Towards Different Conversations About the Internationalization of Higher Education
Bibliographic record
Abstract
As institutional commitments to internationalize higher education continue to grow, so too does the need to critically consider both the intended purposes and actual outcomes of the programs and policies that result. In particular, there is a risk that internationalization efforts may contribute to the reproduction of harmful historical and ongoing global patterns of educational engagement. In this paper we explore these issues by offering a social cartography of four possible articulations of internationalization, and considering their relation to an often-unacknowledged global imaginary, which presumes a colonial hierarchy of humanity. We also address the practical and pedagogical possibilities and limitations of enacting each articulation within mainstream institutional settings, and propose that social cartographies offer a means of reframing and deepening engagement with the complexities, tensions, and paradoxes involved in internationalizing higher education.
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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 | 0.037 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.019 | 0.095 |
| Scholarly communication | 0.026 | 0.028 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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".