« Traduire à l’oreille » : vers une poétique de la « musicaméricanité » chez Michel Tremblay
Bibliographic record
Abstract
S’il ne fait aucun doute que les toutes premieres « adaptations » de Michel Trembley furent marquees par une visee ethnocentriste, l’on ne peut en dire de meme de sa traduction d’ Oncle Vania ni de toutes celles qui suivirent. Les traductions (et adaptations) de Tremblay gagneraient d’ailleurs a etre envisagees a la lumiere d’une reflexion nourrit simultanement par les notions d’americanite et de musicalite. Nous procederons a l’analyse comparee des traductions d’ Orpheus Descending de Tennessee Williams, signees par Raymond Rouleau et Michel Tremblay, a l’aide de ces concepts entendus comme postulats traductologiques. Nous croyons ainsi pouvoir ouvrir de nouvelles perspectives, a la fois ethiques et esthetiques, sur l’œuvre de l’auteur quebecois en general et sur ses traductions en particulier. Loin d’etre exogenes ces notions, qui resident au cœur meme du projet litteraire tremblayen, concourent a lui conferer une veritable unite (poetique) sans pour cela laisser en reste la traduction.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".