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Record W1969702809 · doi:10.3109/10826084.2012.644107

The Injection Support Team: A Peer-Driven Program to Address Unsafe Injecting in a Canadian Setting

2012· article· en· W1969702809 on OpenAlexaffabout
Will Small, Evan Wood, Diane Tobin, Jacob Rikley, Darcy Lapushinsky, Thomas Kerr

Bibliographic record

VenueSubstance Use & Misuse · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsAIDS VancouverSt. Paul's Hospital
Fundersnot available
KeywordsSAFEROutreachHarm reductionIntervention (counseling)Drug userInjection drug useMedical educationMedicineNursingDrug injectionDrugPsychologyPublic healthComputer securityPsychiatryComputer sciencePolitical science

Abstract

fetched live from OpenAlex

In 2005, members of the Vancouver Area Network of Drug Users (VANDU) formed the Injection Support Team (IST). A community-based research project examined this drug-user-led intervention through observation of team activities, over 30 interviews with team members, and 9 interviews with people reached by the team. The IST is composed of recognized "hit doctors," who perform outreach in the open drug scene to provide safer injecting education and instruction regarding safer assisted-injection. The IST represents a unique drug-user-led response to the gaps in local harm reduction efforts including programmatic barriers to attending the local supervised injection facility.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.002
Scholarly communication0.0010.001
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.053
GPT teacher head0.364
Teacher spread0.312 · 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 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

Citations81
Published2012
Admission routes2
Has abstractyes

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