The neglect of climate change-induced displacement in policy instruments: interrogating Nepal’s climate change policies and adaptation plans
Bibliographic record
Abstract
Climate change has escalated disaster events globally, disrupting local livelihood systems and, at times, causing displacement. There is a growing consensus that climate change policies must address displacement to protect vulnerable communities and their livelihoods. This paper examines the extent to which Nepal’s climate change policies have considered displacement and identifies the key reasons behind its inclusion in – or exclusion from – these policies. It primarily draws on policy analysis, expert interviews and a review of the Local Adaptation Plan of Actions (LAPAs). Findings reveal that while displacement is a significant issue for Nepal, the country’s national and local climate change policy instruments have largely failed to incorporate directly relevant provisions. We find that this failure is linked to policy incoherence and the nature of policy making, which focuses on responding to urgent and immediate climate change impacts. Our analysis also suggests that the neglect of displacement in climate policies stems from a vulnerability risk assessment method that is poorly guided by the estimation of future risk and vulnerability scenarios. There was also a lack of shared understanding among key stakeholders about climate-induced displacement and the adaptive capacity of vulnerable communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".