Une foi exemplaire ? Abraham, Esther et David à l’épreuve de la tragédie huguenote1
Bibliographic record
Abstract
Les tragédies bibliques qui furent composées par plusieurs auteurs réformés à l’orée des guerres de religion (1550-1570 : Bèze, Coignac, A. de La Croix, Rivaudeau, Des Masures, La Taille) ont cette particularité de proposer des intrigues construites autour d’une crise d’ordre tout à la fois politique et spirituel. Les héros ainsi confrontés à un événement grave, capable de remettre en question l’Alliance jadis conclue avec Dieu, sont-ils, au coeur de la tourmente, des fidèles exemplaires ? Pour répondre à cette question, nous tentons, dans un premier temps, de mieux cerner la figure de l’élu souffrant (Job et Abraham) telle qu’elle ressort des Sermons sur Job et du Commentaire sur la Genèse de Calvin. Sur la base de cette réflexion préliminaire, la seconde partie de l’article se donne pour objectif d’interroger, à travers un survol synthétique du corpus, les modalités dramaturgiques régissant la représentation du fidèle mis à l’épreuve.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".