Enhancing the public safety web by standardizing the HUB model in British Columbia
Bibliographic record
Abstract
In Canada, police leaders and politicians have had to address the unsustainable rising costs of policing while crime statistics have been steadily declining for well over a decade. Equally significant is the changing landscape where police services no longer have a monopoly on providing safety to the public. Within this context, there was a push to search for, adopt, and implement models where the police would play an integral part in providing public safety along with other agencies whose services have proven to be more appropriate than traditional law enforcement.\n\nThis major research paper examines the HUB model from its inception in Scotland and subsequent implementation in various Canadian communities. The HUB model’s ideal was implemented in Prince Albert Saskatchewan where supporting models were also adopted with the goal of identifying systemic issues and provide adequate governance.\n\nIn British Columbia, the HUB model has been recognized as a significant crime reduction initiative and in 2015, a pilot project was launched in the City of Surrey. Research findings in this major paper suggests that Surrey’s pilot project would benefit greatly from adopting Prince Albert’s supporting models.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.001 |
| Scholarly communication | 0.024 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".