Once Upon a Queer Time: A Study of Reparative and Speculative Histories in the Work of 2SLGBTQ+ Contemporary Artists
Bibliographic record
Abstract
In this portfolio dissertation I attend to the ways in which artists have navigated the various challenges of doing 2SLGBTQ+ history through creative practice. I focus on the archive (both tangible and conceptual) as an important intervention site for queer and trans artists seeking to expand how 2SLGBTQ+ histories are depicted. Through a series of case studies on contemporary artworks, I ask: What are the specific strategies that queer and trans artists have used to interrogate gaps in archives? And, relatedly, what strategies have these artists used to address some of the broader methodological challenges of researching and (re)presenting 2SLGBTQ+ histories? I argue that artists’ adoption of historiographic strategies may effectively bypass methodological challenges and present alternative models for gaining insight into queer and trans histories. Within the context of the broad archival turn in cultural theory and the archival turn in contemporary art, the four essays in this dissertation loosely chart the period from the mid-1990s to the present, during which queer and trans artists in North America have continuously been working with the concept, spaces, and materials of archives. Three of four essays focus on American artists, while one focuses on Canadian artists. The artworks engage with a range of historical periods and contexts, from the turn of the twentieth century to as recently as 2008. I attend to a series of interrelated but distinct methodological questions across the case studies, including: What kinds of materials can constitute a queer archive? What might constitute queer forms of historical evidence? And, what happens if we take speculative narratives seriously as a historical mode? Drawing on Eve Kosofsky Sedgwick’s concept of reparative reading (2003) I describe the artists examined in this dissertation as reparative in their approach. What this looks like is varied; some of the artists moonlight as archivists or historians, others engage magical realism and/or speculative fiction as historical methodologies, and still others seek to reactivate the past in the present. Across the case studies, I focus on speculative fiction as a particularly generative reparative response to the historical absences and erasure experienced by minoritized communities.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.037 | 0.061 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| 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".