Process and Outcome of Community Engagement Event on Substance Use and Addiction Risks Facing Their Immigrant Communities in Regina, Saskatchewan
Bibliographic record
Abstract
Canada is a significant destination for immigrants who are drawn from different ethnic and cultural backgrounds some of whom have a hidden risk for substance use disorders due to acculturation stress and are not screened for risks of substance use or addiction when considering medical admissibility. Not surprisingly, healthcare providers in Regina are reporting a noticeable increase in substance use among immigrants. These immigrants experience barriers in seeking substance use prevention and treatment services due to diverse challenges: stigma, shame, and lack of knowledge of existing services. Considering the discussed challenges and risks of substance use disorders in immigrant communities, creating a safe space for discussing these topics is urgent. To understand and address these challenges, a connection grant from the Saskatchewan Health Research Foundation (SHRF) to mobilize immigrant communities in Regina to explore substance use issues and their impact on the community was sought and received. Subsequently, a Zoom knowledge-sharing event brought settlement agency stakeholders together to deliberate issues on substance use and addiction faced by immigrants in Regina, Saskatchewan. The Zoom session included presentations on immigrants and substance use from the clinical, community, and lived experience perspectives of immigrants. Because of the challenges and risks, this community consultation process revealed that acculturation stress and the ease of obtaining socially acceptable substances fuel substance use and addiction among immigrants in Regina; this is further exacerbated by the lack of programming available to prevent and reduce the risks of substance use in this population. A team of knowledge keepers with lived experiences, service providers, and researchers was assembled to explore substance use and addiction among immigrants. This manuscript reports the process of community engagement to identify solutions to this budding issue. The strengths, challenges, and lessons learned are identified.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".