Compound impacts from droughts and structural vulnerability on human mobility
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
Extreme dry events already disrupt populations' ability to migrate. In a warming climate, compound drought events could amplify vulnerability and drive forced migration. Here, we contribute the first multi-method research design on societal impacts from compound drought events. We show how mobility patterns are shaped by the intersection of drought and social vulnerability factors in three drought-prone countries - Madagascar, Nepal, and Mexico. We find that internal migration in agricultural communities in Mexico increased by 14 to 24 basis points from 1991 to 2018 and will prospectively increase by 2 to 15 basis points in Nepal in case of a compound drought event in 2025. We show that consecutive drought events exacerbate structural vulnerabilities, limiting migrants' adaptation options, including long-range migration. We conclude that the additional social pre-conditions, e.g., social isolation and lack of accurate information, ultimately limit migration as an adaptation option for households vulnerable to compound drought events.
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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 | 0.003 | 0.001 |
| 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