Embedding regional actors in social and historical context: Australia-New Zealand integration and Asian-Pacific regionalism
Bibliographic record
Abstract
Abstract The regionalisation of the world economy is one of the most important developments in global governance in the past two decades. This process has seen ‘inter-regional’ economic agreements emerge between two or more regional groupings. Drawing mainly on the European Union’s external relations, observers accordingly point to the growing importance of regional actors, explaining their agency (or ‘actorness’) with regional attributes such as (supranational) institutional design, size, and member state cohesion. This article challenges this dominant explanation of regional agency. It argues that regional actors are socially, politically, and historically ‘embedded’. Agency reflects the contingency of regional integration processes, the motivations that underpin those processes, and the specific relationships between regions and third parties. This approach explains an important case of inter-regionalism from the Asia-Pacific: CER-ASEAN relations. Since the early 1990s, Australia and New Zealand have used their ‘Closer Economic Relations’ trade agreement for relations with the Association of Southeast Asian Nations. This reflects the ambitions of Australasian officials to shape processes of Asian-Pacific regionalism, and the interests of ASEAN officials in consolidating their own process of transnational market-making. Here, regional agency owed to a transforming world economy and the reconceptualisation of regions within new networks of trade 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".