Bibliographic record
Abstract
Few studies that examine the public's perception of the police force exist in Canada. To contribute to this gap in the literature, this article will examine the impact of visible minority status on an individual's level of confidence in police officials in Canada, by utilizing the data collected by the General Social Survey of Canada in 2014. Previous research indicates that often members of visible minorities are inclined to view police officials with suspicion and distrust, frequently reporting that police disproportionately target them due to their race or ethnicity. Contrary to this evidence, the results of this multivariate analysis suggest that individuals who identify as a visible minority do not report a lower level of confidence in the police when compared to those who identify as a non-visible minority when controlling for the effects of sex and age. In comparison to other democratic states, Canada has embraced its multicultural identity by implementing cultural sensitivity training for police officers to challenge pre-existing biased perceptions to effectively engage with citizens in the community. It appears from this analysis, that these combined efforts have proven successful, suggesting that historical discrepancies between visible minorities' perceptions of the police force and the perceptions of non-visible minorities have begun to converge.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".