Racist nativist microaggressions and the professional resistance of racialized English language teachers in Toronto
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
English language teaching upholds racist nativist notions that competent teachers are white native speakers of English born in majority-white countries. These notions manifest when international students, expecting to be taught by these speakers, are skeptical about having a racialized instructor, who may be seen as non-native to English and the nation where it is natively spoken. Rather than overt, this skepticism may appear in the form of microaggressions. Informed by critical race and resistance theories, this article uses interviews with 10 racialized teachers in Toronto, Canada to detail the racist nativist microaggressions that they experience at work and their professional resistance strategies that combat these microaggressions. The findings describe the following microaggressions: interrogations of the teachers’ nativeness, insinuations of their foreignness to English, and behavioral indications that they are ‘invading’ the classroom. Their professional resistance either conformed to or sought to transform notions of the supremacy of white (Canadian) teachers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it