Traditional activities and general and mental health of adult Indigenous peoples living off-reserve in Canada
Bibliographic record
Abstract
Introduction: We examined associations between traditional Indigenous activities and self-perceived general and mental health in adult Indigenous persons living off-reserve in Canada using the 2012 and 2017 Aboriginal Peoples Surveys (APS), the two most recent datasets. We utilized four traditional Indigenous activities including hunting, making clothes or footwear, making arts or crafts, and gathering wild plants to investigate these self-reported data. Methods: Data from 9,430 and 12,598 respondents from the 2012 and 2017 APS, respectively, who responded to 15 questions concerning traditional activities were assessed using multivariable logistic regression to produce odds ratios (OR) and 95% confidence intervals (CI). Covariates included age, sex, education-level, income-level, Indigenous identity, residential school connection, ability to speak an Indigenous language, smoking status, and alcohol consumption frequency. Results: Using the 2012 APS, clothes-making was associated with poor self-reported general (OR = 1.50, 95%CI: 1.12-1.99) and mental (OR = 1.59, 95%CI: 1.14-2.21) health. Hunting was associated with good mental health (OR = 0.71 95%CI: 0.56-0.93). Similarly, 2017 analyses found clothes-making associated with poor general health (OR = 1.25, 95%CI: 1.01-1.54), and hunting associated with good general (OR = 0.76, 95%CI: 0.64-0.89) and mental (OR = 0.69, 95%CI: 0.58-0.81) health. Artmaking was associated with poor general (OR = 1.37, 95%CI: 1.17-1.60) and mental (OR = 1.85, 95%CI: 1.58-2.17) health. Conclusion: Hunting had protective relationships with mental and general health, which may reflect benefits of participation or engagement of healthier individuals in this activity. Clothes-making and artmaking were associated with poor general and poor mental health, possibly representing reverse causation as these activities are often undertaken therapeutically. These findings have implications for future research, programs and policies concerning Indigenous health.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".