Bibliographic record
Abstract
Dans ce numéro consacré au temps des femmes et à la participation des femmes à la construction de la mémoire collective, une réflexion générale suggère que le rapport des femmes à l'histoire pose des problèmes à la fois épistémologiques et politiques. Par la suite, les articles mettent en évidence le défi de découvrir une réalité des femmes dont les traces sont presque invisibles (Collin); une analyse critique de l'historiographie américaine du féminisme (Toupin); le choix politique que représente l'histoire orale pour les femmes (Baillargeon); la présentation d'un nouvel imaginaire des romancières de l'histoire (Simard) et l'examen de l'identité inaccessible, faute de mémoire, des héroïnes de France Théoret (Couillard). Trois notes de recherche examinent enfin les apports de trois groupes de femmes, les infirmières de colonie (Daigle et al.), les vieilles femmes (Charles) et les cinéastes de l'ONF (Denault) à la constitution de la mémoire des femmes.
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 | 0.002 | 0.005 |
| 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 | 0.017 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".