A pathway to initiate bottom-up community-based disaster risk reduction within a top-down system: The case of China
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
In China, as in other countries, inadequate knowledge of local vulnerability and hazard characteristics, and a rapidly industrialising society render enhancing resilience to natural disasters particularly challenging.This is particularly evident in rural areas with limited human and financial resources available for disaster risk reduction initiatives.The Chinese government institutionalized a top-down community-based disaster risk reduction (CBDRR) system to ensure that the capacity of communities would be enhanced effectively.In the long run, a top-down management style often undermines local capacities and vernacular DRR (disaster risk reduction) knowledge.There is a need to recognize the importance of communities as complex and dynamic entities in reducing disaster risks.Adopting participatory action research (PAR), this in-progress exploratory study examines a pathway to initiate bottom-up CBDRR within China's top-down institutional setting.Through PAR, the study of a rural village in Shaanxi Province shows that bottom-up initiatives can complement the existing system.Its current progress demonstrates the potential for using a transdisciplinary perspective to initiate CBDRR in China, where both top-down and bottom-up approaches, come together alongside different disciplines to increase a rural community's disaster 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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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