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Record W4407275633 · doi:10.1080/09687637.2025.2461006

The social organization of structural vulnerability among people who are homeless and use drugs: an institutional ethnography

2025· article· en· W4407275633 on OpenAlexafffundabout
Naomi Nichols, Samantha Blondeau

Bibliographic record

VenueDrugs Education Prevention and Policy · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEthnographyVulnerability (computing)Social vulnerabilitySociologyPsychologyCriminologySocial psychologyComputer securityAnthropology

Abstract

fetched live from OpenAlex

Background In this article, we describe an institutional ethnographic investigation of the housing and homelessness response in one municipality in Ontario, Canada.Methods Drawing on 42 interviews with social service professionals and municipal government employees and 49 interviews with people who are or have been using municipal housing and homeless services (e.g. emergency shelters, mobile healthcare, outreach services, transitional housing), we bring into view some of the inter-institutional and organizational processes that shape housing precarity among people who use drugs.Results Our research pinpoints specific institutionally-organized processes – i.e. structural vulnerabilities – that expose people who use drugs to housing loss, unsheltered homelessness, and difficulties in re-housing (or homeless chronicity). In many cases, the processes also make people more vulnerable to harms associated with substance use.Conclusion The specificity of our analysis points toward policy, legislative and institutional reforms that could improve access to justice, health, and housing for people who use drugs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.379
Teacher spread0.359 · 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.

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