Exploring the Role of Public Health in Climate Change Initiatives and the Mining Industry in Ontario, Canada
Bibliographic record
Abstract
Background: Climate change is a global crisis that is impacting population health. With its significant expansion, the mining industry in Ontario, Canada has the potential to contribute to the development of green energy technologies, but can also threaten the climate and population health. Research has begun to explore the impact of extractive industries on climate change but has not examined the barriers for climate change initiatives and policy implementation in Ontario in relation to population and environmental health. This research aims to address the role public health can play in promoting climate change initiatives and policies in extractive industries in Ontario. \n \nObjectives: The objectives of this research are to (1) understand the role that public health could play in mitigating the impact of Ontario’s mining industry on the environment; (2) understand what barriers might prevent public health from playing a more active role in climate action within the mining industry in Ontario; and (3) explore what key actions could be taken to address barriers to allow public health to take an active role in the extractive industry in Ontario. \n \nMethods: This study employed a qualitative methodological approach using semi-structured interviews as a primary method of data collection. Interviews were conducted with 12 key stakeholders, including policy makers, representatives of public health units, government workers, researchers and not for profit agencies. Data was analyzed utilizing a critical realist lens using inductive, thematic analysis. \n \nFindings: This study displayed the complexity of the government priorities in the green energy transition and opposing viewpoints of environmental and health advocates. The findings suggest that public health should play a larger role in advocating for health to be at the forefront of climate change initiatives in the mining industry in Ontario. It highlighted how to mitigate barriers and tensions to public health interventions while seeking to utilize or implement health frameworks that have not yet been applied in the mining sector in Ontario. \n \nConclusion: There is potentially a role for public health to have in regard to policy creation, advocacy and implementation in public health units across Ontario. Public Health Ontario could be viewed as a body to provide scientific knowledge and evidence for industries and public health units in relation to climate change initiatives and the mining industry. There is a lack of collaboration between industry, health units, government and community. Current regulations and policy do not reflect the needs of surrounding, impacted communities and the climate crisis.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".