Seed and Information Exchange through Social Networks: The Case of Rice Farmers of Indonesia and Lao PDR
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
The study investigates the structure of information exchange among men and women farmers who were involved in participatory varietal selection (PVS) on submergence-tolerant varieties in pilot communities in Lao PDR and Indonesia. The paper shows that network relationships influence the dissemination of new information on seed. In their decisions to adopt new rice varieties, farmers are strongly influenced by their kin and friends. The study also investigated social networks by gender in order to gain greater insights into how gender inequalities influence the effectiveness of social capital through social networks. Results show that information opportunities of men and women vary in terms of exposure to and control of information. These differences are mainly influenced by their social and cultural setting in rice farming systems and communities. The paper shows that gender should be accounted for when investigating the determinants of social networks. Factors affecting social networks differ by gender, and also across countries. For instance, older males in Indonesia tend to have larger social networks. Women who belong to large farming households tend to have bigger social networks. Generally, having more relatives is a good opportunity to increase social networks for males and females.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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