Rural Older Adults in Disasters: A Study of Recovery From Hurricane Michael
Bibliographic record
Abstract
OBJECTIVE: This study aims for a greater understanding of how older adults (age 65 and older) in Jackson County, Florida, are prepared for and cope with the effects of a natural disaster. METHODS: A multidisciplinary, international research team developed a survey examining: (1) resources available to individuals aged 65+ in rural communities for preparing for a disaster; (2) challenges they face when experiencing a disaster; and (3) their physical, social, emotional, and financial needs when it strikes. The survey was administered with older adults (65+) in Jackson County, Florida, following Hurricane Michael in 2018. The descriptive, multivariate logistic, and linear regression analyses were performed to examine the relationship between respondents' demographic information and needs, concerns, and consequences of disaster. RESULTS: = 139) rural community-dwelling older adults rely on social support, community organizations, and trusted disaster relief agencies to prepare for and recover from disaster-related events. CONCLUSIONS: Such findings can be used to inform the development of new interventions, programs, policies, practices, and tools for emergency management and social service agencies to improve disaster preparedness and resiliency among older populations in rural communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".