Community Drug Checking and Substance Use Stigma: An Analysis of Stigma-Related Barriers and Potential Responses
Bibliographic record
Abstract
The illicit drug overdose crisis is an ongoing epidemic that continues to take lives at unprecedented rates and British Columbia, Canada has been identified as the epicenter in Canada, where approximately five deaths per day are linked to unregulated substances most often including fentanyl (Service, 2022). In Victoria, British Columbia, community drug checking sites have been implemented as a public health response to the ongoing overdose crisis and the unregulated illicit drug market through a community-based research project called the Vancouver Island Drug Checking Project. In addition to providing anonymous, confidential, and non-judgmental drug checking services with rapid results, the project has conducted qualitative research aimed to better understand drug checking as a potential harm reduction response to the illicit drug overdose crisis and the unregulated illicit drug market (Wallace et al., 2021; Wallace et al., 2020). An analytical framework was utilized to understand the impact substance use stigma has on those accessing drug checking services, as well as those who avoid accessing these services as a direct result of substance use stigma. This study found that the risk of criminalization and the anticipation of being poorly treated appear to be the most significant barriers related to stigma, rather than actually experiencing stigma. Further, it appears the implementation of community drug checking creates tensions that need to be navigated as sites and services balance a hierarchy of substances and stigma; differing definitions of peers; public yet private locations; and, normalization within criminalization. The findings suggest the solution to substance use stigma and drug checking will not come from continuing as we are, but through making changes at all levels (individual, interpersonal, and structural) and thus for all people who access community drug checking.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".