Towards an Ethical Approach to Climate Change and its Health Risks for older adults
Bibliographic record
Abstract
Abstract Climate change is a public health threat that disproportionately impacts certain groups more than others. Getting old is something that most of us will experience during our lifetime, and older adults are among those at elevated risk for adverse impacts due to climate change. As a result, it behooves us as a society to consider how we will approach mitigating climate change impacts on older adults. We must carefully consider what ethical principles underpin the policies and laws that affect older adults, particularly as the world is facing increasing challenges with the distribution of resources. This paper argues for an ethical approach to climate change and older adults that is based on the care-ethic framework developed by Gilligan, Tronto and Fisher using case studies from New Zealand and Italy to illustrate how this framework could be applied.
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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 | 0.079 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.073 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.023 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 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".