Bibliographic record
Abstract
INTRODUCTION This chapter summarizes China's progressive opening to foreign trade and investment in the years since 1978. These reforms led China's foreign trade to soar from $21 billion in 1978, when China at best was a marginal player in global trade, to more than $1.1 trillion in 2004,whenChina became the world's third largest trading economy (National Bureau of Statistics, 2005, p. 161; World Trade Organization, 2005, p. 16). We will briefly review the history of Chinese trade and investment policy from 1978 to 2001 and note the impact of important policy changes on expansion of trade and investment. Because accession to World Trade Organization (WTO) marked an important watershed in the evolution of Chinese policy in this realm, we will also include a discussion of the key features of the agreement under which China joined the WTO and an assessment of the progress China has made to date in implementing its obligations. The WTO accession agreement opens up important components of the service sector of the Chinese economy, and these will receive special emphasis. We will also address the high-profile debate over China's currency regime and discuss the implications of China's expanding trade and foreign investment for the rest of the world. In providing this overview, we will be emphasizing several themes. First, China achieved a greater degree of openness to foreign trade in manufactures prior to WTO accession than is generally acknowledged, even in much of the best recent scholarship.
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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 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".