Bibliographic record
Abstract
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.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.084 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".