Determinants of market participation decision by smallholder haricot bean (<i>phaseolus vulgaris</i> l.) farmers in Northwest Ethiopia
Bibliographic record
Abstract
Current knowledge on product marketing in Ethiopia is poor and inadequate for designing and implementing policies to overcome problems in the marketing system. This study was conducted to identify the factors influencing the market participation decision of smallholder haricot bean (Phaseolus vulgaris L.) farmers in Northwest Ethiopia. Survey data were collected from 312 smallholder farmers and analyzed using Heckman’s two-step econometric model that estimates probit model in the first step and regression model with the parameters estimated using the Ordinary Least Squares (OLS) method in the second step. The educational status, non-farm income from nonfarm employment, number of extension contacts, gender, improved seed use, chemical fertilizer, and farmers' perception of land degradation were the significant variables affecting the market participation decision of smallholder farmers. The amount of haricot bean output supplied to the market were influenced by age, experience, livestock holding, nonfarm income, extension contacts, gender, market access, and membership in marketing association. Participation in the market can be improved by providing training and education regarding the production and marketing of haricot bean output and increasing farmers' contact with extension agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".