Human Mobility and Climate Change Adaptation in Small-Scale Farming Areas in Eastern Zimbabwe
Bibliographic record
Abstract
Abstract This paper examines the role played by human mobility as a climate change adaptation strategy in Zimbabwe’s small-scale farming areas. Livelihoods in Zimbabwe’s small-scale farming areas are mostly agriculture-based and have long suffered from low levels of production. This is largely due to poor agroecological conditions and lack of agricultural investment, including income diversification projects from the central government. Recently, extreme climatic events in these areas have exacerbated food insecurity challenges, prompting many households to relocate. The findings of this study indicate that most households in the small-scale farming regions are resorting to either short- or long-term migration to areas that offer them food security. In these areas, poor households are forced to work on large commercial farms where they are paid in maize grain or trade their products for food to support their families. This paper argues that, if properly used together with other climate change policies promoted in Zimbabwe, human mobility can be an effective climate change adaptation strategy in small-scale farming areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".