Globalizing regional development in East Asia : production networks, clusters, and entrepreneurship
Bibliographic record
Abstract
1. Globalizing Regional Development in East Asia: Production Networks, Clusters, and Entrepreneurship - Henry Wai-chung Yeung 2. Situating Regional Development in the Competitive Dynamics of Global Production Networks: An East Asian Perspective - Henry Wai-chung Yeung (National University of Singapore) Part One: Global production networks and regional development 3. Revisiting the Silicon Island? The Geographically Varied in the Development of High-technology Parks in Taiwan - You-ren Yang, Jinn-yuh Hsu, and Chia-ho Ching (National Taiwan University) 4. Strategic Coupling of Regional Development in Global Production Networks: Redistribution of Taiwan PC Investment from Pearl River Delta to Yangtze River Delta, China - Chun Yang (Chinese University of Hong Kong) 5. Multinationals, Geographical Spillovers and Regional Development in Thailand - Suksawat Sajarattanochote and Jessie P.H. Poon (State University of New York, Buffalo) 6. From Global Production Networks to Global Reproduction Networks: Households, Migration and Regional Development in Cavite, Philippines - Philip F. Kelly (York University, Canada) Part Two: Politics and entrepreneurship in regional development 7. Balanced Development in Globalizing Regional Development? Unpacking the New Regional Policy in South Korea - Yong-Sook Lee (Korea University) 8. Scaling Up Regional Development in Globalizing China: Local Capital Accumulation, Land-Centered Politics, and Reproduction of Space - George C.S. Lin (University of Hong Kong) 9. Globalizing Regional Development in Sunan, China: Does Suzhou Industrial Park Fit a Neo-Marshallian District Model? Dennis Wei, Yuqi Lu, and Wen Chen (University of Utah, USA) 10. Clustering as anti-politics machine? Situating the politics of regional economic development and Malaysia's Multimedia Super Corridor - Josh Lepawsky (Memorial University of Newfoundland, Canada) 11. Entrepreneurship and Regional Culture: The case of Hamamatsu and Kyoto, Japan - Yuko Aoyama (Clark University, USA)
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".