Bibliographic record
Abstract
This article explain the trade policy changes in China and strategies of Japan. China’s trading partners regard rising China as both opportunity and threat. Each country tries to maximize opportunities by developing friendly relations with China as well as helping its business community to explore new trade and investment opportunities in China. For trade and investment policy issues, each government uses different approaches, depending on the leverage it can exercise with respect to China. For larger and more powerful countries such as the U.S. and the EU, more aggressive and sometimes confrontational approaches are adopted, usually in the form of using national trade legislations or WTO dispute settlement mechanism. Smaller countries such as Canada, Australia and Switzerland seem to prefer less confrontational and more cooperative approach vis-a-vis China. In the case of Japan, despite the huge trade and investment ties between the two countries, the government policy remains passive with the private sector initiatives mainly driving the increasing economic ties. Through this studies of trade policy changes in China and strategies of Japan, I first explains the overview of Japan trade relations with China, then show(analyze) evolution of trade policies toward China(before WTO accession/after WTO accession, relationship to foreign policy/domestic support for current policy). Second, I examined the outstanding trade issues and disputes in terms of bilateral and multilateral. Third, I argue that the current trade policy strategy toward China and China’s response(assessment of effectiveness of China strategy) and Forth, I surveyed the current institutional framework for dealing with trade issues with China and its effectiveness. Lastly, I showd direction of China’s future trade policy and the alternatives for policy responses of trading partners.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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; both teacher heads agree on what is shown here.
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".