Farmers’ preference for soil and water conservation practices in central highlands of Ethiopia.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Land degradation is a major socio-economic and environmental concern in the Ethiopian highlands where the phenomenon has rendered vast areas of fertile land unproductive. To reverse this trend, the adoption of soil and water conservation (SWC) practices is crucial. However, failure by research and development organisations to take into consideration farmers preference for SWC practices have resulted into low adoption of these technologies. This paper presents the findings of a study that evaluated farmers ’ preferences of SWC practices, including the economic perspective; as a basis for enhancing adoption of the technologies in the central highlands of Ethiopia. Four soil and water conservation (SWC) practices; (i) soil bunds alone (SB), (ii) soil bunds with vetiver grass (SB+Vg), (iii) soil bunds with Susbania susban (SB+Ss) (iv) and soil bunds with elephant grass (SB+Eg), were evaluated in the Borodo Watershed in the central highlands of Ethiopia. These are the only SWC measures introduced and implemented in Borodo watershed. Data on these SWC practices were collected from farmers using focus group discussion. A multi-criteria analysis (MCA) approach was used to analyses the data. The criteria were weighted using pair-wise ranking and SWC practices were scored with a scale of 1(not good) to 5 (best) based on each criterion. The overall weighted scores were obtained using the Simple Additive Weighting Model. Farmers assigned highest relative weights to criteria related to economic criteria (0.58) than technical
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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 | 0.000 | 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 | 0.000 |
| 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 it