Promoting Older Adults’ Engagement in Disaster Settings: An Introduction to the Special Issue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Globally, surging extreme events and the escalating aging population present ongoing and severe challenges to the full spectrum of international community development (for example, social, health, and economic) (Dee 2024 ). Over the past 20 years, climate-induced and environmental disasters worldwide have caused over 1.3 million casualties and left more than 4.4 billion people injured, homeless, and/or in need of emergency assistance, with total direct economic losses approaching USD 3 trillion (UNDRR 2018 ). The rising human and economic costs have compelled international communities to prioritize resilience enhancement. Furthermore, the United Nations (UN 2019 ) reported that the global population of adults aged 65 and older will almost double from 9% in 2019 to 16% in 2050. Some countries, such as Greece, Korea, and Japan, have an even faster aging rate than the global average (World Economic Forum 2020 ).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it