Crime, costs, and well being: policing Canadian Aboriginal communities
Bibliographic record
Abstract
Purpose – The purpose of this paper is to compare the community level factors associated with police strength and operational costs in Aboriginal police services from four different geographic zones, including remote communities inaccessible by road[1]. Design/methodology/approach – Analysis of variance was used to determine whether there was a statistically significant difference in per capita policing costs, the officer to resident ratio, an index of community well-being and crime severity in 236 rural and remote Canadian communities. Findings – The authors found that places that were geographically inaccessible or further from urban areas had rates of police-reported crime several times the national average and low levels of community well-being. Consistent with those results, the per capita costs of policing were many times greater than the national average, in part due to higher officer to resident ratios. Research limitations/implications – These results are from rural Canada and might not be generalizable to other nations. Practical implications – Given the complex needs of these communities, these findings reinforce the importance of delivering full-time professional police services in rural and remote communities. Short duration or temporary postings may reduce police legitimacy as residents may perceive that their rural or Aboriginal status makes them less valued than city dwellers. As a result, agencies should prioritize the retention of experienced officers in these communities. Originality/value – These findings validate the observations of officers about the challenges that must be overcome in policing these distinctive communities. This information can be used to inform future studies of rural and remote policing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".