Changing climate policy paradigms in Bangladesh and Nepal
Bibliographic record
Abstract
The aim of this article is to explain and compare the changes in climate policy paradigms (CPPs) of Bangladesh and Nepal. Climate policies are shaped by the underlying CPPs that refer to a dominant set of prevailing and institutionalized ideas and strategies to reduce the impacts of climate change. We focus the analysis on the timeframe between 1997 and 2016, using policy documents (n = 46) and semi-structured interviews (n = 43) with key policy actors. We find that in both countries several CPPs have emerged: disaster risk reduction, climate change adaptation, mainstreaming, and localized action for adaptation. In Bangladesh, specific policy goals and instruments for each CPP have emerged, whereas in Nepal the government has been struggling to develop specific policy instruments to implement the paradigms. We conclude that competing CPPs currently exist which creates diversified policy responses to climate change impacts in both countries. This ‘layering’ of different CPPs can be attributed to drivers such as unstable political situation, lack of financial support, influence of national and international non-governmental organizations and global policy frameworks. The findings in our study are relevant to further discussions on how to design future climate policy responses to adapt to climate change.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".