Factors Affecting the Choice of Marketing Channel by Vegetable Farmers in Swaziland
Why this work is in the frame
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Bibliographic record
Abstract
<span style="font-family: Times New Roman; font-size: small;"></span><p>Vegetables as a group of horticultural crops are important for their contribution as an income support to a large proportion of the rural households. However, enhancing vegetable farmers to reach markets and actively engage in the markets is a key challenge influencing vegetable production in Swaziland. The perishable nature of vegetables necessitates effective marketing channels. The aim of this paper was to investigate factors affecting farmers’ choice of marketing channels using survey data gathered during the 2011 production season. Data were collected from 100 randomly selected vegetable farmers. Descriptive and multinomial logistic regression analyses were used. The results indicated that age of the farmer, quantity of baby corn produced and level of education were significant predictors of the choice to sell vegetables to NAMBoard market channel instead of selling to other-wholesale market channel. The age of the farmer, distance from production area to market, membership in farmer organization and marketing agreement were significant determinants of the choice to use non-wholesale market channel over other-wholesale market channel. It is therefore important to promote collective action as an institutional vehicle for linking farmers to agribusiness supply chains. Farmers should establish networks since they aid in sharing knowledge, farmers can improve produce grades as required by market.</p><span style="font-family: Times New Roman; font-size: small;"><br /></span>
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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