Evolving high altitude livelihoods and climate change: a study from Rasuwa District, Nepal
Bibliographic record
Abstract
This study examined local people’s perception of climate change and its impacts on their livelihoods, and identified key opportunities and threats arising in four Village Development Committees in the high mountains of Rasuwa District, Nepal. The local people are still heavily dependent on agriculture and livestock for their food security and livelihoods, despite the involvement of a significant proportion of households in non-agricultural income-generating activities, such as tourist services and labour work in other areas (outmigration). In agriculture, farmers mainly cultivate traditional food crops such as millets, buckwheat, local beans, and barley. They also cultivate rice, potato, and vegetables. Agriculture is mainly rainfed with a few exceptions of micro-irrigation systems fed by springs and snow-melt water. The impacts of climate change are mixed to date: changes in patterns of snowfall and snowmelt, rainfall, and temperatures are having both positive and negative impacts. Households are adapting to this changing climate through changes in their cropping patterns, integration of livestock with agriculture, and adoption of non-farm income activities. There are also new opportunities coming up at the study sites such as new markets for vegetables, traditional crops, and livestock.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".