Une approche linguistique vers l’égalité des genres/sexes grâce à la traduction féministe et l’exercice de réécriture : Le désert mauve de Nicole Brossard
Bibliographic record
Abstract
La traduction litteraire represente beaucoup plus que le transfert linguistique d’un mot a un autre. Dans les annees 1960 et 1970, au cours de la seconde vague de feminisme, au Quebec et au Canada, la traduction devint un outil de revendication pour les traductrices feministes, grandement inspirees par la theorie de la differance et du deconstructionnisme de Jacques Derrida. Nicole Brossard est consideree comme une pionniere de la traduction feministe. Le desert mauve, son roman le plus connu, met en scene un exercice de traduction intralinguale effectue par une traductrice fictive. Cet exercice de reecriture agira en tant que strategie feministe et traductologique, au meme titre que les strategies feministes de traduction interlinguale, afin de demontrer l’aspect « organique » de certaines experiences exclusivement feminines mises en lumiere par les protagonistes du recit.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".