Latin American Homicide (Chapter 3)
Bibliographic record
Abstract
The urgency for studying Latin America and the Caribbean(LAC) emanates from violence rates that are remarkably higher than in most world regions. Global homicide rates have recently declined (Rogers & Pridemore, 2018; Tuttle et al., 2018). While LAC followed suit, its rates are still comparatively high, and it is home to less than 10% of the global population but about one-third of homicides. The World Health Organization defines violence as endemic if a nation reaches ten homicides per 100,000 residents. Over two-thirds of LAC, nations meet this threshold (World Health Organization, 2023), and the regional mean is above 10. The Pan American Health Organization deemed LAC violence the social pandemic of the century in the Americas (Imbush, 2011). Of the 50 most dangerous cities in the world – as measured by homicide rates – 42 are in LAC (Igarapé, 2023). Although not experiencing civil war, homicide rates in Brazil, Colombia, El Salvador, Guatemala, Honduras, and Mexico are at or above nations with active conflicts (Feldmann & Luna, 2022). Beyond the harm to individuals, families, and communities, the Inter-American Development Bank reported that crime and violence in the region cost a quarter trillion dollars annually, or 3.5% of the region's Gross Domestic Product (GDP) (Jaitman et al., 2017).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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.
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; both teacher heads agree on what is shown here.
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".