Crack Pipe Sharing Among Street-Involved Youth in a Canadian Setting
Bibliographic record
Abstract
Introduction and Aims Crack pipe sharing is a risky practice that has been associated with the transmission of Hepatitis C and other harms. While previous research has exclusively focused on this phenomenon among adults, this study examines crack pipe sharing among street-involved youth. Design and Methods From May 2006 to May 2012, data were collected from the At-Risk Youth Study, a cohort of street-involved youth age 14–26 in Vancouver, Canada. Survey data from active crack smokers were analysed using generalised estimating equations logistic regression. Results Over the study period, 567 youth reported smoking crack cocaine and contributed 1288 observations, among which 961 (75%) included a report of crack pipe sharing. In multivariate analysis, factors that were associated with crack pipe sharing included: difficulty accessing crack pipes (adjusted odds ratio [AOR] =1.58, 95% confidence interval [CI] 1.13–2.20); homelessness (AOR =1.87, 95%CI 1.43–2.44); regular employment (AOR =1.53, 95%CI 1.15–2.04); daily non-injection crystal methamphetamine use (AOR =2.04, 95%CI 1.11–3.75); daily crack smoking (AOR =1.37, 95%CI 1.01–1.85); encounters with the police (AOR =1.42, 95%CI 1.01–1.99); and reporting unprotected sex (AOR =1.95, 95%CI 1.47–2.58). Discussion and Conclusions The prevalence of crack pipe sharing was high among our sample and independently associated with structural factors including difficulty accessing crack pipes and homelessness. Crack pipe sharing was also associated with high intensity drug use and a number of other markers of risk and vulnerability. Collectively, these findings highlight opportunities for health services to better engage with this vulnerable group and reduce this risky behaviour.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".