Smallholder Farmers’ Decision to Participate in Vegetable Marketing and the Volume of Sales in West Shewa Zone of Oromia National Regional State, Ethiopia
Bibliographic record
Abstract
This study examines vegetable producers’ market participation and sales volume using cross-sectional data obtained from 385 randomly and proportionately sampled households from West Shewa zone, Oromia region of Ethiopia. Heckman two-step procedure was used to analyse the determinants of participation in vegetables markets and volume of sales during the study period. Probit model shows that education level, distance to nearest market, access to irrigation, use of pesticide and participation in any civic organization significantly affect market participation decision. Further, results from ordinary least squares regression show that sex of household head, land size, distance to farmer training centre, access to irrigation, use of pesticide and participation in civic organization significantly affect the level of market participation of the farm households in vegetable markets. The findings imply that support for female households, improving adult based education, participation in civic organization, infrastructure, access to irrigation and improved inputs are a means to increase vegetable production market participation and sales volume in West Shewa, Ethiopia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".