Théodore de Bèze et la première « Tragedie Françoise » : imitation, innovation et exemplarité
Bibliographic record
Abstract
Théodore de Bèze attache le sous-titre « Tragedie Françoise » à la pièce qu’il tire du chapitre 22 de la Genèse lorsqu’il la publie en 1550. Or, la classification générique d’Abraham sacrifiant est une question qui a longtemps préoccupé les critiques. Cet article se propose, dans un premier temps, d’éclairer le choix de Bèze de nommer sa pièce une tragédie en examinant la question de l’exemplarité, celle d’Abraham et celle de l’oeuvre elle-même. Dans un deuxième temps, nous justifions cette classification générique grâce à une analyse de la pièce selon le code de la tragédie antique développé par Florence Dupont dans ses travaux sur le théâtre de Sénèque. Cette analyse nous permet de voir comment Bèze incorpore les quatre composantes de ce code tragique — dolor, furor, crime et monstre tragique — dans sa dramatisation du récit biblique et d’observer la façon dont il exploite la focalisation de la tragédie antique sur le héros et sur sa souffrance pour faire d’Abraham un modèle de foi.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".