Resource Productivity of Smallholder Vegetable (<i> Corchorus olitorius</i>) (L.) Farms in Nigeria
Bibliographic record
Abstract
Vegetable farming is an attractive business to small scale farmers in Nigeria. The paper focuses on specific potentials of Corchorus olitorius by estimating the level of resource productivity and costs and return to the vegetable production using farm level survey data. Multistage sampling technique was used to obtain information from 200 farms in Oyo State, Nigeria using simple random selection. The data were analyzed using budgetary technique and stochastic frontier. Results showed that ₦1 expended on the vegetable farming, ₦0.09 is realized as profit. Benefit cost ratio was also estimated to be N1.09. However, all the factor resources employed by the farmers were found to be grossly underutilized while the computed returns to scale (RTS) was 0.4826 suggesting diminishing returns to scale. The findings show that there is a significant economy of scale to be exploited and that factor resources could be well utilized by reducing technical inefficiency. The results have important implications for Nigeria’s agricultural input supply policy, and more specifically for profitable vegetable farming.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".