What Explains Criminal Violence in Mexico City? A Test of Two Theories of Crime
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are competing theories of what drives crime in cities and neighbourhoods. Two widely cited theoretical approaches focused on social disorganization and institutional anomie propose different explanations for the causes and dynamics of criminality. Yet these theories are seldom empirically tested, much less acknowledged, outside of North America and Western Europe. This article considers their applicability in Mexico’s capital, a sprawling metropolis of more than 20 million people. The authors administer spatial and general statistical tests to explain the geographical patterns of crime rates across multiple forms of criminality. The assessment demonstrates that both theories accurately predict the spatial distribution of crime. The article concludes with a host of policy conclusions, emphasizing social crime prevention over more traditional law and order measures. and consolidating families, parents and childcare.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it