« Libre d’aimer » ? Loi du péché et destin romanesque chez Segrais et Mme de Lafayette
Bibliographic record
Abstract
Comment le libre arbitre des personnages de la nouvelle classique est-il mis à mal par la passion amoureuse ? Dans les nouvelles de Segrais et de Mme de Lafayette qui insistent sur la difficulté à résister aux injonctions du désir, on décèle deux influences de nature bien distinctes, voire antagonistes : une reprise presque anodine de topoï romanesques concernant le destin et une suggestion de l’inclination perverse de la volonté qui s’apparente à la doctrine de saint Augustin. Après un rappel des propositions de ce théologien, notre article décrit la manière dont ces deux auteurs classiques s’approprient le problème de la fatalité amoureuse. Il relève, dans quelques-unes des Nouvelles françaises où prolifèrent les lieux communs à ce sujet, une saturation de son explication causale. Cela forme un contraste avec l’étonnement qui accompagne la naissance de la passion dans La Princesse de Clèves ; étonnement qui engendre des réflexions de psychologie morale proches de l’augustinisme.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".