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Record W2797387654 · doi:10.6000/1929-4409.2018.07.12

Construction and Deconstruction of a Homicide Reduction Policy: The Case of Pact for Life in Pernambuco, Brazil

2018· article· en· W2797387654 on OpenAlexvenueno aff
José Luiz Ratton, Jean Daudelin

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHomicideCorporate governanceDeterrence (psychology)State (computer science)Government (linguistics)Economic JusticeState policeDeconstruction (building)CriminologyDeterrence theorySociologyPolitical scienceLawPoison controlEconomicsSuicide preventionLaw enforcementEngineeringManagementEnvironmental health

Abstract

fetched live from OpenAlex

This paper tries to demonstrate that both the fall in homicides in Pernambuco (from 2007-2013) and the resurgence in them that followed (2014-2017) are fundamentally linked to two explanatory variables, which are in turn connected: the model of governance of public security produced in Pernambuco at the level of state government strategy and the capacity for deterrence produced in the framework of the Criminal Justice System (especially that of state police, who are under the responsibility and “control” of the executive power of the state). This article argues that the construction of this specific model of governance of Public Security and the definition, monitoring and realization of deterrence strategies within the police were crucial to the reduction of the number of homicides in the most violent areas of the state. On the other hand, the dissolution of the capacity for integrated governance of the police, with the consequent dismantling of the deterrence capacity aimed primarily at the reduction of homicides and crimes against life that had been successfully conceived and realized between 2007 and 2013, explains the increase in intentional violent crimes that has been observed since 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.375
Teacher spread0.330 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations20
Published2018
Admission routes1
Has abstractyes

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