Vulnerability to Environmental Risks and Effects on Community Resilience in Mid-West Nepal and South-East Pakistan
Why this work is in the frame
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Bibliographic record
Abstract
Nepal and Pakistan face a triple challenge of political instability, weak governance and vulnerability to climate change. Communities are highly vulnerable to floods, landslides and droughts. However, the reasons for their vulnerability are complex and differ from location to location. This study has two objectives. First, we analyze and compare the vulnerability of communities to environmental risks in three districts of Nepal with communities in three districts of Pakistan. While we address environmental exposure and sensitivity, the main focus is placed on adaptive capacity including obstacles to adaptation and maladaptation. Second, we explore how the resilience of communities is affected by the combination of environmental risks and weak governance. To identify common and different attributes between and within the two research regions, we apply a comparative conceptual framework to guide the community level case study research conducted in 2011 and 2012 in the Banke, Dang and Rolpa districts of Nepal, and the Badin, Karachi and Thatta districts of Pakistan. We interviewed a total of 288 respondents, including community members and key informants. Our findings suggest that poor governance is a central obstacle to adaptation in both countries but driven by different factors. Examples of maladaptation to climate change risks include provision of rice which undermines the production of traditional crops in Nepal and a water project in Pakistan exposing local communities to floods. The challenge is to improve relations between governance providers and local communities while addressing consequences of environmental risks, including migration and conflict.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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