Crise du dicible. Euphémismes et détournements du visage dans "Une saison de machettes" de Jean Hatzfeld
Bibliographic record
Abstract
Après avoir écouté les témoignages de survivants tutsis (Dans le nu de la vie, 2000), l’écrivain et journaliste français Jean Hatzfeld a renversé la perspective en recueillant les récits de génocidaires hutus, avec la publication d’Une saison de machettes (2003). Cet article montre comment les récits des bourreaux sont empreints d’indicible, étant marqués par une démarche discursive calculée et réifiante, qui vise plus à taire qu’à dire en détournant et en orientant l’acte narratif. L’expérience de l’événement y est réduite à sa dimension factuelle, évacuant par l’occasion toute subjectivation. Une telle posture rhétorique, parfois très directe et très crue, mais surtout empreinte d’euphémismes et de détournements, contribue à dépersonnaliser les bourreaux, donc à normaliser l’extrême violence et à occulter le visage tutsi.
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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 | 0.003 |
| 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 | 0.020 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".