Internationalization of the university: factors impacting cultural readiness for organizational change
Bibliographic record
Abstract
In response to an increasingly globalized world, universities are engaged in an ambiguous and unclear journey of internationalization for economic and political reasons, and guided by different ideologies. Universities’ distinctive nature and unique characteristics give culture a prominent role in mediating the university environment. This study examines cultural readiness for internationalization at two US universities at the micro (individual), meso (organizational) and macro (external stakeholders) levels. The Cultural Readiness for Internationalization model, introduced here, identified multiple factors impacting cultural readiness for organizational change. First, it is important to ensure congruency between espoused and enacted values among the institution’s membership and second, it is critical to align this value congruency with the institution’s mission. Third, the extent to which senior leadership perceived the institution’s community as local and/or global influenced the level of support for internationalization. Finally, economic and political influences can leverage the extent to which internationalization is articulated as an institutional priority.
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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 | 0.003 | 0.016 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".