Strategic Benefits, Symbolic Commitments: How Canadian Colleges and Universities Frame Internationalization
Bibliographic record
Abstract
This article examines how Canadian colleges and universities formally articulate their priority activities for internationalization, and what discursive rationales justify their approaches. Data come from 32 publicly-available internationalization strategies published in English by Canadian colleges and universities. In terms of practices, we find that institutions are adopting a largely similar set of activities, focused on partnerships and student and scholarly mobility. In terms of their justifications, we find that most institutions combine the strategic benefits of revenue generation and reputational prestige with symbolic commitments to diversity and excellence. We argue that by drawing on multiple rationales, internationalization strategies imbue the same generic activities with many meanings, which helps the internationalization project garner acceptance from an institution’s diverse stakeholders. In concluding, we also point to a number of noticeably absent ideas, including equity, empathy, humility, and civic responsibility
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.028 | 0.032 |
| Scholarly communication | 0.026 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| 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".