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Record W3201236580 · doi:10.22230/cjc.2021v46n3a4155

“Multicultural Snake Oil” and Black Cultural Criticism

2021· article· en· W3201236580 on OpenAlexaffvenueabout
Daniel McNeil, Chris Russill

Bibliographic record

VenueCanadian Journal of Communication · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsCarleton UniversityQueen's University
Fundersnot available
KeywordsCriticismMulticulturalismSociologyPolitical scienceGender studiesLawPedagogy

Abstract

fetched live from OpenAlex

This article presents a wide-ranging and reflective dialogue between Daniel McNeil and Chris Russill on the ideological, institutional, and cultural dimensions of multiculturalism in Canada, particularly as they intersect with Black cultural criticism. McNeil critiques the banal and bureaucratic deployment of multiculturalism as a state strategy and media discourse, characterising it as “multicultural snake oil”—a symbolic and ideological product that masks systemic inequalities while promoting a sanitised image of diversity. Drawing on personal experiences, archival research, and cultural theory, McNeil explores how multiculturalism functions as both a mythology and a mechanism of governance that often marginalises radical Black thought and expressive cultures. The conversation examines the work of figures such as Rosemary Brown and Frances Henry, contrasting their institutional engagements with the more subversive, ironic, and aesthetic approaches of Black Atlantic intellectuals like Paul Gilroy and Armond White. Through this lens, the article interrogates the limits of recognition-based politics, the commodification of diversity, and the challenges of sustaining critical, decolonial, and liberatory practices within academic and cultural institutions. Ultimately, it calls for a more nuanced, historically grounded, and politically engaged form of Black cultural criticism that resists co-optation and reclaims the radical potential of multicultural discourse.<br/>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.239
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2021
Admission routes3
Has abstractyes

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