Bibliographic record
Abstract
Le problème de la traduction des sociolectes demeure « […] one of the biggest lacunae in translation studies » (Herrera 2014 : 290). Dans ce qui suit, j’espère contribuer à la discussion entamée par Brodsky (1993, 1996), Lavoie (1994, 2002) et d’autres sur la traduction du vernaculaire noir américain (VNA) en examinant le cas de deux romans autobiographiques de Maya Angelou, I Know Why the Caged Bird Sings (1969) et The Heart of a Woman (1981), et le bestseller de Lawrence Hill, The Book of Negroes (2007). Il s’avère que le rôle du Black English dans ces romans dépasse celui de la simple « couleur locale ». Comment les traducteurs Besse (2008), Saint-Martin et Gagné (2008), et Noël (2011/2014), les traducteurs des romans précédemment cités, ont-ils négocié la tension entre fidélité à la langue source et fidélité à la langue cible ? Il ressort de cette étude qu’une plus grande volonté de dévier des normes et des formes du français permettrait de mieux « traduire » ce parler noir dans le but d’en préserver la valeur culturelle et idéologique.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".