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Record W7117482722 · doi:10.1111/soc4.70158

Disciplining Desire: Rethinking Racial Capitalism Through Black Queer Resistance

2025· article· en· W7117482722 on OpenAlexafffund
Seon Yuzyk

Bibliographic record

VenueSociology Compass · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Sexualities and LGBTQ+ Issues
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaGovernment of Canada
KeywordsHeteronormativityCapitalismQueerResistance (ecology)Human sexualityNarrativeRacial politicsPoliticsDiscipline

Abstract

fetched live from OpenAlex

ABSTRACT In Black communities, heteronormativity installs the belief that Black people are inherently straight, erasing Black Queer histories. Despite its significance, homophobia remains underexamined in racial capitalism discourse, which neglects the interplay of race, gender, sexuality, and capital. This omission reinforces harmful narratives that Queerness is “un‐African.” This paper employs Foucauldian genealogy to uncover how Black people have lived otherwise, tracing the disciplinary mechanisms enforcing heteronormativity. Sexual violence and exploitation are shown as central to racial capitalism, sustaining racial and economic domination. I argue that heteronormativity disciplines Black sexuality and perpetuates exploitation, illuminating racial capitalism's uneven impacts on Black Queer, Trans, and Women of Color. The paper highlights the radical potential of Black Queer resistance to disrupt heterosexual orthodoxy and inspire transformative Black political imaginaries. Findings contribute to a reimagined racial capitalism discourse, attuned to the interplay of race, sexuality, and gender.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.049
Scholarly communication0.0080.008
Open science0.0010.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.052
GPT teacher head0.380
Teacher spread0.328 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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