Study of International Regulatory Co-operation (IRC) arrangements for air quality
Bibliographic record
Abstract
China, Japan and Korea have deployed a multiplicity of co-operation efforts at different levels of government to promote air quality and curb transboundary pollution. This paper identifies the existing arrangements for air quality co-operation in North East Asia and provides guidance to advance the co-operation required to face cross-border air pollution building on the experience of two long-standing co-operative agreements in this area: the Canada-United States Air Quality Agreement and UNECE’s Convention on Long-Range Transboundary Air Pollution. This paper finds that the multilateral arrangements existent in North East Asia are yet to produce a comprehensive science-based regional approach to address transboundary air pollution. Key suggestions for countries to capitalise on the stronger momentum for co-operation in this area include: i) building on the existing frameworks for international regulatory co-operation for air quality; ii) advancing a common understanding of transboundary air pollution across scientific regional arrangements; and iii) strengthening the domestic policy frameworks for air quality in each country as a key prerequisite.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".