Exploring the modes of internationalization : \nthe case of UK Business Schools
Bibliographic record
Abstract
Recently there has been a large expansion of Higher Education (HE). Master of Business Administration (MBA) degree programmes have seen a large rise in international applications. As a consequence, the UK is gaining more revenue from the Internationalisation of Higher Education than the export of iron and steel. Subsequently, many Higher Education Institutes (HEI’s) have over a decade of \nexperience of operating in the international market. In addition other HEI’s from Australia, Canada and USA are competing in this new environment. Events may go even further with French Business Schools now starting to deliver MBA degree programmes taught in English at various overseas locations. Consequently, countless lessons are being learnt concerning the best way of entering the international market. Collaborative agreements, setting up subsidiary colleges and \ndelivery directly abroad have all been tried. This paper attempts to apply theories of internationalisation to this service sector in order to help better understand the various choices available for HEI’s. A variety of case models will be contrasted. In conclusion it seeks to provide advice also on future internationalisation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".