Impact of Extreme Weather Disasters on China’s Barley Industry under the Background of Trade Friction—Based on the Partial Equilibrium Model
Bibliographic record
Abstract
The world has entered a compound risk era with multiple crises, and the adverse impact of trade friction and extreme weather disasters on China's barley import has become increasingly prominent. In this context, this study uses superimposed epoch analysis and partial equilibrium model to evaluate the impact of extreme weather disasters in China's major barley-exporting countries on China's barley industry in the course of China-Australia trade friction. The results show that: (1) extreme weather disaster caused barley production in France and Canada to decrease by 7.95% and 18.36% respectively; (2) when the two external shocks occur at the same time, China's barley import volume tends to decline compared with the basic scenario, the import price rises sharply, there are certain trade-diverting effects in barley import, and China's imports from countries not affected by extreme weather disasters will increase to a certain extent; (3) China's barley production remains at a low rate of growth and is vulnerable to external shocks, facing certain import risks. This study provides important policy implications for preventing import risks and ensuring the sufficient supply of domestic barley.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".