Adaptation to the Impact of Climatic Variations on Agriculture by Rural Farmers in North-Western Nigeria
Bibliographic record
Abstract
The impact of climatic variations on crop yields and the adaptation by farmers in north-western Nigeria are examined using the modeling approach and farm surveys. Accordingly, regression models which relate climate data to crop yields were constructed. The results showed that rainfall has a positive relationship with crop yields in the region and explained over 70 percent of the variations in the yields of sorghum, millet and maize, all of which were significant at the 0.05 level. Evaporation also had a significant but inverse relationship with crop yields. Other climatic elements in the experiment provided minimal levels of explanation. The farm surveys found that rural farmers in north-western Nigeria were quite innovative when it comes to adapting to drought. The study concluded that the impact of climatic variations on crop yields in north-western Nigeria can be substantial especially under drought conditions. The need to update farmers’ adaptive strategies is emphasized.
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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 | 0.001 | 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) | 0.000 | 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; a candidate call from one teacher head, 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".