Long-Term Adaptation: Selecting Farm Types Across Agro-Ecological Zones In Africa
Bibliographic record
Abstract
Using economic data from more than 8,500 household surveys across 10 African countries, this paper examines whether the choice of farm type depends on the climate and agro-ecological zone of each farm. The paper also studies how farm type choice varies across farmers in each zone, using a multinomial logit choice model. Farmers are observed to choose from one of the following five types of farms: rainfed crop-only, irrigated crop-only, mixed rainfed (crop and livestock), mixed irrigated, and livestock-only farming. The authors compare current decisions against future decisions as if the only change were climate change. They focus on two climate scenarios from existing climate models: the Canadian Climate Centre scenario, which is hot and dry, and the Parallel Climate Model scenario, which is mild and wet. The results indicate that the change in farm types varies dramatically by climate scenario but also by agro-ecological zone. Policy makers must be careful to encourage the appropriate suite of measures to promote the most adapted farm type to each location
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".