Nina Bouraoui, martyr(s) de l’écho : de la blessure à une nouvelle sexualité par l’affect
Bibliographic record
Abstract
Analysant les romans de Nina Bouraoui, en particulier Mes mauvaises pensées, Appelez-moi par mon prénom et Nos baisers sont des adieux, cet article démontre comment l’écrivaine transforme l’extrême violence de sa prose – à raconter son sentiment de blessure face aux identités distinctes d’auteure française, algérienne et queer qu’on veut lui imposer – en un véhicule capable de transmettre des affects plutôt qu’une logique narrative. En reliant certaines œuvres d’art (y compris ses propres textes littéraires) à d’autres corps dans une même virtualité en tant qu’« émetteurs-récepteurs » d’affects, Bouraoui en arrive à suggérer la possibilité d’une nouvelle sexualité queer affective, c’est-à-dire relationnelle et allant au-delà de l’orientation sexuelle de chacun(e).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".