Repression of Pro-Palestinian Student Movements in Canadian Universities: Ideological and Institutional Challenges to Free Expression post-October 7th, 2023
Bibliographic record
Abstract
This study examines the repression of pro-Palestinian student movements across Canadian universities in the aftermath of October 7th, 2023, focusing on the ideological and institutional challenges students have faced. Drawing on case studies from Concordia University, McGill University, the University of Toronto, and the University of British Columbia, the study analyzes how institutional responses, media narratives, and external political pressures–including donor influence have converged to constrain student activism. Using a mixed-method approach, the research explores how pro-Palestinian student activists have faced surveillance, disciplinary actions, and public vilification. Particular attention is paid to the role of religion, as Muslims, marginalized, and anti-Zionist Jewish students have been especially targeted through the racialization of religious practices, and the framing of the movement as inherently extremist or sectarian. The findings reveal a broader ideological and institutional struggle over the limits of dissent in Canadian higher education, shaped by settler colonialism, neoliberal governance, securitized campus environments, and Islamophobic and antisemitic discourses. Despite these repressive measures, pro-Palestinian student activism has persisted–and in many cases, intensified. Students have shown extraordinary resilience through coalition-building, strategic mobilization, and the use of digital platforms and cultural practices to assert their demands and reframe narratives. This study contributes to debates on student activism, political repression, academic freedom, freedom of speech and the intersection of religion and resistance in a polarized academic landscape.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.014 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".