Exploring the Ethical Dimensions of All-Hazards Public Health Emergency Preparedness in Canada
Bibliographic record
Abstract
Introduction: With increasing disaster risks from extreme weather, climate change, and emerging infectious diseases, the public health system plays a crucial role in community health protection. The disproportionate impacts of disaster risks demonstrate the need to consider ethics and values in public health emergency preparedness (PHEP) activities. Established PHEP frameworks from many countries do not integrate ethics into operational approaches. Aim: To explore the ethical dimensions of all-hazards public health emergency preparedness in Canada. Methods: A qualitative study design was employed to explore key questions relating to PHEP. Six focus groups, using the Structured Interview Matrix (SIM) format, were held across Canada with 130 experts from local, provincial, or federal levels, with an emphasis on local/regional public health. An inductive approach to content analysis was used to develop emergent themes, and iteratively examined based on the literature. This paper presents analyses examining the dimensions of ethics and values that emerged from the focus group discussions. Results: Thematic analysis resulted in the identification of four themes. The themes highlight the importance of proactive consideration of values in PHEP planning: challenges in balancing competing priorities, the need for transparency around decision-making, and consideration for how emergencies impact both individuals and communities. Discussion: Lack of consideration for the ethical dimensions of PHEP in operational frameworks can have important implications for communities. If decisions are made ad-hoc during an evolving emergency situation, the ethical implications may increase the risk for some populations, and lead to compromised trust in the PHEP system. The key findings from this study may be useful in influencing PHEP practice and policy to incorporate fairness and values at the core of PHEP to ensure readiness for emergencies with community health 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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.034 | 0.016 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".