Good governance and local level policy implementation for disaster-risk-reduction: actual, perceptual and contested perspectives in coastal communities in Bangladesh
Why this work is in the frame
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Bibliographic record
Abstract
Purpose Despite Bangladesh's great strides in formulating disaster management policies following the principles of good governance, the degree to which these policies have successfully been implemented at the local level remains largely unknown. The objectives of this study were two-fold: (1) to examine the roles and effectiveness of local-level governance and disaster management institutions, and (2) to identify barriers to the implementation of national policies and Disaster-Risk-Reduction (DRR) guidelines at the local community level. Design/methodology/approach Between January 2014 and June 2015 we carried out an empirical investigation in two coastal communities in Bangladesh. We employed a qualitative research and Case Study approach, using techniques from the Participatory Rural Appraisal toolbox to collect data from local community members as well as government and NGO officials. Findings Our study revealed that interactive disaster governance, decentralization of disaster management, and compliance by local-level institutions with good governance principles and national policy guidelines can be extremely effective in reducing disaster-loss and damages. According to coastal community members, the local governments have generally failed to uphold good governance principles, and triangulated data confirm that the region at large suffers from rampant corruption, political favoritism, lack of transparency and accountability and minimal inclusion of local inhabitants in decision-making – all of which have severely impeded the successful implementation of national disaster-management policies. Research limitations/implications While considerable research on good governance has been pursued, our understanding of good disaster governance and their criteria is still poor. In addition, although numerous national disaster management policy and good governance initiatives have been taken in Bangladesh, like many other developing countries, the nature and extent of their local level implementation are not well known. This study contributes to these research gaps, with identification of further research agenda in these areas. Practical implications The study focuses on good disaster governance and management issues and practices, their strengths and limitations in the context of cyclone and storm surges along coastal Bangladesh. It offers specific good disaster governance criteria for improving multi-level successful implementation. The paper deals with International Sendai Framework that called for enhancement of local level community resilience to disasters. Thus, it contributes to numerous policy and practice areas relating to good disaster governance. Social implications Good disaster governance would benefit not only from future disaster losses but also from improved prevention and mitigation of natural hazards impact, benefiting society at large. Improvement in knowledge and practice in disaster-risk-reduction through good governance and effective management would ensure local community development and human wellbeing at the national level. Originality/value The failure of local-level government institutions to effectively implement national disaster management and resilience-building policies is largely attributable to a lack of financial and human resources, rampant corruption, a lack of accountability and transparency and the exclusion of local inhabitants from decision-making processes. Our study identified the specific manifestations of these failures in coastal communities in Bangladesh. These results underscore the vital need to address the wide gap between national DRR goals and the on-the-ground realities of policy implementation to successfully enhance the country's resilience to climate change-induced disasters.
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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 | 0.000 | 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 | 0.001 |
| 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