Bibliographic record
Abstract
Dans Angéline de Montbrun, Laure Conan offre à lire une réflexion existentielle qui, en raison de sa dimension émotionnelle ici mise en valeur, conserve sa pertinence pour penser les rapports d’appartenance au genre féminin. Dans le champ de l’exégèse conannienne, cette contribution vise à nuancer la lecture de la destinée du personnage d’Angéline dans le repli sur soi par un examen des représentations de la honte. L’approche adoptée s’inscrit dans le cadre plus général de la recherche actuelle qui se veut un apport à la théorisation des émotions. Elle permet de montrer comment la honte structure les moments clés du roman, tout en modulant les relations entre les personnages et les identités sexuelles. Les analyses s’attardent d’abord à l’affect de la honte qui, par le repli qu’il entraîne, marque la frontière d’une intégrité à préserver. Elles mettent ensuite en évidence que la « honte-signal » mobilise la quête pour donner une valeur positive non seulement au repli, mais également au pathos de la souffrance.
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 | 0.002 |
| 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 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".