Institutional Engagement Practices as Barriers to Public Health Capacity in Climate Change Policy Discourse: Lessons from the Canadian Province of Ontario
Bibliographic record
Abstract
Public health engagement in the communication, discussion, and development of climate change policies is essential for climate change policy decisions and discourse. This study examines how the existing governance approaches impact, enable, or constrain the inclusion, participation, and deliberation of public health stakeholders in the climate change policy discourse. Using the case study of the Canadian Province of Ontario, we conducted semi-structured, key informant interviews of public health (11) and non-public health (13) participants engaged in climate change policies in the province. The study results reveal that engagement and partnerships on climate change policies occurred within and across public health and non-public health organizations in Ontario. These engagements impacted public health’s roles, decisions, mandate, and capacities beyond the climate change discourse; enabled access to funds, expertise, and new stakeholders; built relationships for future engagements; supported knowledge sharing, generation, and creation; and advanced public health interests in political platforms and decision making. However, public health’s participation and deliberation were constrained by a fragmented sectoral approach, a lack of holistic inter-organizational structures and process, political and bureaucratic influences, irregular and unestablished communication channels for public health integration, and identities and culture focused on functions, mandates, biased ideologies, and a lack of clear commitment to engage public health. We conclude by providing practical approaches for integrating public health into climate change discourse and policymaking processes and advancing public health partnerships and collaborative opportunities.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.046 | 0.016 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".