Orientalism and linguicism: how language marks Iranian-Canadians as a Racial ‘other’
Bibliographic record
Abstract
This study examines the social experiences of Iranian female immigrants in schools in Toronto, Canada. Drawing on postcolonial theory and critical whiteness studies, I interrogate the ways in which ‘Oriental’ subjects are Othered among their peers, and how whiteness is established as the invisible norm. This study observes the role that having an immigrant, English-as-a-second-language (ESL) identity plays in shaping the participants’ social experiences at school. The women in this study rejected racism as a plausible cause of their social exclusion. I suggest two possible explanations for this: (1) the ‘Aryan myth’, which still heavily circulates within Iranian communities, constitutes a subtle mechanism by which white supremacy is culturally inherited by many Iranians; (2) the participants’ ability to ‘pass’ as white acted as a privilege which made race a less salient marker of difference to them. Instead, their status as the ‘Oriental Other’ was most visible when language was concerned.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.019 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".