Efficiency Profiles of Vegetable Producers in Akwa Ibom State, Southern Nigeria
Bibliographic record
Abstract
<p>Vegetables are among the major staple foods in Southern Nigeria. This study assessed the efficiency profiles of vegetable producers in Akwa Ibom State, Southern Nigeria with specific focus on farm level technical efficiency. One hundred and twenty (120) vegetable producers were randomly selected from three agricultural zones in the State. The Maximum Likelihood Estimates (MLEs) indicate positive relationships between input variables used by farmers and farm outputs. The Generalized Likelihood Ratio test confirms that vegetable producers in the area are relatively technically inefficient. The technical efficiency of the farmers ranged from 48 to 99 percent with a mean of 70 percent. The implication is that there is allowance to improve efficiency with available resource.There is, therefore, the need for policies to promote the availability of affordable farm inputs and technology to help improve farmers’ efficiency and increase vegetable production in the area. Extension services would also help provide useful information to the farmers on farm practices that would enhance output and ensure environmental sustainability of the production process by maintaining the quality of some critical environmental factors especially soil quality.</p>
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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 | 0.030 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".