Bibliographic record
Abstract
Parce que la face obscure de l’humain éclaire tout le reste, parce que l’histoire de l’Italie n’a cessé de ressembler à un giallo, parce que, dans la Botte comme partout, le polar est un excellent analyseur social et enfin parce que le roman noir incarne outre-Alpes comme ailleurs un des secteurs les plus dynamiques de la littérature, il occupe une place centrale dans nos collections « Bibliothèque italienne » et « Suites italiennes ». De l’auteur collectif Wu Ming à Valerio Evangelisti, en passant par Andrea Camilleri et Massimo Carlotto, c’est en Italie qu’on trouve quelques-unes des expériences littéraires les plus originales de notre époque, qui s’appuient sur la littérature de genre pour mieux la subvertir. Ces auteurs dont nous analyserons quelques œuvres dessinent un certain visage de l’Italie : terre d’immigrants et d’immigrés, partagée entre replis xénophobiques, petitesses identitaires et un amour des lieux et des langues, une ouverture aux grands vents du monde.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".