Analysis of Factors Influencing Market Participation of Smallholder Bean Farmers in Nyanza District of Southern Province, Rwanda
Bibliographic record
Abstract
Rwanda remains trading very low volume of beans inside the country and across borders thereby becoming unable to meet national and international demands. This is exacerbated by low market participation of bean growers. This study assessed factors that influence market participation and extent of participation among bean growers in Nyanza district. Probit model was used to analyze the factors influencing market participation among bean growers while the extent of market participation was analyzed using Tobit model. The probit results indicated that factors that positively and significantly influenced the probability of farmers to participate in output market were bean quantity produced, market experience, and access to credit while factors that negatively and significantly influenced market participation decisions included distance to nearest market, age and access to off-farm activities. Tobit results revealed that factors that were found to have positive statistical significant impact on the extent of market participation were bean quantity produced, marketing experience and selling price. Contrary to earlier expectation, land size was found to have negative significant impact on the quantity of bean marketed. This is possibly an indication that the increased household’s participation in output market is a function of farm productivity too.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".