Bibliographic record
Abstract
How do we understand the evolution of internationalization as a concept? Is a more diverse and inclusive internationalization replacing the western paradigm? Is there a shift in paradigm from cooperation to competition? Do we see an ongoing dominance of the internationalization abroad component at the cost of internationalization at home, or a more comprehensive and inclusive approach to internationalization? And is internationalization a key change agent towards innovation and global social responsibility of higher education? This contribution provides a critical reflection on internationalization in higher education, particularly in the current nationalist, populist and anti-global political climate! The challenges that institutions encounter are divers. There is pressure of revenue generation, competition for talents, and branding and reputation (rankings). There is pressure to focus on international research and publication, on recruitment of international students and scholars, and on the use of English as language of research and instruction. These challenges and pressures conflict with a more inclusive and less elitist approach to internationalization. In other words, there are tensions between a short term neoliberal approach to internationalization, focusing primarily on mobility and research, and a long term comprehensive quality approach, global learning for all.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".