Crime Prevention and the Science of Where People Are
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
Crime prevention initiatives are often conceptualized working at primary-secondary-tertiary (PST) levels. Primary prevention efforts address the underlying social, economic, and physical environmental conditions that generate crime; secondary prevention efforts focus on people, places, and social conditions that are at high risk of crime; whereas tertiary prevention efforts are directed toward already existing and specific crime problems. This article discusses the uses of the ambient population (a 24-hr average estimate of the population present in a spatial area) to better inform crime prevention initiatives within the PST framework. Though the results indicate the ambient population has utility for all three levels of crime prevention, the most immediate use is in tertiary prevention to better understand the nature of areas with a current crime problem. This information is not available from the resident (or census) population because the resident population indicates where people sleep, not where they are.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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