Factors influencing public satisfaction with the local police: a study in Saskatoon, Canada
Bibliographic record
Abstract
Purpose – The purpose of this paper is to explore determining factors that account for variation in public satisfaction with the local police in Saskatoon, Saskatchewan, Canada. Design/methodology/approach – An integrated method was used to gather the data for this study, including official survey data conducted by Insightrix, and interviews with citizens in Saskatoon. Findings – This research found that demographic factors including age, race (in this study, Aboriginal status in particular), education, and income, perception of neighborhood safety, citizen-police interaction, and learning about crime from news media all have impact on public attitudes toward the police, to different degrees. The gap or distance between the police and the Aboriginal community was highlighted as a major factor. Research limitations/implications – Further research should be done to compare statistical patterns in other same-level cities in Canada. Practical implications – This paper indicates that Saskatoon Police Service in the future should provide a more structured avenue for citizen participation in establishing safe neighborhoods, more structured cultural sensitivity training, and create a wider channel through which community residents with various social backgrounds can demand some measure of accountability for police work in their area. Originality/value – The paper is of value to law enforcement policy-makers and academic researchers with interest in policing and police-community relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".