Determinants Influencing Market Outlet Choices Among Smallholder Dairy Farmers in a Developing Economy
Bibliographic record
Abstract
Dairy farming is an important livelihood source for most smallholder farmers in Kenya. However, most smallholder dairy farmers in Kenya face various challenges in selecting profitable market outlets, and their choices are influenced by various factors. Understanding these determinants is crucial, as market outlet decisions directly impact farmers’ income, livelihoods, and the overall growth of their agrienterprises. However, there is limited empirical evidence on the determinants influencing market outlet choices among smallholder farmers in Kenya specifically Narok County which is an emerging dairy hub in the country. In this context, this study analyses the determinants influencing market outlet choices (Farm gate, Milk bars, Traders, Cooperatives, and Processors among smallholder dairy farmers in Narok County, Kenya using a multivariate probit model. Data was collected using a multi-stage sampling procedure from the 384 smallholder dairy farmers. Some of the key factors that shape smallholder dairy farmers’ milk market choices, based on the results of the study include household head occupation, farm size, production cycles, milk volumes, market distance, and group membership. Policy interventions should aim to strengthen cooperative structures, support group memberships, invest in transport infrastructure to mitigate distance barriers, encourage prompt payment systems, and enhance market information access to support sustainable participation of smallholder dairy farmers in diverse market channels.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".