Improving the feedback loop between community‐ and policy‐level learning: Building resilience of coastal communities in Bangladesh
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
Abstract Building community resilience has been widely recognized as a learning process at multiple societal levels, yet few prior studies have examined the feedback loop between community‐ and policy‐level learning. Following a qualitative research approach, we document experiential and transformative forms of learning from coastal cyclones in Bangladesh that help local community and their institutions mitigating the impact of cyclonic shocks and recovering from disaster‐related losses, both in the shorter and longer term. This study discovers that such community‐level learning (when scaled‐up) as well as learning from policy failure significantly enhanced programmatic interventions, which in turn enhanced community resilience to cyclones and future disasters. However, this feedback loop can be attenuated by multiple factors, such as lack of attention to community‐level learning by policy/decision makers in non‐disaster settings and the presence of a strong vested interest group, may impede learning‐based policy instrumentation. Boundary spanners or organizations can significantly improve the feedback loop, thus enhancing community resilience and improving policy.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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