Reflections on symmetries and asymmetries in the internationalization of higher education in Brazil and Canada
Bibliographic record
Abstract
In this article we reflect on how internationalization is articulated in different ways within the context of a relatively new global educational credentials export industry (GEEI). This industry emerged largely as a response to decreased public funding of higher education in specific 'education export' countries. We take Canada as an example of one of these countries, to illustrate how the marketization of internationalization in higher education is reproduced and contested within that context. We contrast how internationalization is articulated in Canada with the context of internationalization in Brazil. We offer the case of a Brazilian university - UNILA, the Federal University for Latin American Integration, as an example of internationalization that attempts to challenge the global credentials export industry. mple. The example of UNILA shows how a commitment to international public service stands in contrast to transactional internationalization processes that sustain dominant trends of student and knowledge flows in North-South asymmetrical engagements.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".