www.mdpi.com/journal/ijerph Article Risk Factors Associated with the Choice to Drink Bottled Water and Tap Water in Rural Saskatchewan
Bibliographic record
Abstract
Abstract: A cross-sectional study investigated risk factors associated with choices to drink bottled water and tap water in rural Saskatchewan. Of 7,500 anonymous postal questionnaires mailed out, 2,065 responses were analyzed using generalized linear mixed models. Those who reported a water advisory (p < 0.001) or living in the area for 10 years (p = 0.01) were more likely to choose bottled water. Those who reported tap water was not safe to drink were more likely to choose bottled water, an effect greater for those who had no aesthetic complaints (p ≤ 0.001), while those with aesthetic complaints were more likely to choose bottled water if they believed the water was safe (p < 0.001). Respondents who treated their water and did not use a community supply were more likely to choose bottled water (p < 0.001), while those who did not treat their water were more likely to choose bottled water regardless of whether a community supply was used (p < 0.001). A similar pattern of risk factors was associated with a decreased likelihood of consuming tap water daily; however, the use of a community water supply was not significant. Understanding the factors involved in drinking water choices could inform public health education efforts regarding water management in rural areas.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".