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Record W4415976794 · doi:10.1177/26326663251390271

“It comes with the territory”: Policing the carceral boundary in Ontario, Canada

2025· article· en· W4415976794 on OpenAlexaffabout
Aidan Lockhart

Bibliographic record

VenueIncarceration · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBoundary (topology)Boundary-workScholarshipBoundary objectPrisonCriminal justice

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.312
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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