Bibliographic record
Abstract
T Z a HE WORLD iS considered as having three major regions: Western Europe, North America and East Asia. Unlike the other two regions, however, East Asia is not as well defined as an economic region. While Western Europe and North America are economically institutionalized by the European Union (EU) and the North American Free Trade Agreement (NAFTA) respectively, East Asia has no comparable regional arrangement. This paper argues that East Asia is a globally defined economic region different from the other major regions. While cultural and economic diversity prevents formal integration, regional integration has been achieved by informal means such as regional production networks, ethnic business networks and subregional economic zones. The case of economic integration in East Asia also adds to conventional theories of economic integration by providing an alternative to the EU-type formal integration. This paper studies the regional production network (RPN), a major regional element of Asian economic integration. These networks, driven by the foreign direct investment (FDI) from Japan and based on a multi-tier division of labor, are stitching together the disparate economies of Asia, integrating them with one another.' They helped to launch first the East Asian newly industrialized economies (EANIEs) and then those of the ASEAN Four (Thailand, Malaysia, Indonesia and the Philippines) and China. The RPN has created a trade triangle amongJapan, East Asia and North America (In this paper, East Asia is referred as Northeast Asia and Southeast Asia, but when it is used in parallel to Japan, Japan is not included.). In this triangle, Japan provides capital goods and technology to East Asia, East Asia exports consumer goods to North America, and North America is a major market for both Japan and East Asia. However, while the RPN was the dominant form of informal integration in the past, its weakness has also recently become
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".