An Empirical Study on the Export Growth of China's Aquatic Products in Japan and South Korea
Bibliographic record
Abstract
China, Japan and South Korea have a close relationship in aquatic products trade. Japan and South Korea are both China's important export markets. Based on the data of UN Comtrade Database from 2001 to 2012, the paper compares the trade status of China's aquatic products exported to Japan with those exported to South Korea, and then use the CMS model to figure out the factors that influence the volume growth of the aquatic products of China exported to Japan and South Korea. The results show that, the increasing demand of Japan and South Korea is the main factor that promotes the export growth of China's aquatic products. The product structure effect and the comprehensive competitiveness effect of China's aquatic products in Japan market are higher than in South Korea, while the product competitiveness effect and cross effect are not obvious in the two markets. Based on the results of empirical research, the corresponding policy recommendations are given.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 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 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".