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Record W4411338226 · doi:10.1111/hojo.12614

“What If I Call Them the Smurfs?” Comparing Marginalized People Who Use Drugs’ Experiences and Interactions with Auxiliary and Sworn Police Officers

2025· article· en· W4411338226 on OpenAlexafffundabout
Marta‐Marika Urbanik, Katharina Maier, Carolyn J. Greene, Kaitlyn Hunter

Bibliographic record

VenueThe Howard Journal of Crime and Justice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of WaterlooWilfrid Laurier UniversityUniversity of WinnipegUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCriminologySociologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Police civilianization represents one of the most significant developments in contemporary policing. However, little is known about how marginalized communities, who are routinely subjected to civilian police work, perceive, and experience these actors. Drawing upon interviews with 66 unhoused people who use drugs in Winnipeg (Canada), we compare participants’ perceptions of and experiences with the Winnipeg Police Services’ (WPS) Auxiliary Force Cadets—civilian police with limited legal authorities—and sworn WPS officers. Participants reflected on Cadets’ inferior legal authority to explain their invasive and aggressive policing style, whereas they perceived sworn officers as more passive. They thus modified their behaviours in response to their perceptions of and interactions with these different policing actors. We demonstrate how marginalized persons distinguish between varied policing actors, engaging in what we coin police actor demarcation , and analyze why this distinction matters with respect to how they navigate and interact with policing bodies.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.065
GPT teacher head0.363
Teacher spread0.299 · 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 designQualitative
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 routes3
Has abstractyes

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