Mobility in the Internationalisation of Higher Education Institutions
Bibliographic record
Abstract
International mobility of higher education institutions’ members within the European Union is explicitly encouraged and used as one of the higher education institutions’ quality criteria. This paper aims to contribute to the analysis of the phenomenon of international mobility between higher education institutions, especially within the European area in the broad sense, and for which the ERASMUS+ Programme is paradigmatic. The authors have been linked to mobility processes by addressing issues of internationalisation and receiving and sending students and teachers in and out of their institution, and/or hosting them in curricular units taught by them or in other training actions. It is in this context that theoretical reflection has been carried out, to respond to the objective of analysing the relevance of mobility in the internationalisation of higher education institutions and to reflect on questions of its evaluation. It is concluded that there is interest in allowing a mutually enriching scientific dialogue for the personal and professional development of those involved – students, academics and other staff members. Furthermore, it is institutionally considered that the higher education institution is promoting its quality and image if it provides an in-depth exchange of ideas and practices that foster improvements in teaching and research of the institutions involved. It is also concluded that there is a need for structures to respond to this new reality and that the evaluation processes can contribute to measuring and promoting it.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".