La mémoire dans la peau. Les généalogies alternatives de <i>Douce France</i> de Karine Tuil
Bibliographic record
Abstract
Le présent article analyse le changement de peau de la narratrice de Douce France de l’auteure française Karine Tuil après son incarcération dans un centre de rétention à la lumière des enjeux mémoriels et généalogiques qu’il soulève. Fable sur la (post)mémoire, l’identité et l’immigration, Douce France fait valoir le caractère poreux de la subjectivité, la façon dont celle-ci est façonnée par les discours qui précèdent et entourent le sujet sans que soient pour autant forcloses toutes possibilités de transformation. La mise en dialogue de récents travaux de la critique féministe sur la subjectivité, dont ceux de Judith Butler et de Rosi Braidotti, avec des écrits sur les retombées du nazisme chez les générations d’après permet d’envisager l’intrication de la subjectivité, du corporel et du mémoriel dans Douce France.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".