Cervelines ou Princesses de science ? Les entraves du savoir des jeunes héroïnes dans le roman de la Belle Époque
Bibliographic record
Abstract
La réflexion proposée dans le présent article porte sur les conditions d’accès des jeunes filles au savoir dans la France des années 1890-1914, peu encline à promouvoir l’image oxymorique d’une jeune femme savante qui possède tous les moyens pour entamer une carrière de médecin, de juriste, d’enseignant, de journaliste ou d’écrivain. Il s’agit de savoir comment le roman de la Belle Époque, notamment celui dit middle brow , négocie, à partir de trois exemples de Colette Yver, l’émergence d’un nouveau modèle féminin en plaçant au cœur de l’intrigue des protagonistes qui tentent de faire valoir leur capital intellectuel dans une société qui perpétue, nonobstant les changements sociaux et culturels, le cadre marital comme principale vocation du sexe féminin.
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 | 0.003 | 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 | 0.009 | 0.029 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 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".