“They're causing more harm than good”: a qualitative study exploring racism in harm reduction through the experiences of racialized people who use drugs
Bibliographic record
Abstract
BACKGROUND: Increased opioid-related morbidity and mortality in racialized communities has highlighted the intersectional nature of the drug policy crisis. Given the racist evolution of the war on drugs and the harm reduction (HR) movement, the aim of this study is to explore racism within harm reduction services through the perspectives of our participants. METHODS: We conducted a qualitative descriptive study to explore the perspectives of racialized service users and providers on racism in the HR movement in the Greater Toronto and Hamilton Area (GTHA). Four racialized service users and four racialized service providers participated in semi-structured interviews that were audio-recorded, transcribed, and analysed thematically. RESULTS: Five themes related to racism in HR were generated: (1) whiteness of harm reduction as a barrier to accessing services, (2) diversifying HR workers as a step towards overcoming distrust, (3) drop-in spaces specific to Black, Indigenous, and people of colour are facilitators to accessing harm reduction, (4) lack of representation in HR-related promotional and educational campaigns, and (5) HR as a frontier for policing. CONCLUSIONS: Our findings suggest that structural and institutional racism are prevalent in HR services within the GTHA, in the form of colour-blind policies and practices that fail to address the intersectional nature of the drug policy crisis. There is a need for local HR organizations to critically reflect and act on their practices and policies, working with communities to become more equitable, inclusive, and accessible spaces for all people who use drugs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".