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Low-barrier harm reduction and housing for older people in Vancouver’s opiate crisis: meeting people where they are

2024· article· en· W4400143423 on OpenAlexaffabout
Donna Baines, Susan Braedley, Tamara Daly, Sean Hillier, Frances Cabahug

Bibliographic record

VenueCritical and Radical Social Work · 2024
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsYork UniversityUniversity of British Columbia
Fundersnot available
KeywordsHarm reductionOpiateHarmReduction (mathematics)Older peoplePsychologyGerontologyMedicineSocial psychologyNursingPublic health

Abstract

fetched live from OpenAlex

Drawing on recent case-study data, this article explores innovative practices around harm reduction and housing for older people who use drugs. Although right-wing groups call for further criminalisation of drug use, in light of extraordinarily high levels of deaths from opioid overdose in Vancouver, Canada, the provincial government has quietly permitted the development of safe supply, the testing of illegal drugs to avoid poisonings and the provision of low-barrier, inclusive and supportive social housing, including housing specifically for older people. Drawing on crisis theory, the article analyses the provision of low-barrier harm reduction services for this marginalised and highly vulnerable group of older people and reflects on what we can learn about providing supports that are needs based and strengths based and embody meeting people where they are.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.574
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.010
Scholarly communication0.0050.002
Open science0.0020.010
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 head0.015
GPT teacher head0.297
Teacher spread0.282 · 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
Published2024
Admission routes2
Has abstractyes

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