Migration and Household Adaptation in Climate-Sensitive Hotspots in South Asia
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
Abstract Purpose of Review South Asia is highly vulnerable to the impacts of climate change, owing to the high dependency on climate-sensitive livelihoods and recurrent extreme events. Consequently, an increasing number of households are adopting labour migration as a livelihood strategy to diversify incomes, spread risks, and meet aspirations. Under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) initiative, four research consortia have investigated migration patterns and their inherent linkages to adaptation to climate change in climate hotspots. This article synthesizes key findings in regional context of South Asia. Recent Findings The synthesis suggests that in climate-sensitive hotspots, migration is an important livelihood diversification strategy and a response to various risks, including climate change. Typically, one or more household members, often young men, migrated internally or internationally to work in predominantly informal sectors. Remittances helped spatially diversify household income, spread risks, and insure against external stressors. The outcomes of migration are often influenced by who moves, where to, and what capacities they possess. Summary Migration was found to help improve household adaptive capacity, albeit in a limited capacity. Migration was mainly used as a response to risk and uncertainty, but with potential to have positive adaptation co-benefits.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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