Le vernaculaire noir américain : Ses enjeux pour la traduction envisagés à travers deux oeuvres d’écrivaines noires, Zora Neale Hurston et Alice Walker
Bibliographic record
Abstract
Le vernaculaire noir américain : Ses enjeux pour la traduction envisagés à travers deux oeuvres d'écrivaines noires, Zora Neale Hurston et Alice Walker - Zora Neale Hurston et Alice Walker font usage dans leurs oeuvres d'une langue autre, d'un sociolecte longtemps dénigré, le vernaculaire noir américain. Cette utilisation va bien au-delà de la simple caractérisation sociale de leurs personnages et constitue un geste contestataire, une revendication et une célébration. Dans ces conditions, la traduction annexionniste qui consisterait à avoir recours à des sociolectes effaçant totalement la négritude et la problématique raciale, tel le langage « paysan », apparaît comme une véritable mutilation des oeuvres. Il convient donc d'opérer le décentrement du texte-cible en y inscrivant la négritude. Les divers créoles à base française et les variétés du français parlées en Afrique noire peuvent fournir des marqueurs qui, sans relocaliser abusivement le texte-cible, serviront à cette fin.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".