East Asian Environmental Co-operation: Central Pessimism, Local Optimism
Bibliographic record
Abstract
Introduction Much of the literature on environmental politics has discussed the the possibilities for and limitations of regional environmental cooperation in East Asia. States in this region have increasingly recognized the need for regional as well as international co-operation on environmental matters and have set out to create a variety of organizations, action plans, agreements, talks, and networks for co-operation.1 The efforts made by different actors at different levels in the region are many. They include the regional environmental co-operation subgroup of the Asia Pacific Economic Co-operation (APEC) forum, bilateral or multilateral talks, such as the Tripartite Environmental Ministers Meeting made up of China, Japan, and South Korea (TEMM) , intergovernmental mechanisms like Acid Deposition Monitoring Network in East Asia (EANET), and nongovernmental organizations (NGOs) and civil networks such as the North Asia-Pacific Environmental Partnership (NAPEP) . In spite of these efforts, however, there is a consensus among scholars that, overall, regional environmental cooperation in East Asia has been more discussed than acted on, and less institutionalized and less productive than was originally hoped. Although there are serious environmental problems that require a certain level of regional co-operation, such as acid rain, marine resource protection and yellow dust, states in general have to this point failed to deploy and implement concrete action plans to tackle these problems. While literature on East Asian regional environmental co-operation has proposed various possible reasons for this weak co-operation, such as heterogeneity of the key actors, historical legacies, insufficient scientific evidence and even culture, they have mostly
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".