Repurposing beauty pageants: The colonial geographies of Filipina pageants in Canada
Bibliographic record
Abstract
This paper considers how notions of beauty and performances at pageants transform as they move across different colonial times and spaces. It examines how gender, racial, and sexual subjectivities take shape among cisgender Filipina women who participate and organize community-based pageants on the traditional and ancestral territories of the Musqueam, Skxwú7mesh, and Tsleil-Waututh peoples (Vancouver, Canada). I analyze observations and interviews conducted with Filipina/os who organize and participate in community pageants. Based on this examination, I argue that spatial processes make apparent the shifting nature of gendered, racialized, and sexualized pageant performances. Pageant ideals change with migration as white heteropatriarchal logics, which are enmeshed in settler colonial projects of Canada, make grooves into the ways Filipino gendered sexualities come to be in Canada. More broadly, the paper speaks to the ways in which power works with and through space through the logics of race, gender, and sexuality. It outlines how racialized women’s feminine heterosexuality is made legible by liberal scripts designed for immigrants in the white settler colonial context of Canada. Thus, the paper sets in motion questions of how intersections of power are shaped by contemporary forms of colonialism.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".