De je à toi, une question inter-subjective de la traduction. Réflexion à partir de la traduction de Peau noire, masques blancs de Frantz Fanon
Bibliographic record
Abstract
Partant d’une tendance à uniformiser les sujets nous et je constatée dans la traduction anglaise de Peau noire, masques blancs de Frantz Fanon, le présent article réfléchit sur la traduction de différentes subjectivités. Appuyé par les deux traductions existantes en anglais qui soulèvent des problèmes communs, notre questionnement est surtout basé sur notre propre exercice de la traduction du même ouvrage vers la langue chinoise. Comment démêler les nombreuses présences de je qui mettent en voix et en mouvement des corps et des expériences? Comment restituer l’écriture poétique performative? Ces questions nous conduisent vers une interrogation sur la relation avec l’autre qui est au centre de la pensée de Fanon et essentielle pour toute réflexion sur 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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.061 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| 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".