Examining the public health implications of drinking water-related behaviours and perceptions: A face-to-face exploratory survey of residents in eight coastal communities in British Columbia and Nova Scotia
Bibliographic record
Abstract
In Canada the quality of drinking water and its availability are a reflection of where one lives. Coastal communities, which are particularly susceptible to boil water advisories, present an understudied opportunity to understand drinking water–related behaviours and perceptions. How public health practitioners determine actions needed to prevent water-borne illness is a key factor in the public adopting messaging and/or employing behavioural change. This study involved face-to-face surveys with residents in eight coastal communities in British Columbia and Nova Scotia. All communities had recent histories of boil water advisories and/or water shortages. The findings have significant implications for public health practice seeking to reduce the incidence of water-borne diseases. For example, the respondents had a limited sense of risk of exposure to water-borne illness. This serves as a challenge for public health professionals who are tasked with educating residents about the health benefits and risks associated with drinking tap water, wherein coastal residents not concerned with water quality/availability may view this information as unnecessary. Generally, obtaining a deep understanding of place-based knowledge around health-related issues, as done here, has the potential to impact future policy and management-level decisions and lead to meaningful integration of local perspectives.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".