Bibliographic record
Abstract
This volume examines the challenge of coordinating local performance of international trade and human rights standards in the Asia Pacific region, with particular attention to questions about the right to development.The book is part of a group of edited volumes examining different aspects of trade and human rights performance presented by the Asia Pacific Dispute Resolution (APDR) project and published in the UBC Press Asia Pacific Legal Culture and Globalization series.The APDR program began in 2003 with a SSHRC/MCRI-supported project on normative and operational conditions for local compliance with international trade and human rights standards in Canada, China, and Japan.Since 2009, the APDR project has focused on "understanding integrated compliance with international trade and human rights standards from a comparative perspective." This has involved building conceptual understanding and generating policy analysis on coordinating performance of international standards on trade and human rights in the Asia Pacific region, with particular attention to Canada, China, India, Indonesia, and Japan.The APDR project is based at the Peter A. Allard School of Law and the Institute of Asian Research of the Univer sity of British Columbia, and involves a collaborative network of colleagues from UBC and from partner institutions in North America, Asia, and Australia.The challenge of coordinating local compliance with international trade and human rights standards is a critical issue for the globalized world.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.629 | 0.541 |
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".