Boil, boil, toil and trouble : the trouble with boil water advisories in British Columbia
Bibliographic record
Abstract
Boil water advisories (BWAs) are public notifications of drinking water quality and are used as temporary, precautionary measures to protect the public from possible waterborne illnesses. British Columbia (BC) has among the highest numbers of BWAs and many have been in place for months to years, leading to the concern over their use as a ‘band-aid’ to water treatment and a substitute to action needed for its removal. With lengthier or on-again-off-again BWAs, there is concern that the public will become complacent and not comply with the BWA. Research on BWA is scarce and not much evidence is available to support practical decision making by the two groups of key players responsible for the management of BWAs – health authority officials and water suppliers. Short-term and long-term BWAs from four of BC’s five health authorities were randomly selected for investigation. Interviews of health authority officials and water suppliers were conducted to determine the decision-making process by which BWAs are issued; how BWAs are communicated to the public; and what consequential corrective action is taken after issuing, to progress towards the notification’s removal. A total of 31 BWAs were investigated. The decision-making processes varied considerably from case to case; different factors were considered depending on who was involved and the water system in question. The history of the water system, lack of water treatment, positive bacteriological water sample results and the type of water source were common criteria considered in the decision process. The majority of BWAs were communicated via personal interactions with the members of the public and public postings. Challenges with risk communication, message fatigue and public compliance were identified. Obstacles to the removal of longstanding BWAs included the lack of funding for infrastructure improvements or construction and technical challenges with the geographical remoteness of some small water systems. Solutions that look to improving the overall management of small water systems in BC and that provide necessary guidance to decision-makers, before, during and after the issuing of BWAs, are needed for alleviating some of the challenges faced with BWAs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".