic record
Abstract
Cet article se propose de décrire le travail de retraduction à la lumière des premières traductions du poème le plus connu d’Adrienne Rich, « Diving into the Wreck ». Ce texte emblématique de l’engagement féministe de la poétesse a fait l’objet de deux traductions en français. Afin d’illustrer le processus de retraduction, nous analyserons le poème, les habitus des traducteurs, et leurs traductions. Nous verrons ainsi que ces dernières, en tant que traductions-introductions, contiennent ce qu’Antoine Berman nomme des « tendances déformantes », inclinant la traduction à s’éloigner de la dynamique de l’original. Nous esquisserons ensuite une nouvelle traduction afin de déterminer des stratégies qui peuvent être mises en place en retraduction, au sujet notamment des enjeux principaux du poème : le niveau de langue, la concrétude du style et le traitement du genre grammatical.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 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; both teacher heads agree on what is shown here.
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".