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Record W2615424300 · doi:10.1186/s12954-017-0154-1

Supervised injection facilities in Canada: past, present, and future

2017· review· en· W2615424300 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHarm Reduction Journal · 2017
Typereview
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of British ColumbiaBritish Columbia Centre on Substance UseOntario HIV Treatment NetworkSt. Paul's HospitalUniversity of British Columbia Hospital
FundersCanadian Institutes of Health Research
KeywordsHealth psychologySocial policyPublic healthHealth services researchMedicineEnvironmental healthPolitical scienceNursingLaw

Abstract

fetched live from OpenAlex

Canada has long contended with harms arising from injection drug use. In response to epidemics of HIV infection and overdose in Vancouver in the mid-1990s, a range of actors advocated for the creation of supervised injection facilities (SIFs), and after several unsanctioned SIFs operated briefly and closed, Canada's first sanctioned SIF opened in 2003. However, while a large body of evidence highlights the successes of this SIF in reducing the health and social harms associated with injection drug use, extraordinary efforts were needed to preserve it, and continued activism by local people who inject drugs (PWID) and healthcare providers was needed to promote further innovation and address gaps in SIF service delivery. A growing acceptance of SIFs and increasing concern about overdose have since prompted a rapid escalation in efforts to establish SIFs in cities across Canada. While much progress has been made in that regard, there is a pressing need to create a more enabling environment for SIFs through amendment of federal legislation. Further innovation in SIF programming should also be encouraged through the creation of SIFs that accommodate assisted injecting, the inhalation of drugs. As well, peer-run, mobile, and hospital-based SIFs also constitute next steps needed to optimize the impact of this form of harm reduction intervention.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.127
GPT teacher head0.378
Teacher spread0.251 · 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