Economics of Production and Marketing for French Bean in Kalikot District (Tilagupha Municipality), Nepal
Bibliographic record
Abstract
The research, conducted from February to July 2023 in Tilagupha municipality, Kalikot, Nepal, focused on French bean production and marketing.Sixty participants were surveyed using a stratified sampling technique.Primary data, gathered through household surveys, interviews, and field visits revealed insights into the agricultural landscape.Bean cultivation occurs once a year on small farms averaging 17.16 ropani, with 30.33% of land dedicated to beans.The average yield was 658.2 kg/ha, below the reported ADO Kalikot figure (1477 kg/ha).Production cost was Rs. 21,054.7 per ropani, with a return of Rs. 75,240 and a benefit-cost ratio of 1.20.Most producers (61.3%) were satisfied with bean prices.Challenges included diseases, pests, lack of irrigation, and limited marketing information, obtained mostly from neighbors (94.8%).The average retail price was Rs. 250 per kg, with a marketing margin of Rs. 78.34 per kg.Lack of market information was a significant issue in bean marketing.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".