Households' responses to climate change: contingent behavior evidence from rural South Africa
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We investigate households' decisions regarding livelihood activities in response to future climate change in the Eastern Cape, South Africa. We use the contingent behavior method and account for unobserved heterogeneity in order to overcome problems associated with limited data, collinearity and endogeneity. We characterize the climate change with two types of climate change scenarios: dry-spells and wet-spells. Results show that moderate and extreme increases in dry-spells increase adoption of off-farm activities such as casual labor and small business, and decrease adoption of on-farm activities such as gardening. We find opposite cases for mild or moderate wet-spells. Our results also show that households tend to diversify their livelihood portfolios in response to a moderate increase in dry-spells and a mild increase in wet-spells. Some household characteristics are also important in influencing some types of activities, including household's health status, gender of the household head, and household's prior experience.
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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 | 0.000 | 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 | 0.001 | 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 it