Bibliographic record
Abstract
The effects of intergenerational trauma, colonization, and genocide are numerous and include higher rates of health disparities such as substance use. The purpose of this research is to identify areas of resilience and empowerment in addiction recovery among Indigenous Peoples living in Saskatchewan, Canada. Community approval was sought from the Community Research Advisory Committee and network sampling was used for co-researcher recruitment. Co-researchers included individuals in sustained recovery of 12 months or more (n=5), Elders and Knowledge Keepers (n=2), and physicians (n=1). Indigenous story-telling was used during one-on-one interviews with co-researchers via phone call. Thematic analysis resulted in 12 themes identified from the interviews. These include trauma, systemic racism, gaps in care, role of physicians, health care needs, confidence, family support, peer support, spiritual care, resilience, culture and Elders, and words of advice. Co-researchers identified many areas of resilience and empowerment among Indigenous Peoples in addiction recovery including spirituality and prayer, and connection to culture, Elders, and traditional healing practices. Connecting with peers and family members who have been through similar recovery journeys and creating long-term, trusting relationships with physicians is also important for recovery. Development of addiction treatment models should consider the impact of colonization on substance use and integrate strengths-based approaches to care. It may also be useful to include connection to culture and traditional spirituality as methods to improve resilience and empowerment among Indigenous Peoples.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.083 | 0.015 |
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".