Examining National Higher Education Policy Initiatives in OECD Countries Attracting a Large Number of International Students
Bibliographic record
Abstract
This study aims to comparatively examine national strategic higher education policy initiatives of selected OECD countries attracting a large number of international students. As an example of a multiple-case study, the study group comprised Australia, New Zealand, the United Kingdom, and Canada. The data were the official strategic education policy documents of these countries and obtained from the official government websites of these countries. The qualitative thematic analysis method was employed to analyze the data. The study concluded that visa and employment convenience, expanded national scholarship opportunities, advertisement and promotion of higher education, accreditation/recognition-related strategic policy initiatives, government and third-party partnerships, and strategies to enhance student well-being were the main themes observed in the national higher education policy documents. Analyzing the common similarities and tendencies in top-ranked OECD countries' national strategic higher education policy initiatives, this study offered a visionary perspective for other countries to revise or redesign their national education policies to attract more international students in the future.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".