Bibliographic record
Abstract
By the 1990s, East Asia had become one of three core economic regions (along with Europe and North America) that together dominated the world economy, accounting for 25 per cent of world GDP by 1995. East Asia had become the new workshop of the world, the location of fast emerging markets, and a new financial power in the making. Japan had first spearheaded East Asia’s economic rise up to the 1990s, and now China has become a major force behind the region’s economic momentum. Theses two countries are amongst the world’s four largest national economies, but East Asia is also host to the highest concentration of newly industrialized economies (e.g. South Korea, Taiwan Singapore, Thailand, Malaysia) found anywhere in the world. The trade and financial surpluses generated by East Asian countries are second to none. The region accounts for just over a quarter of world trade, production, new technology patents and gross domestic product. It is also the home of some of the world’s largest banks and multinational enterprises. East Asia has achieved one of the most profound economic transformations in recorded history. In the 1950s and 1960s, it was a relatively poor developing part of the world, with countries such as Korea having comparable income per capita and development levels on par with many sub-Saharan African states. The region accounted for only 4 per cent of world gross domestic product (GDP) in 1960. In this article, the relation of global market, regionalization and regional conflict is discussed. The role of economic community in emerging market and global market in the East Asia is the section of establishing trade investment liberalization. So, new liberalization is based an economic regionalization and global market. This model is forming is East Asia and APEC region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.079 | 0.093 |
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".