Estudio comparado entre España y México sobre el marco jurídico aplicable al feminicidio
Bibliographic record
Abstract
La idea de llevar a cabo el presente trabajo surge a raíz de los casos de feminicidios que en los últimos años están teniendo lugar en España y la consecuente necesidad de que el gobierno tome todas las medidas posibles para atajar la comisión de los actos delictivos que causan el asesinato de mujeres, empezando por la tipificación del feminicidio como un delito autónomo en el Código Penal español. Al hilo de estas circunstancias en este trabajo, se realiza un análisis de las causas que dan lugar a la comisión de tales actos, se argumenta la necesidad de su tipificación y se proponen algunas estrategias para erradicar la violencia feminicida. Asimismo, estos mismos parámetros analíticos (causas, tipificación y estrategias para su erradicación) se utilizan para estudiar la cuestión de los feminicidios en México.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".