Conference Proceedings for the Workshop on China & Global Governance
Bibliographic record
Abstract
China's active participation and influence in a wide range of global regimes, from the World Trade Organization to international energy markets, has inspired growing attention and excitement among scholars, policymakers, business people, and others both within and outside of China. In July 2010, Indiana University's Research Center for Chinese Politics & Business organized a conference at Peking University that brought together more than 40 scholars, government officials and industry representatives officials to discuss China's growing participation in global governance. The diverse group of conference participants had a wide range of expertise and came from the Chinese mainland, Taiwan, Canada, Japan, South Korea, Switzerland, and the United States. The conference covered a number of contentious and important issue areas, including the WTO, trade remedies, currency and financial market regulation, technology standards, global energy markets, climate change and the relationship between bilateral relationships and multilateral forums. The goal of this paper is to: 1) Present a faithful summary of the central points of discussion and debate of each panel; 2) Provide an analysis which highlights similarities and differences in Chinese participation across regime areas; and 3) Indicate likely areas of research which emerged from the discussion. Since the presentations and discussion were made on a not for attribution basis, the names of individual participants and their identifying information have been withheld.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.160 | 0.020 |
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".