Policing the ‘Middle of Nowhere’: Officer Working Strategies in Isolated Communities
Bibliographic record
Abstract
Abstract Thousands of isolated communities across the globe are policed by officers who confront the challenges posed by distinctive geographic and environmental conditions, and many serve in places with a high proportion of economically and politically marginalized peoples in the population. This study reports the results of a survey soliciting the perceptions of 827 Canadian officers working in Indigenous communities; 260 of whom were deployed in isolated locations. Comparison of their responses using t-tests reveal that officers working in isolated communities confront a greater volume and seriousness of crime, and higher levels of social problems contrasted against their counterparts policing non-isolated communities. The results show that officers working in these locations develop a style of policing that is responsive to the characteristics of these places. Considering the perceptions of officers serving in isolated communities is an important step to consider when developing a list of best policing practices that are responsive to the needs of these places, regardless of where in the world they are located.
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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 | 0.002 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".