Advancing knowledge and increasing capacity to address climate-driven infectious diseases in Canada
Bibliographic record
Abstract
(PCF) was adopted in December 2016. This collaboratively developed federal, provincial and territorial report documents Canada's plans to meet its Paris Agreement commitments and stimulate Canada's economy. This PCF identifies a series of actions that will be addressed through four key pillars: pricing carbon pollution; complementary measures to reduce emissions; adaptation and climate resilience; and enabling economic growth through clean technology, innovation and jobs. Within the PCF, protecting and improving human health and well-being was included as an essential aspect of adaptation and climate resilience. New actions in the PCF included greater federal action to prevent illness from extreme heat events led by Health Canada and to reduce the risks associated with climate-driven infectious diseases led by the Public Health Agency of Canada (PHAC). Public health and climate change intersect in the area of infectious disease. To deliver on its new commitments in the PCF, PHAC established the Infectious Diseases and Climate Change (IDCC) program, and a new grants and contributions fund. The program has three principal aims: to increase PHAC's capacity to respond to the increasing demands posed by climate-driven infectious diseases; to provide Canadians access to timely and accurate information to better understand their risks and take measures to prevent infection; and to improve the adaptability or resiliency to the health impacts of infectious diseases through surveillance and monitoring, increased laboratory diagnostic capabilities, and access to education and awareness tools. In the first year of the IDCC Fund, a number of projects on monitoring and surveillance and on education and awareness have been approved. In collaboration with our stakeholders as well as governments at all levels and in all provinces and territories, PHAC will continue to work to raise awareness about the effects of climate change on the prevalence of infectious diseases and help Canadians to prepare for the anticipated and unanticipated impacts.
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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 | 0.017 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".