A laugh for the national project: Contemporary Canadian blackface humour and its constitution through Canadian anti-blackness
Bibliographic record
Abstract
This article investigates the ways that the ostensible humour associated with contemporary blackface incidents in Canada is constituted. It argues that the conditions of possibility for contemporary Canadian blackface humour are an anti-black libidinal economy dependent upon the tropes of biological racism, and a socially embedded, psychic association of the Black body with pleasure that was entrenched through slavery’s relations of domination. With the specificities of anti-blackness in view, this article refines Simon Weaver’s concept, embodied racism, to emphasize that it is a form of biological racism that has historically targeted Black people, and continues to do so today. Then, building upon these foundations, I argue that contemporary Canadian blackface humour is constituted and intensified by the specific racialized social relations in Canada, such as its postracialist claim to being racially egalitarian, and the ways it mobilizes multiculturalist discourse to make Blackness perpetually foreign and out-of-place in Canada—matters that, in part, characterize the contemporary Canadian colonial project. The article therefore suggests that making clear these ways in which contemporary Canadian blackface is only legible as humour through racialized social relations is a necessary component of challenging suggestions that blackface is harmless, non-racial humour.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.039 | 0.024 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".