History matters: racial variation in the prevalence of sexual offence convictions
Bibliographic record
Abstract
Overrepresentation of racial minority groups in the criminal justice system is a significant social problem, but little is known about representation in sexual crime. In this study, a cohort of adult males convicted of sexual offences in British Columbia, Canada (N = 4,362) was compared with census data (N = 4,074,385) for patterns of over- and underrepresentation. Demographic information, criminal history, and psychological risk factors (from Static-99R, STABLE-2007) were compared across six different racial groups (White, East Asian, South Asian, Black, Latin American, and Indigenous). Racial groups with a history of colonial oppression in North America (i.e. Black, Indigenous, Latin American) were overrepresented; White, South Asian, and East Asian groups were underrepresented. Differences in reported crime correlated with scores on items related to the propensity for rule violation, but not sexual crime-specific factors. Considering the social-historical context associated with an evaluee’s race may improve the cultural sensitivity of risk assessments.Practice impact statement The overrepresentation of racial minority groups in the criminal justice system is a significant social problem. However, our results indicate that only racial groups with a history of colonial oppression were overrepresented amongst adult males convicted of a sex offence. The social and historical context may provide an increased understanding of systematic bias.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".