“It comes with the territory”: Policing the carceral boundary in Ontario, Canada
Bibliographic record
Abstract
Police are uniquely empowered to restrict movement, manage the circulation of bodies, and facilitate passage into the carceral system. And yet, carceral scholarship tends to separate prisons from the police that fill them. Combining key sensitizing concepts from the sociological literature on boundaries and critical border studies, this article shows how police activate a socio-symbolic separation between civil society and the prison, which shares important, analytically revealing properties with territorial borders. Based on 29 in-depth, open-ended interviews with police from 13 different services across the Windsor-Quebec City corridor, Canada, this study analyzes how police make sense of their occupational activity in terms of their location in the carceral structure. Paying special attention to the shared representations officers use, three central themes emerge. First, police-civilian encounters constitute a core site of carceral boundary production. Second, much like national borders, the carceral boundary produces tremendous insecurity that officers attempt to manage through constant vigilance and the threat of force. Finally, conflict escalates as interactions at the boundary intensify. By attending to the ways police conceptualize their constitutive role in carceral boundary production, we can better appreciate the tension at the heart of the police civilian encounter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Science and technology studies | 0.037 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".