Reimagining Internationalization in Higher Education Through the United Nations Sustainable Development Goals for the Betterment of Society
Bibliographic record
Abstract
Higher education institutions (HEIs) play a critical role in creating and distributing the knowledge required to tackle the complex global challenges faced by society today. This role is frequently linked with the concept of the internationalization of higher education, but this concept in practice is also subject to criticism. This article argues that integrating the United Nations (UN) sustainable development goals (SDGs) into the teaching and learning functions, partnerships, research, and discovery functions of institutions has the potential to transform institutions and improve society through internationalization. In this article, the ideological and practical intersections of internationalization and the SDGs are discussed. Examples of initiatives around the world that have shaped societal discourse through the lens of internationalization and sustainable development are reviewed. The authors posit that integration of both concepts would enable HEIs to rise up to the global challenge of creating a better world for all.
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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 | 0.023 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".