Ma(r)king Space, Selling Place: Afro-Caribbean Women’s Spatial Negotiations at Caribana
Bibliographic record
Abstract
This MA thesis explores the gendered geographies of Caribana, Toronto’s carnival-festival that celebrates Caribbean dance, music, band competitions, and masquerades/Mas. A longstanding feature of the festival has been the fence along the parade route, which separates the performers from the audience; the fence, which is meant to maintain security and order within the parade, has come to define the geography of Caribana since 2009 (Baute, 2009; News Staff, 2009; Aveling, 2009; Elder, 2016; Otchere, 2017). A prominent logistical feature within the parade, and an entry point into this thesis, I read the fence as a metaphor that interrupts “Canadian” consciousness and illustrates material and ideological representations of the nation’s multiculturalism policy. Specifically, I assert that the Multiculturalism Act codifies racial and cultural difference through its diversity rhetoric and, in turn, normalizes whiteness as an indicator of “proper” citizenship. Thinking about this process alongside the spatial politics of Caribana, the fence, then, unfolds into a material, rather than simply metaphoric site that divides the population according to racial, gendered, and sexualized markers. Afro-Caribbean women are particularly vulnerable to and implicated within these violent processes of place-making as they visibly dominate the parade. The thesis works with interdisciplinary scholarship, creative texts, and original accounts (semi-structured interviews and a survey questionnaire) to explore: how Afro-Caribbean women articulate a sense of belonging that disrupts the normalized construction of Canadian citizenship; how the spatial politics of Caribana are predicated on the maintenance and subversion of white settler nationalism—specifically within official multiculturalism and other policies that promote diversity; and how Caribana illuminates Black spatial negotiations and Black women’s liberatory geographies. This research complicates the multicultural nation by demonstrating the ways that Afro-Caribbean women’s relationship to Canada is contingent on their own creative imaginings of a “deterritorialized citizenship” (Walcott, 2001). Whether outside of, against, or next to “Canadianness,” Afro-Caribbean women’s sense of place is always in conversation with longer collective histories of Black and Caribbean movement, migration, and diaspora, whereby their struggles for liberation and freedom are always in motion.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.014 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".