Governance Challenges in Addressing Climatic Concerns in Coastal Asia and Africa
Bibliographic record
Abstract
Coastal people, especially those living within deltaic areas, encounter major climatic concerns which affect their livelihoods. To cope with this problem, different types of planned adaptation strategies have been implemented guided by laws, policies and programs. However, these guiding documents sometimes fall short of addressing the needs of climate-affected people, especially in natural resource-dependent societies in Asia and Africa. Based on this premise, this paper sought to evaluate the effectiveness of existing policy documents which affect the lives of people living in one large delta (Ganges-Brahmaputra-Meghna in Bangladesh), two medium-sized deltas (Indian Bengal delta—part of the Ganges-Brahmaputra-Meghna and Mahanadi in India), and a small-sized delta (Volta in Ghana). The study followed a mixed methods research design, which included desktop analyses of policies, laws and programs, a questionnaire survey conducted among individuals who played various roles in the policy and legal development processes at national and local levels and focus group discussions at the community level in the three countries. National laws, policies and programs were assessed in the context of climate change adaptation through three lenses: human rights, natural resource management and disaster response. Findings of this paper reveal that the existing documents have some strengths to promote adaptation, although they have some major limitations that cause concerns among the delta communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| 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 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".