Bibliographic record
Abstract
Se dibuja una panoramica general sobre los archivos en femenino en nuestro pais. Por una parte, se realiza un breve recorrido por el movimiento de lucha para la igualdad de las mujeres y por los archivos feministas. La documentacion generada por mujeres militantes de este movimiento y la creacion de estos archivos a partir de los anos 70, han sido procesos casi desconocidos con una visibilidad muy limitada. Este patrimonio se encuentra solapado entre el fondo documental de bibliotecas y centros de documentacion de mujeres, pero muy disperso. Se hace necesaria la tarea de unificacion en un archivo propio y la creacion de redes nacionales e internacionales. This paper presents a historical and general overview about women archivist and archives specialized in women and gender. On the one hand, a general review of the feminist archives in Spain is given. The documentation generated by militant women of this movement and the creation of these archives have been almost unknown processes with a very limited visibility. That feminist documentary heritage overlaps with documents stored in libraries and women's documentation centers, but it is very dispersed. The unification in an only archive and the creation of national and international networks becomes a necessary task. In parallel, the profession of archivist in Spain is analyzed from a historical and gender perspective, beginning with the period of the creation of the Facultative Body of Archivists-Librarians in 1858 to the present.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.067 | 0.015 |
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".