Enacting Politics through Art: Encounters between Queer and Trans of Color Organizers and the Canadian City.
Bibliographic record
Abstract
This ethnographic study investigates the role of the arts in the relationship between urban governmental institutions and queer and transgender people of color (QTPOC) community organizations. Toronto is a fitting site for this project given that the city is intensively mobilizing the arts to foster urban economic development and that it is uniquely emblematic of Canada’s regulatory embrace of racialized, gendered and sexual minorities. The findings from this study are derived from two years of ethnographic fieldwork and 63 semi-structured interviews carried out between 2012 and 2014 among state arts institutions, funding bodies and community arts initiatives. Drawing from the fields of social work, anthropology, queer studies, and critical ethnic studies, I argue that the arts operate as a means of constructing the neoliberal welfare state through the incorporation of QTPOC. These inclusionary creative citizenship practices enable QTPOC to engage in a feelings-based mode of community development in ways that are nevertheless constrained by how state institutions administer the programs that fund these initiatives. Each chapter of this dissertation is organized around an ethnographic dilemma that brings into focus how the arts surface as the solution to the diverse challenges that government institutions and minority community organizations face. As a uniquely elastic mode of social action, the arts serve as the linchpin between QTPOC efforts to counter the intertwined mechanisms of racism, sexism, transphobia and homophobia, and municipal imperatives to promote economic growth and address the social exclusion of marginalized populations. By using the arts to explore the interrelated workings of urban government and grassroots collectives, this study demonstrates how questions of space, time, feelings, humanity and political economy are deeply implicated in the politics of making racialized, gendered and sexual difference.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.063 | 0.030 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".