Crop Technology Adoption Among Rural Farmers in Some Selected Regions of Mali
Bibliographic record
Abstract
Enhancing farm production through an application of modern crop technologies to the extant farm system is relevant to improving the lives of farmers in rural areas. The Ecofarm crop technologies are some of the technologies that have been introduced with the aim of improving the lives of rural farmers in Mali. The study was carried out to examine the elements that influenced the adoption decisions of Ecofarm technologies among rural farmers in three selected regions of Mali. It contributes to the present knowledge on the socioeconomic factors that influence farmers in their adoption decisions of crop technologies in dry-land crop growing areas. Through the application of a multi-stage sampling technique, data were collected from 120 rural farmers from the three study regions. The Ordinary Least Square (OLS) and Cost-Benefit analyses were employed to analyze the data. It was evident that household size positively determined the adoption decisions of rural farmers in these regions. Also, the distance to these Ecofarm technologies had influence on the adoption decisions in that, the proximity of these technologies to the farms induced the rural farmers to adopt them. Interestingly, it was also found out that the larger the land holding of the farmers, the less likely it was for them to adopt the Ecofarm technologies. It was concluded that the regions with greater net benefits after the adoption were adopting more of Ecofarm crop technologies than those with less net benefit.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".