Contact is a stronger predictor of attitudes toward police than race: a state-of-the-art review
Bibliographic record
Abstract
Purpose This scoping review thoroughly scanned research on race, contacts with police and attitudes toward police. An exploratory meta-analysis then assessed the strength of their associations and interaction in Canada and the USA. Key knowledge gaps and specific future research needs, synthetic and primary, were identified. The paper aims to discuss these issues. Design/methodology/approach A germinal methodological framework for conducting scoping reviews was used (Arksey and O’Malley, 2005). The authors searched for published or unpublished research over the past 15 years and retrieved 33 eligible surveys, 19 of which were included in a sample-weighted meta-analysis. Findings The independent association of contact with attitudes toward police was estimated to be three times larger than the independent race association. Three large knowledge gaps were identified. Almost nothing is known about these associations among specific racial groups as they were typically aggregated into visible minority groupings. The authors have essentially no knowledge yet about specific racial group by a specific type of contact interactions. There is also a lack of generalizable knowledge as research has been largely restricted to locales. Originality/value This is the first research synthesis of race and attitudes toward the police that incorporated contacts with the police. Its observation of the relative importance of contacts suggested a great preventive potential. This scoping review identified needs for a full systematic research review and a formal meta-analysis to plan future primary research including large national studies that are truly representative of Canada and America’s diversity. Such will be needed to advance more confident knowledge about the factors that would support more trusted relationships between police and people in the communities they aim to serve.
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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 | 0.019 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".