Bibliographic record
Abstract
Un tour d’horizon du cinéma français au vingtième siècle signale une présence spectrale de comédiens noirs à l’écran. Présence qui tend d’ailleurs à décroître lorsque l’on considère le nombre de premiers rôles qui leur ont été attribués. En se penchant sur l’influence de ces artistes sur la scène française, l’on remarque que se dégage un paradoxe : s’ils apparaissent certes dans le spectacle français dès le dix-huitième siècle (avec notamment le fameux Chevalier St George), ils demeurent pourtant des figures spectrales dans la mémoire collective. Comment expliquer la présence si disparate de comédiens noirs dans le cinéma français ? Pourquoi semblent-ils condamnés à jouer des rôles stéréotypés trop souvent nourris de clichés hérités de l’imaginaire colonial ? C’est à ces multiples interrogations que cet article tentera de répondre en cherchant à mettre au jour l’évolution des personnages noirs dans le paysage cinématographique français.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".