Self-reported Effects of Water on Health in First Nations Communities in Saskatchewan, Canada: Results From Community-Based Participatory Research
Bibliographic record
Abstract
Water-related health challenges on First Nations reserves in Canada have been previously documented. Our objective was to describe factors associated with self-reported health effects from tap water in 8 First Nations reserve communities in Saskatchewan, Canada. Community-based participatory approaches were used in designing and implementing cross-sectional household surveys. Individual, household, community, and contextual effects were considered in multilevel analysis. Negative health effects from tap water were reported by 28% of households (n = 579). Concerns about environmental factors affecting water quality (odds ratio [OR] = 3.4, 95% confidence interval [CI] = 1.8-6.7), rarely or never drinking tap water (OR = 2.9, 95% CI = 1.3-6.6), insufficient tap water (OR = 3.0, 95% CI = 1.4-6.3), paying for bottled water (OR = 3.2, 95% CI = 1.2-8.7), and dissatisfaction with tap water were associated with self-reported health effects (n = 393); however, the effect of dissatisfaction was modified by respondent age ( P = .03). Quality and availability were associated with perceptions of health effects from drinking water, providing additional information on how ongoing concerns about drinking water influence self-reported health in some First Nations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".