He Feminicide in Mexico: Challenges Current and Action Proposals
Bibliographic record
Abstract
Femicidal violence is one of the social problems that has marked the agenda public of women, of groups and of the institutions from does some decades, due to increase in femicides that has been experienced in years recent, this increase being concomitant with the quarter wave feminist. The present article HE interested by delve in the bases conceptual and analytical work on femicides in Mexico, therefore, aims to contribute to factual clarifications and debates theorists that have revolved around the definition of the feminicide, so as well as the typologies that have been established for better understanding. Furthermore, this problematic is placed in a frame historical of the society Mexican, about everything from the decade of the years ninety to the topicality, given that it allows visualize that This is a systemic gender violence problem.
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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 | 0.006 | 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 | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".