Climate change and heatwaves: Improving Ontario’s harmonized heat warning and information system
Bibliographic record
Abstract
Created in 2015, Ontario’s Harmonized Heat Warning and Information System (HWIS) has never been evaluated for its processes and implementation. This paper evaluated the HWIS’s processes using a guidance report published by the World Meteorological Organization and World Health Organization. It also evaluated public health units’ implementation of the HWIS using information found on their websites. The results showed the HWIS lacks monthly threshold values, evaluation processes, and a wider action plan. In the implementation of the HWIS, public health units have failed to post on their websites all 15 heat health messages and locations and hours of local interventions. Six recommendations are made to Public Health Ontario, public health units, and Ontario Ministry of Health to improve on the processes and implementation of the HWIS. As climate change increases the frequency and intensity of heatwaves, an improved HWIS can reduce the incidence of heat-related illness and deaths in Ontario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".