Everyday adaptation practices by coffee farmers in three mountain regions in Africa
Bibliographic record
Abstract
Mountain environments in East Africa experience more rapid increases in temperature than lower elevations, which, together with changing rainfall patterns, often negatively affect coffee production. However, little is known about the adaptation strategies used by smallholder coffee farmers in Africa. Using the lens of everyday adaptation, semi-structured interviews were carried out with 450 smallholder farmers living near the Bale Mountains in Ethiopia (n = 150), Mount Kenya in Kenya (n = 150), and Kigezi Highlands in Uganda (n = 150). We report similarities in adaptation strategies used (e.g., increased use of improved seeds, inputs, soil-conservation techniques) but also differences across and within regions (e.g., irrigation, coffee-farming abandonment), related to different biophysical, economic, and sociocultural factors. In all regions, access to land, funds, and limited mutual-learning opportunities between farmers and other agents of change constrained further adaptation options. Local people have capacity and means to determine how best they can adapt to climate change, and government agencies and NGOs could implement more participatory engagement with smallholder coffee farmers, attuned to the opportunities and constraints in everyday life to facilitate adaptation to predicted changes in climate.
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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 | 0.000 |
| 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 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".