Comparative economic analysis of potato production in Western Bhutan-conventional versus in-conversion to organic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bhutan has embraced an organic vision to promote sustainable agricultural practices, aiming to improve food security, alleviate poverty, reduce import dependency, and improve rural livelihoods. To address challenges faced in real-world farming scenarios and its associated costs and benefits, this study compared the economic performances of potato production in conventional and in-conversion to organic farming systems under farmers’ actual practices and conditions. Experimental trials were conducted in Kumbu Village in Gangtey under Wangdue Phodrang District, covering 0.29 and 0.53 hectares for conventional and in-conversion to organic farms, respectively. The benefit-cost ratio was used to assess the profitability, while yield estimates were obtained using the crop-cut method. An independent sample t-test assessed yield differences, and tuber size was analyzed using a two-way ANOVA. Findings revealed productivities of 21,093.75 kg ha−1 for conventional and 14,801.59 kg ha−1 for in-conversion to organic farms. Conventional farms gained a net income of 51,842.33 Nu ha−1 while in-conversion to organic farms incurred a net loss of −294,052.69 Nu ha−1. The benefit-cost ratio was 1.18 for conventional and 0.45 for in-conversion to organic farms. The study recommends policy interventions such as subsidies, market access, and targeted training and awareness programs to support farmers in an effective transition to organic farming.
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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 | 0.002 |
| 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 it