We Have Always Been Here: Pelau MasQUEERade Disturbing Toronto Pride History
Bibliographic record
Abstract
This article addresses the uneasy tensions and overlaps between race, sexuality, and citizenship, by focusing on the moments when queer diasporic people of colour slip “in” and “out” of Pride Toronto—the organization that hosts the annual Toronto lesbian, gay, bisexual, transgender, and queer Pride Parade. Drawing on Pride Toronto’s thirtieth anniversary promotional material, released in 2010, and the organization’s 2002 five-year strategic direction plan, the author applies a queer feminist diaspora reading practice to problematize how the documents, taken together, presents Pride’s queer history in Canada, which continues to be narrated by the organization in ways that de-racialize queer subjects and invoke white gays and lesbians as central to its story. Pelau MasQUEERade, a Caribbean queer diasporic group that participates in the Pride Parade, reveals how the histories of queer diasporic people of colour are strategically appropriated and belatedly visible only in sporadic moments in the documents. Pelau MasQUEERade’s presence works to disturb normative accounts of Pride, while simultaneously opening the door to overlapping histories of queer diasporic people in the event. The group reworks Pride Toronto’s de-racialized narrative of sexuality by gesturing to the ways in which race, sexuality, and notions of citizenship operate in multiple and contradictory ways.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.037 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".