Bibliographic record
Abstract
This book presents research conducted over seven years as part of the Asia Pacific Dispute Resolution (APDR) project at the University of British Columbia.The project examined normative and operational aspects of international trade and human rights performance in China, Japan, and Canada, by reference to the paradigms of selective adaptation and institutional cap acity.Project results have been published in a range of academic and policy journals as well as edited and single-author volumes published in each of the three economies under study.This volume focuses on China's performance with respect to international standards on trade and human rights.China's accession to the World Trade Organization is discussed to provide context for emerging legal regimes on contracts and property.Its performance vis-à-vis international human rights standards is examined by reference to issues of sustainability and social justice.Our hope is that through this volume and other publications supported by the APDR project, dilemmas of trade and human rights performance in cross-cultural and comparative contexts may be better understood.This project was made possible by the financial support of the Major Collaborative Research Initiatives (MCRI) program of the Social Sciences and Humanities Research Council of Canada, for which I am deeply grateful.I would also like to thank the team of co-investigators
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.398 | 0.204 |
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".