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Record W4200556519 · doi:10.1177/00754242211046316

Accent Bias and Perceptions of Professional Competence in England

2021· article· en· W4200556519 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

VenueJournal of English Linguistics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of British Columbia
FundersEconomic and Social Research Council
KeywordsStress (linguistics)PerceptionEthnic groupPsychologyCompetence (human resources)PopulationSocial psychologySalientLinguisticsSociologyPolitical scienceDemography

Abstract

fetched live from OpenAlex

Unequal outcomes in professional hiring for individuals from less privileged backgrounds have been widely reported in England. Although accent is one of the most salient signals of such a background, its role in unequal professional outcomes remains underexamined. This paper reports on a large-scale study of contemporary attitudes to accents in England. A large representative sample ( N = 848) of the population in England judged the interview performance and perceived hirability of “candidates” for a trainee solicitor position at a corporate law firm. Candidates were native speakers of one of five English accents stratified by region, ethnicity, and class. The results suggest persistent patterns of bias against certain accents in England, particularly Southern working-class varieties, though moderated by factors such as listener age, content of speech, and listeners’ psychological predispositions. We discuss the role that the observed bias may play in perpetuating social inequality in England and encourage further research on the relationship between accent and social mobility.

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)0.001
metaresearch head score (Gemma)0.146
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.146
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.341
Teacher spread0.305 · 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