The Value and the Limitations of Comprehensive Multilateralism - An EU Perspective on the Asia-Europe Meeting
Bibliographic record
Abstract
This article examines the attitudes of the European Union on the development of Asia-Europe Meeting (ASEM). It looks first at the trajectory of EU positions on ASEM, before specific sections explore the EU perspective on the style and format of ASEM, on the substantive issues under discussion, and on the wider geo-political relevance of the institution. In order to provide a critical assessment of the EU’s position, the article also discusses some of the key alternative relationships the EU has with the Asia-Pacific region, be it multilaterally or bilaterally. By way of conclusion, the article argues that despite the limitations of ASEM, the process still retains an added value in the context of the wider diplomacy between the EU and its Asian partners.
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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 | 0.036 | 0.040 |
| 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 | 0.020 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".