The role of context in understanding the use of tactical officers: A brief research note
Bibliographic record
Abstract
A small body of research suggests that the use of police tactical officers has become normalized in that they now commonly respond to “routine” calls rather than being restricted to high-risk situations. However, this research has tended to rely on crude data (i.e., call type), which fails to account for the context of the calls (e.g., the presence of potential risk factors that might warrant tactical resources). In this brief research note, we sought to expand upon previous literature by examining the risk factors associated with tactical calls in a Canadian police service. We found that various risk factors were present in many of the calls that tactical officers responded to, some of which might be classified as “routine” (suicide threats, well-being checks, domestic disturbances, etc.). The presence of such risk factors highlights the need to consider context when attempting to understand the use (and consequences) of tactical officers. More rigorous tracking of these factors by police services will facilitate such research and inform policies around the use of tactical resources.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".