Adoption of Conservation Agriculture in Zambia – The Case of Chongwe District
Bibliographic record
Abstract
<p>The Zambian government and its cooperating partners have been trying to promote the use of conservation agriculture for improved food security and promotion of environmental sustainability. The methods used to promote conservation agriculture however are not adequately informed because no Zambia-specific studies have been done to explain adoption behaviour. This study aimed at explaining the factors that affect the adoption of conservation agriculture in Zambia using a case study.</p><p>A cross section survey of 200 randomly selected small scale farmers in Chongwe district was conducted using a structured questionnaire. Information collected included demographic characteristics of participating households, economic, as well as social characteristics. Respondents also provided information on the farming practices they are currently using vis a vis conservation agriculture.</p>A decision model was estimated using logistic regression and the results indicate that the adoption of conservation agriculture in the survey area is basically influenced by ownership of draft power, availability of labour, and the frequency of contact with the farmer support extension system. Potential to increase the adoption rate is plenty, but can only be tapped into if strategies and policies take into account the behavioural aspects of the adoption of the technology.
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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".