It's been a long time running: New understandings of crime severity and specialization in Canada's longest running crime capital, North Battleford
Bibliographic record
Abstract
Until last year, North Battleford, Saskatchewan has held the title for the “crime capital of Canada” with the highest crime severity index in the country. While the crime severity index is considered a better measure of crime seriousness compared to crime rates, it is still largely influenced by population size. As a result, the small municipality of North Battleford, with a population of approximately 14,000 people, may be inappropriately labelled as the crime capital. The current study compares the crime severity index and crime rates against the location quotient: a geographical measure. The location quotient calculates an area's crime specialization, compared to surrounding areas. In the period 2006 to 2018, findings indicate that North Battleford did not specialize in violent crime compared to other municipal police jurisdictions in Saskatchewan. Implications for policy and practice, as well as local narratives and stigmatization, are discussed .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".