Bibliographic record
Abstract
Les connexions entre littérature et histoire ne sont pas immuables, surtout dans le cas des Antilles Françaises. L’affirmation identitaire et la recherche de ses racines sont quelques-uns des tropismes de la littérature de cette région. Elles permettent au romancier (Glissant, Schwarz-Bart, Confiant, Condé…) de s’affirmer comme historien(ne). Ils placent ainsi la fiction et l’histoire dans des positions antagonistes et manifestent la volonté des auteurs de lutter contre l’acculturation et la perte d’identité culturelle et de soutenir une représentation de la réalité et un témoignage qui puissent au moins être libres de toute trace de néocolonialisme. Mais qu’en est-il de ces faits historiques qui n’ont pas leur place dans l’histoire ? Les nouvelles et les incidents quotidiens qui font la une des journaux et déclenchent le débat public, les personnages légendaires qui ont leur origine dans la mémoire collective, les crimes sanglants qui symbolisent soudain une étape particulière de la conscience collective, tels sont les sujets abordés par les romans policiers caribéens.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".