Shelter in place: neighborhood policing of homelessness in Montreal, Canada
Bibliographic record
Abstract
Montreal police officers are increasingly called on to respond to visible homelessness. While previous research has focused on strategies of containment or banishment (where individuals experiencing homelessness are removed from certain areas of the city to more homelessness resource–rich areas by the police or expelled entirely), this study presents evidence of a different strategy: that of maintaining individuals within a given neighborhood. Drawing on 29 semi-structured interviews conducted with officers from the Service de Police de la Ville de Montréal (City of Montreal Police Service or SPVM) about the nature of their work with homeless individuals, a neighborhood-level analysis of these interventions found that officers often saw the neighborhood location of a homeless individual as key. The findings revealed officers bonding and creating alliances with homeless individuals, the presence of neighborhood-specific homelessness resources as central to their interventions, and a concern around the migration of homeless individuals from one area of the city to another. In addressing the role of police officers in frontline interventions with individuals experiencing homelessness, a consideration of the centrality of the precinct neighborhood is essential.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".