‘The weather is like the game we play’: Coping and adaptation strategies for extreme weather events among ethnic minority groups in upland northern Vietnam
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 The Vietnamese government, along with country‐based non‐government organisations, are well aware of the vulnerability of Vietnam's coastal and low‐lying areas to extreme weather events. Yet scant attention has been paid to extreme weather hazards affecting Vietnam's northern mountainous regions and the livelihoods of ethnic minority farmers residing there. Building on conceptual tools from vulnerability, food security and sustainable livelihoods literatures, we examine the impacts of extreme weather, namely drought and severe cold spells, in Vietnam's northern uplands. We explore the degree to which these events impact the livelihood portfolios and food security of ethnic minority farmers, and examine the coping strategies households initiate, based on their ecological knowledge as well as recent market integration initiatives. Drawing on ethnographic fieldwork with ethnic minority Hmong and Yao semi‐subsistence households undertaken yearly from 2012 to 2014, we demonstrate that financial capital – now more central to households' livelihoods than ever before due to state‐sponsored agricultural intensification – is an important means for farmers to cope with extreme weather events. Yet concurrently, longstanding culturally rooted social capital, networks and ties remain critical. Nonetheless, short‐ and long‐term adaptation is not widespread, leading us to investigate possible explanations.
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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 | 0.001 | 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) | 0.000 | 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