Community Disaster Resilience and the Rural Resilience Index
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
This article describes the development and field testing of the Rural Resilience Index (RRI), an applied disaster resilience assessment index for use in rural and remote communities. The index was generated as part of the Rural Disaster Resilience Project. This community-centered action research project was designed to respond to the global emphasis on increasing the capacity of all communities, large and small, to meet the growing challenge of disasters, climate change, and other threats. The goals of the project were to produce resilience assessment and planning tools that could be used by communities to generate locally relevant data on their current resilience and be able to monitor and enhance their resilience over time. This article describes the development and field testing of the RRI, which is designed as a user-friendly, process-based, qualitative resilience assessment tool. The RRI emphasizes the value of citizen engagement in resilience planning and a whole-of-community approach to resilience addressing issues such as the quality and availability of local resources, expertise, skills, and services; governance issues; economic and employment issues; culture; disaster preparedness; and emergency management planning.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 it