Community experiences with police and implications for public health: A focus group study
Bibliographic record
Abstract
Interactions with the police can impact an individual's short and long-term physical, mental, and social wellbeing, as well as levels of violence and unrest within a community. As such, this study aimed to explore experiences with the police among individuals experiencing socioeconomic disadvantages in Edmonton, Canada. For this qualitative study, participants (n = 39) were recruited from an emergency shelter for women, a drop-in community organization supporting individuals experiencing socioeconomic disadvantages, and a centre providing settlement support for newcomers to Canada. During the recruitment process, the research information sheet, including the scope and goals of the study, was presented, and participants who had any experience with the police were recruited. Each participant joined one of seven focus groups, during which experiences with the police were discussed; data from the focus groups were analyzed utilizing thematic analysis. Factors that contributed to satisfactory experiences with the police included the police demonstrating responsiveness and compassion, as well as an individual's understanding of police work. Factors that contributed to unsatisfactory experiences included the experiences of discrimination, stigmatization, and disrespect during interactions with the police. Participants suggested that community-police relationships could be improved by police being less judgemental and suspicious in their approach, undergoing regular training in sociocultural sensitivity, and being more open in their communication and community outreach. Overall, adopting a less discriminatory and more empathetic approach within a police force is essential for creating and maintaining a positive community-police relationship. By considering the socioeconomic context of people's behaviours and actions, police can better support the health and wellbeing of individuals and communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".