Livelihood vulnerability to climatic stresses: A study of the northeastern flood plain communities of Bangladesh
Bibliographic record
Abstract
Climatic stress vulnerability has cross-scaler influences on development interventions, particularly in developing countries.While most of climate adaptation plans and interventions are developed at national or international scales, relatively little attention has been paid to incorporate the contextual properties of climate vulnerability in adaptation-related decision making.Focusing on vi CONTRIBUTIONS TO KNOWLEDGEThis dissertation provides novel empirical insights in support of developing better contextualized climate change adaption planning and policy processes in the northeastern floodplains of Bangladesh.Chapter 2• Using a systematic review approach, I assess the historical evolution of climate change research, existing research gaps and their implications for public policy in Bangladesh.Most research has been undertaken at a national scale, although the need for local-level studies is well acknowledged.Multidisciplinary studies were concentrated in six main groups: socio-economic, environmental conservation, technological innovation and environmental risks, health impacts and impacts on fish resources.The northeastern floodplain is the most understudied area in Bangladesh.Chapter 3• Using empirical evidence, I identify that local changes can alter a climatic event to a stress, which would not be represented in local-level climate models.While both socioeconomic and climatic factors are considered in explaining multiple exposures, very little is known about how the local bio-physical changes intensify a climatic event to a stress.I identify land use practices, resource types and their uses can serve to constrain the adaptation measures available to affected communities.I also find that climatic stress perceptions among community members vary with local innovations and practices.vii Chapter 4• I present and test a methodological approach designed to better explain the adaptation measures taken by community members to sustain their livelihoods in response to climatic stresses.I find that community members organize, transform, and combine their livelihood assets to reduce climate sensitivity through generating non-natural resource dependent activities and intensifying natural resource uses.I also identify a strong role for external supports provided either by government, non-government organizations or market mechanisms.Chapter 5• Assessing climate change-focused policy making and institutional adaptation in Bangladesh, I find that the government has made significant advancement in establishing institutional structures that can support adaptation actions.Evaluating local communities' responses to government interventions, I find that discrepancies still remain between national adaptation plans and local demands, which results from insufficient knowledge on climatic impacts in local level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".