Public Support for Conducted Energy Weapons: Evidence from the 2014 Alberta Survey
Bibliographic record
Abstract
This paper examines support for the use of conducted energy weapons (CEWs) by police in Canada using data from the 2014 Alberta Survey (N = 1,204). Support for CEW use is measured using four Likert-scale questions, capturing different dimensions of CEW use: (1) “less-lethal” weapons such as Tasers should be made available to police officers; (2) Tasers are a safe policing tool; (3) the use of Tasers reduces levels of confidence in the police; and (4) official explanations regarding injuries and casualties in Taser-related incidents are satisfactory. Results of a logistic regression indicate that race, age, and gender are key predictors of perceptions of CEW use by police in Canada. Specifically, women, young people, and racialized minorities are least likely to be supportive of CEW use by police. Individuals identifying as white are over three times more likely to support CEW use by police, compared to those identifying as Aboriginal or members of another racialized group. Having a low household income, living in an urban area, and education are not statistically significant predictors of support for CEW use by police.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".