Peer-engagement and its role in reducing the risky behavior among crack and methamphetamine smokers of the Downtown Eastside community of Vancouver, Canada
Bibliographic record
Abstract
BACKGROUND: The role of peers (former or current drug users) in reducing risky behavior within methamphetamine and crack smokers has not been well described or researched. The current study not only explores the role of peers in reducing risk factors for morbidity within the illicit drug smoking population in the Downtown Eastside (DTES) community of Vancouver but it also investigates the changes in the nature of drug use after the closure of an unsanctioned smoking facility. METHODS: The data pertain to qualitative interviews with 10 peers and 10 illicit drug smokers. The semi-structured interviews were conducted through community-based research, and the digital transcripts were analyzed via NVivo 10 software. RESULTS: The results indicate that peers (former and current drug users who are employed as educators) are instrumental in transferring risk reduction knowledge within crack and methamphetamine smokers. For example, these peers have been able to teach users about the risk of sharing pipes, using brillo, and using public drug. Furthermore, the Vancouver Area Network of Drug Users provides employment for crack and methamphetamine users in Vancouver who tend to have scarce sources of employment. However, since the closure of the unsanctioned inhalation facility, there has been significantly more public drug use and pipe sharing in the vicinity of the facility, placing drug smokers at significant risk of arrest, violence, and blood-borne infections. CONCLUSIONS: The current study recommends expanding the harm reduction peer network for people who smoke illicit drugs in the DTES community of Vancouver who have historically been underserved.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".