Goals, Strategies, and Achievements in the Internationalization of Higher Education in Japan and Taiwan
Bibliographic record
Abstract
International knowledge and skills are essential for success in today’s highly competitive global marketplace. As one of the key providers of such knowledge and skills, universities have become a key focus of the internationalization strategies of governments throughout the world. While the internationalization of higher education clearly has certain benefits for students, schools, the national economy, and the international community, each country gives a different degree of importance to each of these various benefits. The purpose of this study was threefold: 1) to determine which benefits of the internationalization of education are deemed most important in Taiwan and Japan; 2) to determine which measures are most effective for realizing these benefits; and 3) to determine the extent to which these measures have actually been carried out. A questionnaire was used to obtain the views of 100 professors, 50 in Taiwan and 50 in Japan, as to the current situation in their respective countries. The results indicate that there are significant differences between the two country’s reasons for promoting the internationalization of education, as well as in their respective internationalization strategies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".