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Record W4410156195 · doi:10.5206/ijoh.2023.3.21346

Homelessness, Social Disorder and Public Transit in Calgary, Canada: Examining perspectives from law enforcement through the lens of critical social theory

2025· article· en· W4410156195 on OpenAlexaffvenueabout
Lee Stevens, Katrina Milaney, Tessa Penich

Bibliographic record

VenueInternational Journal on Homelessness · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLaw enforcementLens (geology)Transit (satellite)CriminologySociologyEnforcementThrough-the-lens meteringPolitical scienceLawPublic transportEngineering

Abstract

fetched live from OpenAlex

Homelessness and social disorder on public transit are on the rise across Canada. We studied the factors contributing to social disorder on public transit, including homelessness, from the experiences and perspectives of frontline staff including police officers, transit peace officers, and an outreach team in Calgary, Alberta, Canada. Using Braun and Clark's reflexive qualitative analysis approach and a critical social theory framework, we identified significant gaps in services for addressing homelessness, mental health, and substance misuse that are negatively impacting the effectiveness of responses to social disorder. An over-reliance on law enforcement is the first and sometimes only solution. Other results include the stigma of substance use and homelessness in hospitals, and a lack of access to harm reduction and addictions treatment services. The findings reflect broader political and economic trends, including Canada's diminishing supply of low-cost housing and historical and current cuts to financial and social programs.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0510.038
Scholarly communication0.0110.003
Open science0.0030.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.388
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes3
Has abstractyes

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