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Record W2527890678 · doi:10.7202/1067942ar

EXPERIENCIAS INDIVIDUALES Y COLECTIVAS DE VIOLENCIA Y VICTIMIZACIÓN EN TORNO A LA DELINCUENCIA ORGANIZADA EN MÉXICO. UNA APROXIMACIÓN CUALITATIVA

2020· article· es· W2527890678 on OpenAlexvenueno aff
Verónica Martínez Solares

Bibliographic record

VenueRevue québécoise de droit international · 2020
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Issues and Policies in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La violencia que ha padecido México en la última década no encuentra referente alguno en la historia reciente del país. Mientras que en los últimos veinte años las tasas de homicidio habían descendido sistemáticamente, los escenarios de violencia letal y otras formas de violencia grave cambiaron de manera drástica y dramática, en un periodo de tiempo muy breve. Con una realidad muy distinta y cercana a la de un conflicto armado en varias regiones, un gran número de víctimas y comunidades se han visto afectadas por la violencia asociada a la delincuencia organizada y por la respuesta estatal a la misma. En este panorama, el presente artículo explora, desde un enfoque cualitativo, la perspectiva de las víctimas y sus comunidades acerca de cómo han vivido los impactos de la violencia y sus experiencias de acceso a la justicia penal en México.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.014
GPT teacher head0.327
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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