Bibliographic record
Abstract
Cet article compare deux portraits de comédiens dans la littérature moderne. Violette Leduc et Hervé Guibert transforment le corps de l’acteur en une surface sur laquelle s’inscrit la méthode de création de l’écrivain. En dressant un portrait de Jean Marais inspiré du personnage de la Bête qu’il incarne dans le film de Jean Cocteau, Leduc donne à sa beauté physique une valeur éthique. Lorsqu’il retrace les disputes qui rythment sa relation tumultueuse avec Isabelle Adjani, Guibert insiste sur la recherche de la vérité en littérature, selon la parrêsia définie par Michel Foucault dans ses derniers écrits. En s’attachant à des acteurs connus auprès du grand public, les deux auteurs soulignent les enjeux d’une écriture qui engage pleinement leur corps, similaire à l’incarnation d’un personnage devant la caméra.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.028 | 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".