“It Goes on Everywhere”: Injection Drug Use in Canadian Federal Prisons
Bibliographic record
Abstract
BACKGROUND: International and Canadian research on in-prison injection drug use has documented the frequency of its occurrence as well as some of the resulting consequences such as increased prevalence of HIV and hepatitis C virus. Access to prison-based harm reduction programing is thus important. OBJECTIVES: The aim of this study was to learn from former prisoner experiences and insights on in-prison injection drug use in order to advance and improve access to harm reduction options, in particular prison-based needle and syringe programs (PNSPs). METHODS: The qualitative and community-based study was conducted in 2014/2015 and included former prisoners from Ontario, Canada (N = 30) who had recent experience of incarceration in a federal prison and knowledge of injection drug use. Data analysis followed the deductive approach, drawing on the expertise of the academic and community-based research team members. RESULTS: Interview and focus group participants disclosed that drugs are readily available in Canadian federal prisons and that equipment used to inject is accessed in a variety of ways, sometimes gained through illicit means and sometimes made by prisoners themselves. Equipment sharing is a frequent occurrence, and disposal of such supplies is rare. Conclusions/Importance: While not yet available in Canada, PNSPs have led to positive outcomes in international contexts, including reductions in needle sharing and transmission of HIV and hepatitis C. Support for PNSPs among numerous Canadian organizations and associations, along with a recent change in government, could suggest a renewed opportunity for PNSP implementation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".