Community-based Participatory Process Climate Change and Health Adaptation Program for Northern First Nations and
Bibliographic record
Abstract
and Inuit Communities is unique among Canadian federal programs in that it enables community-based participatory research by northern communities. Study design: The program was designed to build capacity by funding communities to conduct their own research in cooperation with Aboriginal associations, academics, and governments; that way, communities could develop health-related adaptation plans and communication materials that would help in adaptation decision-making at the community, regional, national and circumpolar levels with respect to human health and a changing environment. Methods: Community visits and workshops were held to familiarize northerners with the impacts of climate change on their health, as well as methods to develop research proposals and budgets to meet program requirements. Results: Since the launch of the Climate Change and Health Adaptation Program in 2008, Health Canada has funded 36 community projects across Canada’s North that focus on relevant health issues caused by climate change. In addition, the program supported capacity-building workshops for northerners, as well as a Pan-Arctic Results Workshop to bring communities together to showcase the results of their research. Results include: numerous films and photo-voice products that engage youth and elders and are available on the web; community-based ice monitoring, surveillance and communication networks; and information products on land, water and ice safety, drinking water, food security and safety, and traditional medicine. Conclusions: Through these efforts, communities have increased their knowledge and understanding of the health effects related to climate change and have begun to develop local adaptation strategies.
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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 | 0.019 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".