Analysis of Farmers Perception, Preference and Adoption Likelihood for Provitamin-A Cassava Roots in Sierra Leone
Bibliographic record
Abstract
The main achievement of any scientific research is to ensure its technology produced is adopted by the intended clientele. The study aimed was to access Farmers’ Perception, Preferences and Likelihood Adoption for Provitamin-A Cassava storage roots in Sierra Leone. The study sampled three districts (Bombali, Kailahun and Moyamba) to examined socio-economic characteristics, analyze farmer’s perceptions, varietal preferences, determine the maximum likelihood of adoption and rank the most outstanding drivers and barriers of adoption. A multistage sampling technique was employed. Data were collected using pre-tested structured questionnaires for 150 household interviews and semi-structured questionnaires for focus group discussions (FGDs). Data collected were analysed for descriptive and inferential statistics. The results showed that Youths (male) predominated cassava production across the surveyed districts. 43% of the respondents didn’t have access to any formal education while 62% of the respondents did not belong to any organization. Farmers however desired provitamin-A cassava that are high yielding, early maturing, appreciable marketable root size that are Poundable. Interviewees had no prior knowledge about provitamin-A cassava, but were willing to adopt it once it’s made available. 90% of the respondents were willing to cultivate provitamin-A cassava varieties once it made available due to its nutritional value. The adoption likelihood analysis from two scenarios confirmed that total maximum likelihood adoption rate was 75.4% for scenario one followed by 78.1%forv scenario two. To increase maximum adoption rates for provitamin-A cassava varieties once release, flexible recommendations that combines both farmer’s categories and production goals of technologies should be considered given the barriers identified from this pre-ante study in the cassava breeding program.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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 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".