Bibliographic record
Abstract
One of the key rationales for internationalization used by Canadian higher education institutions to legitimate what has become an industry in student recruitment is that of educating for global citizenship, intercultural learning, and developing skills to remain competitive in a global marketplace. This chapter challenges the notion of internationalization as a naturally occurring phenomenon, much like globalization or multiculturalism, and argues that it is an ideological frame produced through texts such as definitions and policies. The analysis in this theoretical chapter is informed by concepts in Dorothy Smith’s institutional ethnography, a method of inquiry, which, conceptually, offers a way to see how textual practices impact people’s lives. The chapter argues that the texts of ‘international’ and ‘internationalization’ form the ruling relations of the internationalizing university. Texts such as definitions of internationalization, federal policies, and multiculturalism are analyzed to show how they order the lives of international students from Asia discursively. International students, from Asia in particular, are constructed as the bearers of culture and as economic assets, and yet their cultural differences are mostly contained and their racialization made invisible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.035 | 0.032 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".