Christelle Taraud, Féminicides. Une histoire mondiale, La Découverte,
Bibliographic record
Abstract
En Quebec, como sin duda en otros lugares de Canadá y Europa, el término “feminicidio” ha empezado a utilizarse desde hace poco. Partiendo de su definición más básica —el asesinato de una mujer a causa de su género—, el término feminicidio se aplicó de manera rutinaria a todos los asesinatos de mujeres, en particular los cometidos por un cónyuge, pasado o presente. Hasta la fecha, las escasas presentaciones y análisis que se han hecho de estos asesinatos en el ámbito público y en los medios de comunicación, sólo excepcionalmente se han basado en una perspectiva de género. La atención se centra casi exclusivamente en las relaciones interpersonales, es decir, entre cónyuges. Rara vez se tienen en cuenta los factores sociales de riesgo más amplios, y rara vez van más allá del historial de violencia del asesino (¡y aún así!) y de su relación inmediata con la víctima.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".