Deterrence and Geographical Externalities in Auto Theft
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
Understanding the degree of geographical crime displacement is crucial for the design of crime prevention policies. This paper documents changes in automobile theft risk that were generated by the plausibly exogenous introduction of Lojack, a highly effective stolen vehicle recovery device, into a number of new Ford car models in some Mexican states, but not others. Lojack-equipped vehicles in Lojack-coverage states experienced a 48 percent reduction in theft risk due to deterrence effects. However, 18 percent of the reduction in thefts was displaced toward unprotected Lojack models in non-Lojack states, providing new evidence of geographical crime displacement in auto theft. (JEL H76, H77, K42, O17, O18, R23)
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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