Factors Associated with Public Injecting Among Users of Vancouver's Supervised Injection Facility
Bibliographic record
Abstract
BACKGROUND: We evaluated factors associated with public drug injection among a cohort of injection drug users (SEOSI) originally recruited from within Vancouver's supervised injecting facility (SIF). METHODS: We used univariate statistics and logistic regression to examine factors associated with public drug injection among SEOSI participants. FINDINGS: Between June 2004 and July 2005, 714 IDU were followed up as part of SEOSI. In multivariate analyses, factors associated with public drug injection included homelessness (adjusted odds ratio (aOR) = 3.10; p < .001), syringe lending (aOR = 5.39; p < .001), requiring help injecting (aOR = 1.60; p = .05), and reporting that wait times affected frequency of SIF use (aOR = 3.26; p < .001). INTERPRETATION: Persistent public injection was independently associated with elevated HIV risk behaviors, as well as programmatic factors that limit SIF use. SIF program expansion may further help to reduce persistent risk behaviors and the community concerns related to public injection drug use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".