Impact of Agricultural Programs on Youth Engagement in Agribusiness in Nigeria: A Case Study
Bibliographic record
Abstract
Using the case of Fadama Graduate Unemployed Youth and Women Support (FGUYS) program, this study assessed the impact of agricultural programs on youth engagement in agribusiness in Nigeria. A total of 977 respondents comprising of 455 participants of the program and 522 non-participants were sampled across three states in Nigeria. Data were analysed using Descriptive and Endogenous Switching Probit Regression (ESPR) Model. The result showed that participation in the program was influenced by age, years of formal education, perception of agricultural programs and type of employment. Furthermore, the results showed a positive impact of the program on youths’ likelihood to engage in agribusiness. The study recommends the need to invest more in agricultural programs such as the case study since it has desirable economic outcome for young people. Also, there is a need to improve the general outlook of agriculture such that it becomes more attractive to young people.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".