Cost Benefit Analysis of Climate Change Adaptation Strategies on Crop Production Systems: A Case of Mpolonjeni Area Development Programme (ADP) in Swaziland
Why this work is in the frame
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Bibliographic record
Abstract
<p>Prolonged drought and floods as a result of climate change are a serious problem for households at Mpolonjeni ADP because their livelihood is mainly rainfedfarming. This is evident as there is high level of food insecurity, crop failure, poverty and hunger, which has forced many households to abandon farming and survive by food aid. The study was a descriptive survey aimed to identify private adaptation strategies to climate change and conduct a cost benefit analysis for the identified adaptation strategies. A stratified random samplingtechnique was used to select 350 households. Personal interviews were conducted using structured questionnaires. Data were analysed using descriptive statistics and cost benefit analysis where net present value (NPV) and internal rate of return (IRR) were used as decision rules. Adaptation strategies used were; drought resistant varieties, switching crops, irrigation, crop rotation, mulching, minimum tillage, early planting, late planting and intercropping. Switching crops had the highest NPV, where maize (E14.40) should be substituted with drought tolerant crops such as cotton (E1864.40), sorghum (E283.30) and dry beans (E292.20). The study recommends that households should grow drought tolerant crops such as cotton, sorghum and dry beans instead of maize. The government should provide irrigation infrastructure, such as dams, strengthen extension services and subsidise farm inputs in order to improve crop production.</p>
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| 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) | 0.000 | 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 it