Disproportionate Minority Contact in Canada: Police and Visible Minority Youth
Bibliographic record
Abstract
There is a consensus that some racial groups are over-represented in their contact with the Canadian justice system, but a lack of agreement about possible reasons for this over-representation. The two dominant explanations for disproportionate minority contact (DMC) with the police are differential involvement in crime and differential treatment by the police. Differential treatment may be due to disproportionate possession by minorities of risk factors for police contact or to discriminatory policing. This paper uses data on self-reported delinquency and police contacts from a representative sample of Canadian youth aged 12 to 17 years from the National Longitudinal Study of Children and Youth to test the hypotheses that DMC is due to differential involvement or to differential treatment due to disproportionate risk factors. The results indicate that there was disproportionate minority contact with the police, but no support was found for explanations of DMC in terms of either differential involvement or differential treatment due to risk factors. Distinguishing between youth who report violent delinquency and all other youth, DMC was found only for the non-violent youth; this DMC was also not explained by differential treatment due to risk factors. By eliminating other explanations, the results suggest that racially discriminatory policing may be one explanation for DMC in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".