Los crímenes atroces cometidos en México en el marco de la guerra contra las drogas y la justicia transicional como respuesta
Bibliographic record
Abstract
El enorme número de graves violaciones a derechos humanos que se han cometido en las últimas décadas en México, particularmente a partir de la sangrienta política de seguridad de los tres sexenios presidenciales recientes, aunado a la falta de capacidad y voluntad de las instituciones de justicia de hacer frente a la impunidad, hacen necesario reflexionar sobre la dimensión de la crisis y sobre cuáles son las alternativas para garantizar los derechos de las víctimas. En este artículo se pretende mostrar el contexto y dimensión de las atrocidades cometidas, así como una serie de propuestas para llevar a juicio a los responsables, reparar a las víctimas y evitar la repetición de conductas delictivas similares, particularmente cuando se cometen al amparo de las instituciones y políticas del Estado mexicano.
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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 | 0.000 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".