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Record W4411683240 · doi:10.1177/00219347251350966

Racial Capitalism and the Propaganda of Conservative Economics

2025· article· en· W4411683240 on OpenAlexaff
Prentiss A. Dantzler, Jason Hackworth

Bibliographic record

VenueJournal of Black Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCapitalismRacismSociologyRacial formation theoryPolitical scienceNeoclassical economicsPolitical economyEconomicsGender studiesLawPolitics

Abstract

fetched live from OpenAlex

Racial capitalism has been an active terrain of political economy debate since the 1970s, but the last 5 years have seen a wider diffusion of the concept. We identify one modern component of racial capitalism that has seldom been discussed in extant work: the role of conservative economics at legitimating racial capitalist processes. To this end, we raise the following question: What does a narrative of support for racial capitalism look like in contemporary political economies, where racism denial is pervasive in political discourse, and trust in authorities are at an all-time low? We submit that narratives legitimating contemporary racial capitalism exist, but they are more subtle, indirect, and more plausibly deniable than the narratives that supported chattel slavery and the 100 years of Jim Crow that followed. The Civil Rights Era provided a legal basis for anti-discrimination efforts previously diluted by American jurisprudence and law. In this essay, we engage in a broader conversation about the intersections between discourse and structure before explicating exactly how conservative economics supports and reinforces racial capitalism. Explicating the components of this architecture is crucial to illustrating the value of racial capitalist approaches within the political economy canon.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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