International Joint Universities: Towards a New Model in International Academic Mobility
Bibliographic record
Abstract
The first International Joint University (IJU) was founded in Cairo, Egypt in 2002. Since then more than 20 IJUs have developed globally, 10 of these in the last five years and several more are in the development phase, symbolizing a growing, yet under researched, phenomenon in international academic mobility. The nature of the IJU transcends both the traditional university, with its strong ties to the nation, and other forms of international academic mobility including branch campuses, franchise programs, and joint and double degrees. The IJU is a cofounded institution, with independent legal status, cogoverned by two or more HEIs from different countries. This thesis on International Joint Universities (IJU) investigates this new phenomenon within international academic mobility. Determining the characteristics of the IJU within the ever-evolving landscape of International Program and Provider Mobility (IPPM) provides insight into a new model of international collaboration in higher education. This thesis defines the IJU through the identification of the underlying principles of reciprocity, collaboration and capacity development driving the distinguishing features as evidenced through an analysis of the founding, governance, positioning and functions of the IJU within the national higher education landscape of both the host and foreign partner countries. The conceptual frame for this study draws upon previous research on the internationalization of higher education broadly with a focus on international academic mobility more specifically. Conceptualization of the IJU fits within the IPPM framework which distinguishes between collaborative and independent approaches to international academic mobility. Through a multi-site case analysis of six of the IJUs across three host countries and engagement with four foreign partner countries, this study determines the distinguishing features and core principles that contribute to the IJU’s distinctiveness within international academic mobility. The study culminates in the presentation of the IJU model within international academic mobility situating the IJU in contrast to the International Branch Campus (IBC) and other forms of international academic mobility. Elucidating what differentiates the IJU within international academic mobility informs practice and supports further research and theorizing of this new phenomenon.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.018 | 0.028 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".