Le roman noir français et les marges rurales : modalités, enjeux et évolutions.
Bibliographic record
Abstract
Le cadre rural n’est pas si nouveau qu’on pourrait le croire dans les romans noirs français. Cependant, le genre explore depuis les années 2010 les territoires ruraux de manière spécifique, dans le sillage du country noir et du nature writing états-uniens. Il poursuit ainsi l’exploration des marges sociales et la relation des hommes à leur environnement naturel. Après une reconfiguration historique de l’apparition du monde rural dans le roman noir français, l’article envisagera le noir rural comme une nouvelle déclinaison romanesque des marges sociales, qui va bien au-delà d’une représentation mimétique. Articulant le pessimisme inhérent au genre et la vision décliniste du monde de la ruralité, le rural noir parvient cependant à transcender la marginalité pour en faire une forme d’ensauvagement revendiqué.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".