Representing the Problem of (Un)Ethical Practices in Canada’s Post-Pandemic International Student Policy Landscape
Bibliographic record
Abstract
This study investigates how the Canadian policy landscape toward international students has changed since the pandemic. It uses a policy mapping of 97 announcements made between January of 2022 and March of 2024 by the federal government, the governments of Ontario and Quebec, and three organizations with expertise in international or higher education. Using the “What’s the problem represented to be?” (WPR) approach, the article analyses the increasing attention being paid to (un)ethical practices as a lens through which policy bodies are constructing the role of international students in Canada. This highlights the differing representations of the “problem” of ethical practices, as well as the call-and-response nature of announcements between policy actors. The focus on ethical practices has created links between international students and national issues such as housing shortages and labour market needs, assigning responsibility to unscrupulous actors but also to students themselves for creating these challenges.
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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 | 0.001 | 0.001 |
| 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".