Transmediation as Radical Pedagogy in Building Queer and Trans Digital Archives
Bibliographic record
Abstract
This article analyzes a one-month, intensive digital collections lab focused on queer and trans community history, in partnership with the LGBTQ Oral History Digital Collaboratory, and based at Toronto’s The ArQuives: Canada’s LGBQT+ Archives. This collaboration between ten intergenerational scholars and two community organizations produced three digital exhibitions, focusing on post-1945 Toronto-based queer and trans activist history: Not a Place on the Map: The Desh Pardesh Project, an oral history project about the queer South Asian diasporic arts and culture festival Desh Pardesh (1988 - 2001); the Foolscap Gay Oral History Project, a 1980s community-based oral history project of Toronto gay life pre Stonewall; and gendertrash from hell, an early 1990s zine published by transsexual artists, sex workers, and activists Mirha-Soleil Ross and Xanthra Phillipa McKay. In analyzing our work within the context of radical pedagogy and critical DH practice, we focus on how we mapped spaces, (dis)inherited metadata, and designed interfaces that would offer tactile, affective engagements with these histories. We analyze our work through the lens of trans(affective)mediation, an approach that understands the conversion of analog to digital objects for online archives in relationship to anti-racist trans studies, affect, and the collaborative potential of community-engaged DH. We argue that this concept offers queer and trans community-based DH scholars and practitioners a means of challenging the ways in which white, cis-normativity is naturalized within both LGBTQ+ community archives and digital humanities tools and practices.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.040 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".