Characterisation of Smallholder Irrigation Schemes in Chirumanzu District, Zimbabwe
Bibliographic record
Abstract
The study was conducted in 2011 at Hamamavhaire and Mhende irrigation schemes in Chirumanzu district in Zimbabwe to determine the typology of the farmers using different irrigation technologies. A structured household survey was carried out on a sample of 79 respondents drawn from farmers using the sprinkler (n=32), flood (n=39) and drip (n=8) irrigation systems. The information gathered was analysed and interpreted using descriptive statistics and inferential statistics in the form of the chi-square test and Analysis of Variance (ANOVA). The main findings showed that there are significant differences (P < 0.05) in yield per hectare (for green maize, maize-grain, wheat and sugar-beans) across the three irrigation systems. Farmers using sprinkler irrigation were found to be better-off in terms of livestock ownership and household assets compared to those using drip and flood irrigation. The study recommended that there is need to provide agricultural training to farmers in irrigation schemes to enhance their productivity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".