The role of peer drug users’ social networks and harm reduction programs in changing the dynamics of life for people who use drugs in the downtown eastside of Vancouver, Canada
Bibliographic record
Abstract
The Downtown Eastside (DTES) of Vancouver, Canada has been the epicentre of HIV, hepatitis C and drug overdose related to People who inject drugs (PWIDs) since the mid1990s. In response to the growing government inaction, numbers of peer-run organizations were formed. This dissertation was conducted to capture the genesis and influence of peer drug users, their networks and harm reduction programs over the past 18 years in shaping the neighborhood. Semi-structured qualitative interviews were conducted with peers from various harm reduction volunteer locations in the DTES. Moreover, various drug users were recruited from a controversial harm reduction program in the DTES that provides pharmaceutical heroin. Interviews were analyzed thematically using two methods of coding analysis.\tFindings suggest that peers were taking on important education and safety roles, and were able to alter the behaviour, attitude, and intention of injection drug users within the DTES area of the city. Further, peer injection drug users were able to reach individuals who were reluctant to seek medical help, housing, and prevention services. Peers serve as an agent of change in the DTES to disseminate information and risk reduction skills to the most marginalized people. Peer drug users have not only been able to change the discriminatory rhetoric but they have been able to reduce the suffering that drug users have endured as a consequence of the war on drugs. Attending heroin trials in Vancouver has been particularly effective in creating a unique microenvironment where PWIDs who have attended heroin trials have been able to form a collective identity advocating for their rights. In physical terms, the DTES has become cleaner and safer for its residents because of availability of an injection facility and numerous peer-run harm reduction programs. In conceptual terms, PWIDs are less likely to experience discrimination by the city, hospital, and police. Moreover, the residents in the new DTES are more likely to be involved in their civic issues and raise concerns in a new political arena. Peer-run harm reduction programs have given a voice to the most marginalized members of society who otherwise would not be represented. The result of this dissertation and costing analyses conducted point to the need for the expansion of the peer and harm reduction programs beyond the current location in the DTES to other locations in Canada such as Montreal, Ottawa, Toronto, Saskatoon and Victoria.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".