Proud Deviants and Queer Multiples
Bibliographic record
Abstract
Queers living in the urban centre of Toronto have a strong history of resistance and deviant practices that skirt social norms in presenting and disseminating queer knowledge and art. These practices include the self-publication of zines, newspapers, posters, wearables, and art objects made as multiples. These materials, unlike popular mass media, are presented by and for queer audiences allowing for more nuanced, complicated, and affective understandings of the city's queer communities. Using an object-based approach grounded in Sara Ahmed’s Queer Phenomenology, I present queer multiples as guideposts for understanding the inherited queer history of Toronto and its influence upon contemporary artists. For Proud Deviants and Queer Multiples, I curated an exhibit comprised of a multi-generational slate of queer artists, multiples and Toronto’s queer history by showing works from my collection. In tandem with the multiples, I have juxtaposed queer archival materials such as scans of the covers of publications like The Body Politic and gendertrash, as well as the map of the Toronto Purchase. The combination of multiples and archives chart moments of tension and jubilation for queers living within the heteronormative colonial and institutional frameworks of Toronto. By using an artist-curator methodology, this exhibition creates the opportunity to consider the past, present and future of queer art-making in Toronto.
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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 | 0.003 |
| Science and technology studies | 0.020 | 0.025 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".