Disease-related stigma among people who inject drugs in Toronto amidst the COVID-19 pandemic
Why this work is in the frame
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Bibliographic record
Abstract
Background: Stigma overwhelmingly affects people who inject drugs. The COVID-19 pandemic posed unique challenges for people who inject drugs, who are already stigmatized as being "dangerous and spreading disease." The present study explored ways in which stigma was experienced by a sample of people who inject drugs in Toronto, Canada following COVID-related public health precaution measures. Methods: = 24) recruited from supervised consumption sites in Toronto, Canada. The semi-structured interview guide focused on the impact of COVID-19 on participants' health and social well-being. Interviews took place six-months after initial COVID-19 precautions (September-October 2020). We used thematic analysis to examine findings, with stigma being an emergent theme. Results: Participants described heightened acts of stigma after COVID-19 restrictions were implemented, including feeling treated as "diseased" and the cause of COVID-19's spread. They reported being less likely to receive emergency care during events such as overdoses. Participants perceived increased disease-related stigma evident through actions of stigma, including amplified dehumanization by the public, others avoiding all contact with them, and more discrimination by police and hospital systems. Conclusion: Participants provided specific examples of how stigmatizing behaviors harmed them after COVID-19 precautions began. It is plausible that stigma contributed to the dramatic increase in fatal overdoses, difficulty accessing housing, and further difficulty accessing needed healthcare in our setting. Integrating evidence-based harm reduction approaches in areas where stigma is evident might offset harms stemming from disease-related stigma and mitigate these harms during future public health emergencies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it