Le regard de tous et le sang d’un seul : les foules des exécutions publiques dans le roman historique du premier xixe siècle
Bibliographic record
Abstract
Dans le roman historique de la première moitié du XIXe siècle, la description d’une exécution publique est un paradigmatique marqueur temporel, qui crée un efficace « effet de passé ». Cependant, grâce à l’étude d’un corpus mêlant deux romans canoniques, Cinq-Mars (1826) d’Alfred de Vigny et Notre-Dame de Paris (1831) de Victor Hugo, et deux romans dont le succès n’a pas dépassé le XIXe siècle, Raoul (1826) de G. de la Baume ou La Cour des miracles (1832) de Théophile Dinocourt, cet article montre que de telles scènes permettent également de confronter le lectorat à des problématiques qui lui sont contemporaines : les enjeux esthétiques de la représentation des foules assistant aux supplices (représenter simultanément la multiplicité des individus et l’unicité de la foule, faire entendre les voix singulières ou collectives, etc.) impliquent un discours ambigu sur le lien entre foule et violence, ainsi qu’une réflexion sur les mécanismes de formation et d’action de la foule, qui anticipe à sa manière la mise en forme de la « psychologie des foules » à la fin du siècle.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".