Construction and Deconstruction of a Homicide Reduction Policy: The Case of Pact for Life in Pernambuco, Brazil
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".