Drought Sensitivity of Municipal Water Supply Systems in Ontario
Bibliographic record
Abstract
The sensitivity of municipal water systems to drought was explored in 1999, with particular attention to major urban centres in Ontario’s Toronto-Niagara Region. A framework of sensitivity was developed, recognizing both water system characteristics, such as type of water source and storage capacity, and situational factors, such as population growth rates. The framework was developed from the literature, scoping interviews with officials in six southern Ontario municipalities, and in-depth interviews and document analysis in three case study municipalities: City of Toronto, Regional Municipality of York, and Regional Municipality of Niagara. The framework suggests that system characteristics that increase sensitivity to drought include groundwater and river water sources, older and/or poorly maintained water system components, and limited storage capacity relative to demand. Situational factors increasing drought sensitivity include rapid population growth and lack of demand management measures. Conversely, system characteristics that reduce sensitivity include interconnection of distribution systems and an abundant water source. Suggestions are offered for utilizing the framework as a checklist for assessing drought sensitivity of municipal water systems.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".