The Asia‐Pacific Partnership: implementation challenges and interplay with Kyoto
Bibliographic record
Abstract
Abstract The Asia‐Pacific Partnership (APP) for Clean Development and Climate, a multilateral agreement between Australia, Canada, China, India, Japan, the Republic of Korea (Korea) and the United States of America, is a nonbinding memorandum of understanding directed at international cooperation on development, energy, environment and climate change issues involving business and industry voluntary action on technology transfer, and research and development. It has been hailed as a new model for an international climate agreement and as an alternative to the Kyoto Protocol. However, APP implementation has had challenges. As an opposing model to that of Kyoto, it is in contravention of the United Nations Framework Convention on Climate Change's (UNFCCC's) principle of common but differentiated responsibilities and a contributor to the crumbling of climate governance. Cooperation rather than competition ideally should be the future for the relationship between the APP and the UNFCCC/Kyoto. Business and industry are involved in implementation of the Kyoto mechanisms under the UN climate regime currently; and for that reason, synchronicity between the APP and Kyoto agreements would be ideal. For example, APP nations could be involved in joint ‘regional’ emissions trading as the United States, Canada, Australia, Korea, and Japan all are in the process of establishing national schemes. However, for the APP to be a complement to Kyoto and not a barrier to its effectiveness, many hurdles need to be overcome including equity issues, additionality questions, capacity building concerns, trade barriers, intellectual property issues, adequacy of funding, assessment of APP emissions reductions, and renewal of US interest in UN climate regime participation. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Policy and Governance > Multilevel and Transnational Climate Change Governance
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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 | 0.044 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".