Assessing the Impact of Educational Levels and Agricultural Practices on Apple Production in Jumla District: A Comparative Study of Farmer Knowledge, Tree Age, and Varietal Diversification
Bibliographic record
Abstract
This study investigates key factors influencing apple production in the Jumla region of Nepal, a region recognized for its apple cultivation.Using survey data collected from 50 farmers across diversed municipalities, the analysis focuses on the impact of farmer demographics (sex and education level), tree age, and geographic location on apple yield, measured by average apple weight per tree.The findings indicate that while male farmers exhibit a slightly higher average apple weight (26.64 kg compared to 25.50 kg for female farmers), a primary education (27.04 kg) level correlates more strongly with increased productivity than secondary (21.83 kg), higher (24.25 kg), or being illiterate (16.94 kg).Tree age significantly affects yield, with trees older than 15 years demonstrating the highest average weight (38.20 kg).Geographical variations reveal that specific municipalities, notably Sinja (35.02 kg), outperform others, suggesting the influence of local environmental conditions and farming practices.This study provides valuable insights for designing targeted agricultural policies and extension services that can enhance apple farming practices and improve overall yields in the region.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".