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Record W4200324610 · doi:10.1177/14687968211055808

“Your English is so good”: Linguistic experiences of racialized students and instructors of a Canadian university

2021· article· en· W4200324610 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEthnicities · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRacializationRacismGender studiesSociologyVietnameseEthnic groupPsychologyNormativeSocial psychologyLinguisticsRace (biology)AnthropologyPolitical science

Abstract

fetched live from OpenAlex

Racism has increasingly been exposed and problematized in public domains, including institutions of higher education. In academia, critical race theory (CRT) has guided scholars to uncover everyday experiences of racism by highlighting the intersectionality of race with other identity categories, among which language constitutes an important, yet underexplored, component. Through the conceptual lens of CRT and counter-storytelling as a methodological orientation, this study investigated how racialized graduate students and faculty members at a Canadian university experienced racialization and racism in relation to issues of language, including communication and the use of ethnic names as semiotic markers. Individual and focus group interviews generated participants’ stories, to which we applied a thematic analysis. Participants generally felt that they were forced into pre-determined and essentialized categories of race, ethnicity, nationality, and language. Racialized non-native speakers of an official language—English or French—often received compliments or inquisitive comments on their language proficiency, which further accentuated their raciolinguistic Otherness and caused pain. Conversely, racialized native speakers did not report receiving compliments on language. For East Asian participants especially, speaking White English seemed to offset their racial stigma and psychologically separated them from non-native, English-speaking East Asian immigrants who looked like them. These experiences indicate normative expectations. The participants felt they were expected to not only speak, write, or communicate in the White normative language and manners, but also to use or not use an Anglicized name against their will. These impositions were questioned and resisted by some participants, and antiracist consciousness was expressed. The participants’ voices encourage universities to validate their stories as well as their ways of telling their stories.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.077
GPT teacher head0.423
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it