Upstream Disaster Management to Support People Experiencing Homelessness
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
The unique context of day-to-day living for people who are chronically homeless or living with housing insecurity puts them at high risk during community disasters. The impacts of extreme events, such as flooding, storms, riots, and other sources of community disruption, underscore the importance of preparedness efforts and fostering community resilience. This study is part of larger initiative focused on enhancing resilience and preparedness among high risk populations. The purpose of this study was to explore critical issues and strategies to promote resilience and disaster preparedness among people who are homeless in Canada. A sample of interviews (n=21) from key informants across Canada was analyzed to explore existing programs and supports for homeless populations. The data was selected from a larger sample of (n=43) interviews focused on programs and supports for people who are at heightened risk for negative impacts during disasters. Qualitative content analysis was used to extract emergent themes and develop a model of multi-level collaboration to support disaster resilience among people who are homeless. The results indicate there is a need for more upstream continuity planning, collaboration and communication between the emergency management sector and community service organizations that support people who are homeless. Prioritization and investment in the social determinants of health and community supports is necessary to promote resilience among this high-risk population. The findings from this study highlight the importance of acknowledging community support organizations as assets in disaster preparedness. Day-to-day resilience is an ongoing theme for people who are chronically homeless or living with housing insecurity. Upstream investment to build adaptive capacity and collaborate with community organizations is an important strategy to enhance community resilience.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.003 |
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