Gender Gaps in Harm Reduction Services: Understanding Women’s Experiences with Supervised Consumption Sites
Bibliographic record
Abstract
In Canada, the opioid overdose crisis continues to have significantly adverse impacts on people who use drugs, their loved ones, and their communities. Increasingly, understanding the impacts of this crisis, as well as the impacts of supports and services aimed at reducing these harms, through a gendered lens has become the focus of researchers and public health officials alike. In line with this, the objective of the current research was to interrogate women’s experiences with one particular substance use intervention, supervised consumption sites, particularly barriers to accessing, experiences within, and outcomes of these sites. During Phase 1, nine women attending a supervised consumption site in Ottawa, Ontario provided feedback on the proposed methods for the second phase of this research. This phase concluded with minor revisions being made to the methodology for the second phase of the research as a result of the feedback solicited from participants. During Phase 2, seven women from the same supervised consumption site completed a brief survey, which collected socio-demographic and health information, as well as information related to their substance use and use of supervised consumption sites. Participants also engaged in a semi-structured interview that asked questions related to barriers to accessing the site, their experiences within the site (e.g., relationships with staff and peers, feelings of safety), as well as the impacts of the site on their drug use and other aspects of their lives. Findings from this second phase highlight the critical role of connection within these spaces, particularly connection to staff, peers, and various supports, including support to engage in safer drug use, as well as health and community resources. Although participants generally had positive relationships with site staff and peers, and overall, felt safe within the site, some participants also highlighted the violence and harassment present both within and outside of the facility. From a psychological perspective, these findings highlight the role supervised consumption sites play in providing much-needed support to women who use drugs, and, concurrently, the importance of ensuring these spaces are free of violence.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".