Internationalization of Higher Education in Post-Soviet Ukraine
Bibliographic record
Abstract
Internationalization of Ukrainian higher education is becoming an important topic of discussion at national and institutional levels. Ukrainian universities consider internationalization as a major tool to impel much needed internal change and improve access to knowledge, research and funding across borders. Ukrainian students view international opportunities as critical to succeed in the European job market. Ukraine, an ex-USSR republic, which borders NATO and the European Union countries on the West and Russia on the East, maintains a semi-peripheral position in the international knowledge system. It tries to locate its own niche internationally and still hesitates about which developmental trajectory to follow. This paper investigates how Ukrainian universities approach the development of international outreach capacity in order to interact with potential partners on student/faculty international mobility, curriculum development, joint/dual degree initiatives, etc. Disproportionate distribution of already scarce resources, the role of historical preference towards cross-border and linguistic inclinations, and current active protests against the state government’s decision to stop the preparation process for an EU agreement emerge as important factors to shape the current Ukrainian higher education internationalization agenda.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".