Assessment of Himalayan Nettle (Girardinia diversifolia) Value Chain Development Interventions: Evidences from Rural Households in the Far Western Nepal
Bibliographic record
Abstract
The Himalayan nettle (Note 1) is a fiber yielding non-timber forest product that has cultural, economic and medicinal values to many ethnic communities residing in the hill and mountain areas of Nepal and India. If the nettle value chain can be strengthened at each node of the chain, then it has high potentiality to uplifting the livelihoods of many poor households in those areas. With this objective, the Himalayan nettle value chain development interventions in the form of promotion of local institutions, enterprise development, product value addition and development, capacity building at the community level and promotion of linkages through private sector engagement were initiated in Darchula, one of the remote districts in far-western Nepal. This paper essentially analyzes the impact of Himalayan nettle value chain development interventions on households’ income from the sale of nettle products. Using propensity score matching (PSM) technique in a cross-sectional data, this study finds that participation in the Himalayan nettle value chain development intervention has positive and significant impact on the households’ annual income from the sale of nettle products. The participating households’ annual income from the Himalayan nettle increases by NPR (Note 2) 2265-2410 than that of non-participating households with similar socio-economic characteristics. The study therefore argues that capacity building and facilitation activities on product development and market linkages are important to help increase productivity and decrease per unit production cost of non-timber forest products like the Himalayan nettle. Value chain development and concentrated market linkages are hence essential to diversify livelihood options for natural resource dependent rural communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".