Student voices on social relations of race in Québec universities
Bibliographic record
Abstract
This study aims to shed light on the role of the university as a space contributing to (re)production and even to the reification of social relations of race. To do this, we sought the views of 30 students enrolled in first-year undergraduate studies to analyze how institutional racism occurs through microaggression interactions, i.e. subjective or overt racism expressed by individuals or through institutional practices, understood as indirect processes that may have unplanned effects on racialized groups via feelings of inequitable treatment. These students were born to immigrant parents from Haiti and sub-Saharan Africa. This article shows that, despite a denial of systemic racism by the Québec government, our data do reveal unequal social relations of race in the daily lives and practices of academic institutions. Students, through their words, tend to emphasize the existence of a boundary linked to power relations between those they name as Whites and Others. They relate incidents of microaggression, which seem normal or banal for the majority group, often taking the form of humour, which constantly bring them back to their otherness, their social positioning vis-à-vis power relations, which they describe as inferiorizing. They also highlight the perception of these boundaries at the institutional level in the choice of staff hired, in the whitewashed image of the institution in promotional materials, in the predominance of formal and hidden ethnocentric or racist curriculum, and in student life.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".