Descente chez les bleus : une expérience professionnelle au sein de la police montréalaise
Bibliographic record
Abstract
The author gives an account of the fifteen years he spent in the Montreal police department as a community relations adviser. In this role, he was asked to examine why his organisation was uneasy about ethnic diversity and unwilling to embrace it. He was also asked, where appropriate, to identify the causes of the problem and make proposals regarding personnel management, recruitment strategies and staff in-service training for police officers in intercultural relations, conflict management and conflict resolution. The article essentially contemplates the progress and setbacks of reform aimed at introducing community policing, which is both preventative and attentive to the specific ethnocultural characteristics of the urban area in which the police have to maintain order. The author concludes that it is impossible to reform the police without giving high priority to diversity management and interethnic relations.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.049 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".