A measured response? Examining the use of specialty resources and tactics adopted by tactical officers
Bibliographic record
Abstract
The use of tactical officers, commonly known as Special Weapons and Tactics (SWAT), has become a contentious issue within contemporary policing. Problematically, most Canadian research has focused on de-contextualized call types (e.g. mental health call, traffic stop) to speak to the use of tactical officers. We move beyond this limitation by conducting a content analysis of incidents that received a response from tactical officers (n = 1652) using operational data from the Winnipeg Police Service. Our results indicate that a pair of tactical officers responded to approximately half of incidents (n = 803) and that the number of responding tactical officers increased when weapons were reported to be involved and when patrol officers requested tactical members to attend the call. Similarly, the use of tactics and other specialty units (e.g. K9) varied depending on the level of risk posed by the incident. Although tactical officers rarely used force (n = 9), most commonly this involved the use of less-lethal options on armed individuals. Taken together, our findings suggest that the use of tactical officers and their tactics are a measured response to risk posed by an incident in an attempt to minimize harm to officers and the public.
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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 | 0.020 | 0.121 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".