Research to support public health action on heat and health - 20th Annual John K. Friesen Conference - Growing Old in a Changing Climate: Exploring the Interface Between Population Aging and Global Warming (2011)
Bibliographic record
Abstract
This video clip comprises the four presentations of Panel Session 2, “Mitigation and Prevention Strategies: Lessons Learned on the Front Lines” held at the 20th Annual John K. Friesen Conference, "Growing Old in a Changing Climate: Exploring the Interface Between Population Aging and Global Warming," MAY 25-26, 2011, Vancouver, BC. Dr. Tom Kosatsky " Research to support public health action on heat and health" - Research from various disciplines can promote, support and contextualize public health action to prevent illness and death related to hot weather. Examples are sociological assessments of who died during the 1995 Chicago heat wave, experimental evidence of age-related differentials in the physiology of the heat response, occupational medicine research into the time course of heat acclimatization, models of the cooling capacity of room fanning versus water misting of occupants, and spatial overlays of attributes of heat vulnerability over a city or region. During this presentation I will review projects to which I have contributed since 2003: the PHEWE study of mortality attributable to heat in 15 European cities; surveys of city and country preparedness for heat in Europe; the influence of local greenery on where hot day deaths occur in Montreal; knowledge, attitudes and practices of Montreal residents with chronic heart and lung disease around hot weather preparedness and response; changes in heat susceptibility from 1985-2010 in Vancouver; and, observed shifts in patterns of mortality during the 2009 Vancouver heat event.\n \nWe also gratefully acknowledge a grant from the SFU Library's Scholarly Digitization Fund for videography and post-production editing.\n \nSee webpage for more information on the 20th Annual John K. Friesen Conference: http://www.sfu.ca/grc/friesen/friesen2011/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".