Race, Street Life, and Policing: Implications for Racial Profiling
Bibliographic record
Abstract
Scholarship is divided over whether youth from marginalized populations are stopped and searched by police primarily due to their illegal behaviours (functionalism), marginalized status (conflict theory), or both. We address this debate by comparing the police interactions experienced by a sample of high school students (N = 3,393) living at home with a sample of youth (N = 396) who have left home and are residing in shelters or on the streets of Toronto, Ontario. Logistic regression analysis demonstrates that after controlling for demographic and behavioural factors, black high school students are more likely than white high school students to report being stopped and searched by the police multiple times; this indicates that they are the victims of racially biased policing. In contrast, black and white street youth are equally likely to report being stopped and searched by the police on multiple occasions. We suggest that this is because all street youth, regardless of race, take part in high levels of deviant behaviour, which attracts police attention. We conclude that consensus theory is appropriate for explaining police stops and searches of street youth, whereas conflict theory is appropriate for explaining police stops and searches of black high school students.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".