Four core principles to reconcile sociocultural conditions and disaster risk reduction in pursuit of community resilience
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
As environmental risks, particularly climate change, exacerbate vulnerabilities, Disaster Risk Reduction (DRR) has increasingly prioritised community protection. However, communities’ unique and contextual nature often renders top-down risk management efforts unsustainable or ineffective. To address these limitations, the community-based approach (CB) has emerged as a promising alternative. It is grounded in four interdependent principles: local participation, valuing diversity and inclusivity, integrating local and indigenous knowledge, and building local capacities for greater autonomy. Each of its principles benefits each other through a dynamic of interconnection and interdependence, which collectively ensure that DRR strategies are tailored to each community's specific needs, strengths, and sociocultural contexts. By promoting decentralised decision-making, participatory governance, co-production, and social learning, the CB approach aligns DRR efforts with local realities, making them more sustainable and effective. Although challenging to implement due to resource constraints and political dynamics, CB remains a vital pathway for building long-term community resilience in the face of evolving environmental risks. This paper provides a comprehensive framework for aligning DRR strategies with sociocultural conditions, offering practical insights and actionable recommendations to enhance community resilience.
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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 | 0.001 | 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 | 0.001 |
| 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 it