Harm Reduction and Women in the Canadian National Prison System: Policy or Practice?
Bibliographic record
Abstract
Applying the principles of harm reduction within the context of incarcerated populations raises a number of challenges. Although some access to harm reduction strategies has been promoted in general society, a divide between what is available and what is advocated continues to exist within the prison system. This paper explores the perceptions and lived experiences of a sample of nationally incarcerated women in Canada regarding their perceptions and experiences in accessing HIV and Hepatitis C prevention, care, treatment and support. In-depth interviews were conducted with 156 women in Canadian national prisons. Q.S.R. Nudist was used to assist with data management. A constant comparison method was used to derive categories, patterns, and themes. Emergent themes highlighted a gap between access to harm reduction in policy and in practice. Despite the implementation of some harm reduction techniques, women in Canadian prisons reported variable access to both education and methods of reducing HIV/HCV transmission. Concerns were also raised about pre-and post-test counseling for HIV/HCV testing. Best practices are suggested for implementing harm reduction strategies within prisons for women in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 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".