China’s export growth and the China safeguard: threats to the world trading system?’ Canadian
Bibliographic record
Abstract
China’s deepening engagement in the global trading system and the threat of its export capacity have affected the negotiation, formation, and rules of international trade agreements. Among other changes, China’s 2001 accession to the World Trade Organization (WTO) intro-duced new allowances for existing members to deviate from core WTO principles of reciprocity and most-favored-nation (MFN) treatment by giving existing members access to a discriminatory, import-restricting China safeguard based on the threat of “trade deflection. ” This paper asks whether there is historical evidence that imposing discriminatory trade restrictions against China during its pre-accession period led to Chinese exports surging to alternative markets. To examine this question, we use a newly constructed data set of product-level, discriminatory trade policy actions imposed on Chinese exports to two of its largest destination markets over the 1992-2001 period. Perhaps surprisingly, we find no systematic evidence that either U.S. or EU imposition of such import restrictions during this period deflected Chinese exports to alternative destina-tions. To the contrary, we provide evidence that such import restrictions may have a chilling effect on China’s exports of these products to secondary markets- i.e., the conditional mean U.S.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".