Determining Canadian water utility preparedness for the impacts of climate change
Bibliographic record
Abstract
Abstract General warming and extreme weather events associated with climate change are expected to negatively impact water utilities. Water utilities will need to adapt to continue providing safe drinking water and wastewater services. In 2012, the Canadian Water and Wastewater Association (CWWA) conducted a survey of 53 water utility officials to understand the expert perceptions of climate change risks and preparedness of Canadian utilities for current and future impacts. Results indicated that there is low awareness among water utility officials (30%) of thepossible impacts of climate change on water utilities, and more than half have not conducted climate change vulnerability assessments (65%) and do not have operational plans to address climate change impacts (56%). Officials from smaller utilities, which are considered to be more vulnerable to impacts, were of those less aware of these risks and reported taking fewer preparedness activities. Efforts to prepare water utilities for climate change impacts in Canada would benefit from education of utility officials about possible climate change risks, encouraging assessments of vulnerabilities, and increased training with new adaptation tools and resources.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 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) | 0.005 | 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".