The internationalization of higher education scrutinized: international program and provider mobility
Bibliographic record
Abstract
Abstract During the last two decades, there has been an exponential increase in all forms of international academic mobility - student and scholar, programs and providers, policies and regulations, and the universal exchange of knowledge, ideas, values, and culture. The diversity in the modes and forms of mobility is unprecedented. As with all new developments, there are multiple benefits, as well as potential risks, and usually some unintended consequences. These need to be carefully monitored. This article focuses on changes in internationalization and new developments such as international program and provider mobility (IPPM). There has been a steady increase in the number of international branch campuses around the world, as well as in the establishment of new independent international joint universities by partner institutions from different countries, an increasing number of joint/double degree programs, and revolutionary developments in distance education. In view of these developments, the purpose of this article is to introduce the IPPM classification framework, which provides a new conceptual structure to analyse the meaning, trends, issues, and opportunities of IPPM activities around the world and to identify areas of further research and policy development necessary to harness the benefits of IPPM, especially in Latin America.a
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".