MétaCan
Menu
Back to cohort
Record W2167381258 · doi:10.1177/1049732311400919

Injection Drug Users’ Access to a Supervised Injection Facility in Vancouver, Canada: The Influence of Operating Policies and Local Drug Culture

2011· article· en· W2167381258 on OpenAlexafffundabout
Will Small, Jean Shoveller, David Moore, Mark Tyndall, Evan Wood, Thomas Kerr

Bibliographic record

VenueQualitative Health Research · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsRestructuringGovernment (linguistics)Observational studyLocal governmentInjection drug useBusinessDrugMedical emergencyPublic relationsPublic administrationMedicineDrug injectionFinancePolitical sciencePharmacology

Abstract

fetched live from OpenAlex

North America's first supervised injection facility (SIF) was established in Vancouver, Canada, in 2003. Although evaluation research has documented reductions in risk behavior among SIF users, there has been limited examination of the influence of operational features on injection drug users' access to these facilities. We conducted an ethnographic study that included observational research within the SIF, 50 in-depth individual interviews with SIF users, and analysis of the regulatory frameworks governing the SIF. The government-granted exemption allowing the facility to operate legally imposes key operating regulations, as well as a cap on capacity, which results in significant wait times to enter the injecting room. Regulations that prohibit practices that are common in the local drug culture also negatively affect SIF utilization. Restructuring policies that shape the operation of the SIF could enhance access to the facility and permit SIF services to better accommodate local drug use practices.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.142
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.297
GPT teacher head0.520
Teacher spread0.223 · 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 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

Citations70
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicHIV, Drug Use, Sexual RiskFrench-language works237,207