When ageing and disasters collide: lessons from 16 international case studies
Bibliographic record
Abstract
Sixteen case studies examined the impact of various natural disasters and conflict-related emergencies on older people, the strengths and gaps in emergency planning, response and recovery, and the contributions older people made to their families and communities. Case examples were chosen from both developed and developing countries. Older persons suffered disproportionate impacts in several cases. Regardless of the country's level of prosperity, those most affected tended to be economically disadvantaged, disabled or frail, women, socially isolated, or caregivers of family members. Emergency responders were often not aware of distinct needs or abilities of older persons and not equipped to respond appropriately. The best emergency practices recognised and included specific needs within mainstream efforts and integrated older persons in community planning, response and recovery activities. This paper presents the 'lessons learned' from these case studies and makes the case for greater attention to this segment of the population in emergency management.
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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 | 0.023 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".