Information provision, policy support, and farmers’ adaptive responses against drought: An empirical study in the North China Plain
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
As an important agricultural production region in China, the North China Plain (NCP) is an ecologically vulnerable region that frequently is hit by drought. Faced with drought and other extreme climate events, policy makers have given top priority to the formulation and implementation of adaptation policies. This paper assessed the effectiveness of adaptation policies, including the provision of early warning information and policy supports, on farmers’ adaptive decisions regarding the planting of the wheat crop in the NCP. Based on a unique dataset from a large-scale village and farm survey in five provinces in the NCP, an econometric model of farmers’ adaptation practices is estimated. Results show that when faced with a more severe drought, farmers change their management practices to mitigate its effects by adjusting seeding or harvesting dates and enhancing irrigation intensity. The provisions of early warning and prevention information and policy supports against drought facilitate farmers to make farm management adaptations. However, the effectiveness of early warning and prevention information or policy supports differs by their provision channels or types. The findings of this study have policy implications in coping with the rising frequency and seriousness of extreme weather events in China as a whole and in ecologically more vulnerable NCP in particular.
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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