An Evaluation of <i>Bani (Dambo</i>) Systems as a Smallholder Irrigation Development Strategy in Zimbabwe
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Bibliographic record
Abstract
There is little disagreement among experts that to increase agricultural production in sub‐Saharan Africa, especially in the semiarid areas, in view of the fact that these areas receive limited rainfall and face frequent droughts and have only 15% of their irrigation potential developed and utilized, irrigation development is critical. Due to high costs of infrastructure development of conventional irrigation systems and the prevalence of general pessimism based on the current low level of performance of the already existing projects in terms of financial, managerial and environmental objectives, it is imperative to evauate smallholder irrigation systems under farmer management as an alternative and/or complementary irrigation development strategy. This paper compares and evaluates the socio‐economic characteristics and the technical efficiency of the Bani system to the formal systems and makes recommendations for its development. Les experts conviennent généralement qu'il faut irriguer pour accroître la production agricole dans l'Afrique sub‐saharienne, surtout dans les régions semi‐arides où il pleut relativement peu, où la sécheresse sévit fréquemment et où les possibilités d'irrigation n'ont été développées qu'à quinze pour cent. Face au coût d'infrastructure élevé des systèmes d'irrigation classiques et au pessimisme général qu'engendre la piètre performance des projets existants quant à la réalisation des objectifs financiers, administratifs et environnementaux, il est impérieux d'évaluer l'utilité des petits systèmes d'irrigation exploités par les cultivateurs comme solution de rechange ou solution complémentaire à la stratégie actuelle de développement de l'irrigation. L'article que voici compare et évalue les paramètres socioéconomiques et l'efficacité technique du système Bani aux systèmes officiels en formulant des recommandations sur son extension.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it