Effect of Socio-Economic on Farmers' Decisions in Using Lowland Rice Production Inputs in Indonesia
Why this work is in the frame
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Bibliographic record
Abstract
In Indonesia, rice was produced by small-scale farmers where yields were still generally low. This was because small-scale farmers still used poor quality seeds and unbalanced fertilizers. Therefore, this research aimed to analyze the socio-economic factors that affected the adoption of quality seeds in lowland rice farming and the use of fertilizers on quality seeds. This research used a double-hurdle model to answer the objectives of research and used 329 farmings which were selected randomly in Central Sulawesi Indonesia. The results show that the gender variable only affected the use of fertilizer on quality seeds. Education, access to credit, sources of income (income diversification), access to extension, meetings with farmer groups were found to be positively correlated with the decision to adopt quality seeds in lowland rice farming and use of fertilizers to quality seeds, while the number of dependents of the household head was negatively correlated. The land area of lowland rice was positively correlated with the adoption of quality seeds in lowland rice farming but negatively correlated with the number of fertilizers used for quality seeds. Based on these findings, the role of extension workers and farmer groups was needed in disseminating quality seeds, and through credit institutions, it was necessary to provide credit facilities to rice producers (farmers) so that rice productivity could be increased.
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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 | 0.001 | 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 it