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Racial, Ethnic, and Cultural Stereotypes in Teaching English

2018· other· en· W2909247197 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.

Bibliographic record

VenueThe TESOL Encyclopedia of English Language Teaching · 2018
Typeother
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEssentialismStereotype (UML)Ethnic groupSocial psychologyConstruct (python library)Social categorySociologyConflationPsychologyNegotiationGender studiesLinguisticsAnthropologySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

As a construct of social psychology, a stereotype is a simplified fixed belief about characteristics of a social group. Essentialism , a similar notion seen in cultural studies, is an assumption that unique features of a social group exclusively define its members. Institutional and everyday discourses shape stereotypes and essentialist ideas about the socially constructed categories of race, ethnicity, and culture, which are often conflated. These categories intersect with language and other differences, forming and imposing identities. Research suggests that learners accommodate, negotiate, or resist stereotypes, such as the model minority and reticent Asian students. Students also hold stereotypical and essentialist images of their peers, teachers, and target language speakers in general, reinforcing the superiority of Whiteness and native speakerness. It is necessary for teachers and students to become critically aware of stereotypes and essentialism and pursue a vision of antiracism and antilinguicism. Institutional practices should also follow this vision.

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)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
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 science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.396
Teacher spread0.370 · 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