Climate change and variability: smallholder farming communities in Zimbabwe portray a varied understanding.
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
Increasing awareness of risks associated with climate change and variability among smallholder farmers is critical in building their capacity to develop the necessary adaptive measures. Using farmer participatory research approaches and formal questionnaire surveys, interaction has been made with>800 farmers in two distinct smallholder farming systems of Makoni and Wedza Districts in eastern Zimbabwe to determine the current level of understanding of climate change and variability, current responses to perceived changes, as well as identify sources of agro-meteorological information. The results indicated that farmers portrayed a varied understanding both within and across the study sites. While poor rainfall distribution was seen as the major indicator for climate change by over two-thirds of the respondents in both sites, more farmers in Makoni attributed delay in onset of rains, high incidences of flush floods and unpredictable ‘wind movements ’ yielding cyclones to climate change. In Wedza, it was recurrent droughts, winter and summer temperature extremes, and increased pest and disease incidences for both crops and livestock that indicated climate change. Perceived changes were linked more to natural and human forces (Makoni), unknown forces as well as breakdown in cultural norms and beliefs and rise of Christianity (Wedza). Disparities between the two sites could be attributed to the inherent differences of the communities in terms to their social settings. The national extension, Agritex, was ranked first by 50-60 % of the
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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) | 0.000 | 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) | 0.001 | 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