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Record W4372294856 · doi:10.1111/1911-3838.12336

A Knowledge Synthesis of Anti‐Black Racism in Accounting Research*<sup>†</sup>

2023· article· en· W4372294856 on OpenAlex
Akolisa Ufodike, Inya Egbe, Bridget Efeoghene Ogharanduku, Temitope Edward Akinyemi

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueAccounting Perspectives · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaSheffield Hallam University
KeywordsRacismRacializationSociologyIntersectionalityDiversity (politics)Race (biology)Gender studiesPolitical scienceAccountingBusinessAnthropology

Abstract

fetched live from OpenAlex

ABSTRACT This structured literature review synthesizes studies that have investigated questions related to anti‐Black racism—namely, the discrimination and marginalization of Black people—in the accountancy literature and identifies opportunities for future research. This study is part of a larger research project that reviewed 161 articles and identified four themes relevant to accounting research on discrimination in general: anti‐Black racism, imperialism and postcolonialism, intersectionality, and diversity. Based on the 25 anti‐Black racism articles reviewed, this paper finds four key subthemes: demand for accountancy services and racial discrimination in accountancy practice, the racialization of professional accounting qualifications, Black professionals in academia, and the supply‐side fallacy. Furthermore, because studies at the intersection of anti‐Black racism and accounting are limited, this study proposes future research directions that will advance knowledge on various topics related to anti‐Black racism.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.045
GPT teacher head0.329
Teacher spread0.284 · 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