Evaluating the use and intent of drinking water advisories in Atlantic Canada
Bibliographic record
Abstract
Abstract Drinking water advisories (DWAs) are used as a tool for identifying water safety concerns in many jurisdictions. Evidence from previous research demonstrates a lack of improvement in water system operations over time, with an increase in the total number of DWAs in place. DWAs are predominantly issued due to operational concerns within a water system, implying a lack of proactive management measures for preventable issues. Therefore, DWAs represent a chronic issue for many water systems, particularly those lacking resources to implement operational improvements. This study explores DWA characteristics in Atlantic Canada, including frequency and duration, focusing on municipal and private water systems. Seasonality was identified as a trend in DWA issuance in Nova Scotia, and reasons for DWA issuance are largely unchanged over time. Neither of these identified concerns has led to a change in DWA reporting or issuance procedures. Additionally, this study identifies a lack of a common reporting format, leading to the proposal of a template of minimum characteristics for future DWA reporting. Overall, this study highlights deficiencies in the DWA issuance process as a water safety measure and suggests alternative methods for risk management in water systems to alleviate the persistence and prevalence of DWAs in Canada.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".