Les limites d’un roman : pratiques transfictionnelles dans l’œuvre de Fortuné du Boisgobey
Bibliographic record
Abstract
La récurrence du Lecoq d’Émile Gaboriau et du Sherlock Holmes de Sir Arthur Conan Doyle illustre éloquemment l’importance des constructions transfictionnelles dans le roman judiciaire et le récit policier. Si aucun autre exemple véritablement comparable ne s’impose d’emblée durant la seconde moitié du xixe siècle, on constate que quelques auteurs se sont employés à édifier autrement des ensembles romanesques. Parmi eux, Fortuné du Boisgobey (1821-1891) se distingue tout particulièrement. Il publie entre 1875 et 1885 plusieurs récits qui, loin de fonctionner en autarcie, se convoquent mutuellement et mettent en place des univers fictionnels fondés sur des procédés qui invitent le lecteur à s’interroger sur le statut de ce qu’il lit. Ce faisant, Boisgobey propose une conceptualisation singulière et originale du genre judiciaire.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.042 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".