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Record W2228552858 · doi:10.26564/21453381.465

Seguridad pública y criminalidad: el caso del departamento de Sucre en 2014

2015· article· es· W2228552858 on OpenAlexaff
Reina Victoria Vega, Enoin Humanez Blanquicett

Bibliographic record

VenueCriterio Jurídico Garantista · 2015
Typearticle
Languagees
FieldSocial Sciences
TopicCriminal Justice and Penology
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Este estudio tiene como objetivos generales: 1) analizar la dinamica de la criminalidad en el departamento de Sucre (Colombia) en el ano 2014, de cara a la inseguridad en la sociedad global y a la luz de la teoria de la seguridad publica; e 2) identificar el delito mas frecuente, su ubicacion a nivel municipal y microlocal y la poblacion afectada. Utilizando la metodologia del estudio de caso se analiza, de manera  comparativa y multidisciplinar, el comportamiento de la actividad delincuencial en este departamento. Los resultados del estudio indican que, en materia de criminalidad, el homicidio es el delito de mayor frecuencia. Sin embargo, la perspectiva comparativa nos permitio establecer que Sucre ha registrado historicamente tasas relativamente bajas de homicidios con relacion a la media nacional y a otros departamentos. En 2014, mientras Sincelejo, la capital departamental, redujo su tasa de homicidios, los municipios de San Onofre y San Marcos registraron una tasa de homicidios superior a la media departamental. En conclusion, en materia de  inseguridad, Sucre ha  seguido la tendencia del pais. Su tasa de homicidios  aumento entre los anos  1980 y 2000 y ha disminuido desde 2005.  El sicariato  fue la principal causa de muertes violentas en 2014.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.048
GPT teacher head0.386
Teacher spread0.338 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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