Racism, eh? Interactions of South Asian Students with Mainstream Faculty in a Predominantly White Canadian University
Bibliographic record
Abstract
Considerations of the interactions between minority students and mainstream faculty in academe have only partially portrayed the enigma of racism. Through this qualitative study of twenty-two South- Asian-students in a predominantly white Canadian university, we investigate how discourses of racism are categorically produced and performed through power relations, notions of ethnicity, negative images and stereotypes that acquire ideological significance in the ivory tower. We argue that both overt and covert racism, more than a mere representation of tension and two solitudes is programmed in the powerful postmodern/postcolonial discourse of the culture of the "Other ". As practiced in the current teaching and learning environment, it seems that differential treatment, inequity, and negligence are perceived in the daily interactions between minority students and mainstream faculty, affecting overall evaluations, grading, tracking, and teaching styles. This analytical inquiry recommends that a critical mass of professors from visible minority and designated groups is needed to address these negative perceptions, leading to a wholesome academic environment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.016 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".