International education policymaking: A case study of Ontario’s Trillium Scholarship Program
Bibliographic record
Abstract
This paper explores Ontario’s international education policy landscape through illuminating the discursive struggles to define international student funding policies, in particular the international doctoral students’ Trillium Scholarship. Adopting Hajer’s (1993, 2006) Discourse Coalition Framework, the study engages with three research questions: What paved the way to this funding policy? Who were the actors engaged in this policy landscape? How has the argumentation over this policy influenced the international education policy context in Ontario? Argumentative discourse analysis was used to analyze three data sources: news articles, policy documents, and interviews. Two storylines were identified: international student funding is desirable and beneficial to Ontario versus Ontario first. Whereas the first storyline achieved hegemony, the second succeeded in bringing discourses of protectionism to the forefront influencing the government’s future engagement with international student funding. The paper ends with three observations on Ontario’s international education policy landscape. This study contributes to our understanding of how international student funding can be highly political and influenced by non-education policy spaces and discourses.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.043 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".