Fostering Global Norms of Research Excellence: National Policies and Strategic Responses of Public Universities in Central and Eastern Europe
Bibliographic record
Abstract
The history of higher education in Central and Eastern Europe goes back to medieval times when the first universities were established in the early XIV century. During the industrialization period, a wide range of technical universities emerged in the region, while the fall of the communist regimes further fuelled the rise of new regional public universities there. Currently, this region provides a diverse set of public universities that vary in their histories, traditions, foundational rationales, etc. Unprecedented openness of Central and Eastern European countries to external norms and concepts following the collapse of the Soviet Union offers a unique research context to investigate the diffusion and local interpretation of global norms.By examining the national policy interpretations of global research excellence norms in Poland, the Czech Republic and Ukraine, and the role of university organizational identities in shaping their strategic responses to these norms, this study makes an important contribution to our knowledge of universities as organizers of their institutional environments, bridging two fundamental approaches to universities as enactors of broader social norms seeking legitimacy and as strategic actors pursuing unique organizational goals. Theoretically, this study explores how the combination of new institutionalism and resource dependence theory through the lenses of Oliver’s strategic responses framework in conjunction with the literature on organizational culture and identity could explore the phenomenon of university research excellence at three levels: macro (global), meso (national), and micro (organizational). Drawing extensively from 38 interviews with policy experts and university leaders and supplemented by document analysis, my findings provide a richer understanding of the interplay between the diffusion of global norms in national contexts as well as the role of national specificities and organizational attributes in shaping diverse organizational responses across the three national contexts and the nine universities. As the first study of diverse public university types and the repertoire of their strategic responses to research excellence norms in Central and Eastern Europe, my thesis contributes to filling the gap in the mainstream literature by including the universities from the outside of “the global core” in the scholarly discussion on university research excellence.
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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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".