Increasing Student Mobility Within Northeast Asian Countries: Implications for the Future of the Region
Bibliographic record
Abstract
Student mobility in East Asia, as elsewhere in Asia in the post-War era, has been very much centred on North America and Western Europe. Each year, tens of thousands students from Japan, South Korea, Taiwan (and from China after the 1990s) left home to study in the wealthy developed countries such as the USA, Canada, UK, Germany, and Australia. In fact, international students from East Asia (Japan, South Korea, China, and Taiwan) have been the largest group in these countries listed above. This trend, however, has changed in the last decade of the 2010s, and there has been remarkable increase in student mobility within the East Asian region. Today, international students from China, South Korea, Japan and other Asian countries comprise the great majority of international students in Japan. This is similar in China, where South Korean students form the largest international students in the last ten years. In South Korea also over 70 per cent of international students are from China, Vietnam, Mongolia and Japan. As a matter of fact, student mobility within East Asia is growing continuously. No doubt such a transnational student mobility within the East Asian region carries important implications for the future of the region. There would be more young people who can speak in their Asian neighbour’s languages and there would be more cultural exchanges within the region. This paper explores the new trends of international student mobility within East Asia. In doing so, it will investigate the causes of such a trend as well as the possible political, social and cultural implications of this growing transnationality within the region.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".