Agricultural Development Programme (ADP) Capacity Building and Cassava Farmers Productivity in Anambra State
Bibliographic record
Abstract
This study was necessitated as a result of the low productivity of cassava farmers in Anambra State. The study set out to examine the effect of Agricultural Development Program (ADP) capacity building on cassava farmers’ productivity in Anambra State. The work was anchored on Cobb-Douglas production model. Descriptive survey research design was adopted for the study. The population of this study comprised of all the ADP cassava farmers and non-ADP cassava farmers in Otuocha and Onitsha Agricultural Zone. With membership strength of three hundred and sixty (360) ADP Cassava farmers and one hundred and sixty (160) non-ADP cassava farmers, making up a total of five hundred and twenty (520) respondents. Structured and unstructured questionnaires were used for data collection and the analysis was done with Analysis of Variance (ANOVA) at 5% level of significance. From the analysis showed that there is a significant difference in the output of ADPCFs and non ADPCFs in Anambra State (F =13.209 and p-value < .05). Based on the findings, the study concluded that belonging to ADP was responsible for the differences in output observed in the study. Sequel to this, it was recommended that cassava farmers in the state that are yet to key into ADP needs to do so in order to learn from the various level of capacity development programs organized by the body.
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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 | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".