Entrepreneurship Skills as a Factor Influencing Adoption of Innovations along Mango Value Chains in Meru County, Kenya
Bibliographic record
Abstract
The study used a descriptivesurvey design. The study was carried out in Meru County, Kenya. Population of the study comprised of 13,574 farmers, traders and exporters, 404 farmers, 12 traders and 2 exporters. Both secondary and primary data was collected. Primary data was collected from the respondents using a structured questionnaire with both open and close ended questions. Both qualitative and quantitative data were used in the analysis. Quantitative data obtained from the field was analyzed using descriptive and inferential techniques. The descriptive techniques used means and frequencies while the inferential technique used were regression and correlation to establish relationship between variables in the study and inferences made. Frequency tables and charts were used to present the findings. The study found out that entrepreneurial skills played a role on the innovations adoption along the mango value chain. However, a linear association does not exist as between entrepreneurship skills and innovation in mango. The researcher concludes that with such a steady growth in yields and development in mango farming in Meru County, Kenyan mango supply chain appears to be promising. In the adoption of new innovations and there is need to train the growers on entrepreneurship. Education tours should be organized for the value chain members to countries such as India and Brazil so that they learn what their contemporaries in these countries are doing and adopt more skills
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".