Commercialisation of Traditional Crops: Are Cassava Production and Utilisation Promotion Efforts Bearing Fruit in Kenya?
Bibliographic record
Abstract
Achieving food security has been an elusive goal for many economies in Sub-Saharan Africa. Among the strategies being pursued to achieve this goal is agribusiness development through strengthening smallholder farmers’ entrepreneurial capacity and promotion of traditional crops production and utilisation. Cassava has been identified as a high value traditional crop that has enormous industrial value. In Kenya, it has been promoted by the government and other interested organisations. However, despite the efforts, cassava has not evolved from subsistence to a commercial crop that can be relied on in the fight against food insecurity. This paper examines the level of adoption of cassava commercialisation technologies by smallholder farmers in Kenya. It is based on a study conducted in Ngata Division of Nakuru District Kenya where 99 smallholder household heads who are members of cassava common interest groups were interviewed and stakeholder discussions held. Data was analysed using descriptive statistics and stakeholder discussions analysed thematically. Though cassava was grown by 57% of the households, very few (6.1%) engaged in entrepreneurial activities involving cassava, selling only the raw tubers. Cassava tended to be grown by older farmers as compared to younger farmers. Smallholder farmers encountered challenges in cassava production, cassava utilisation and cassava commercialisation. For cassava to contribute towards food security, a market-oriented approach that focuses on empowering farmers for entrepreneurial action may need to be considered.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".