Bibliographic record
Abstract
Cet article examine les procédés et les principes selon lesquels trois ouvrages écrits par Eugène-François Vidocq – ses Mémoires (1828), Les Voleurs (1836) et Les Vrais Mystères de Paris (1844) – organisent l’espace social criminel. L’étude exposera une abondante circulation textuelle et mettra en regard les ouvrages évoqués plus haut avec la célèbre enquête d’Honoré-Antoine Frégier, Des classes dangereuses de la population dans les grandes villes et des moyens de les rendre meilleures . L’article dégagera ainsi le portrait cohérent que construisent ces œuvres de Vidocq, portrait qui sert en fait à établir un ethos bien particulier pour Vidocq, non celui de témoin privilégié, en raison de son passé de forçat et de policier, mais celui d’expert capable d’en traiter comme le font à la même époque les enquêteurs sociaux.
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 | 0.011 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 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".