Taking the Pulse: perceptions of crime trends and community safety and support for crime control methods in the Canadian Prairies
Bibliographic record
Abstract
The present study analyzed crime survey data extracted from the 2012 Saskatchewan Taking the Pulse survey on a sample of 1,700 adult Saskatchewan residents. The focus was on examining perceptions of crime trends, perceived effectiveness of various methods for controlling crime, and their sociodemographic correlates. The majority of survey respondents perceived crime in general to be on the rise (37%) or to have not changed at all (48%) over the last three years. Individuals who perceived crime to have decreased were significantly more likely to support alternatives to punishment as effective methods for reducing crime, while individuals who perceived crime to be on the rise were twice as likely to support the use of punitive methods. Perceptions of community safety were unrelated to preference for one crime reduction method over another. Education level was inversely related to crime trend perceptions (r = -.14) and preference for punitive methods to reduce crime (r = -.20). Finally, the results of logistic regression indicated higher levels of education, higher income, and perceptions of crime decreasing were all uniquely associated with a preference for alternatives to punishment in reducing crime. In these analyses, younger age was predictive of a preference for alternatives in reducing youth crime, while urban residential setting was associated with a preference for alternatives to punishment in reducing crime in general.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".