The 60 Years of Queer and Trans Activism and Care Project: Learning to Conduct Archival Research and Write Dramatic Verbatim Monologues
Bibliographic record
Abstract
This reflective essay describes a research course which provided undergraduate students with an opportunity to conduct archival research on six decades of queer, trans, Black, Indigenous, and People of Colour (QTBIPOC) activism and care that have challenged heteronormativity, cis-normativity, and racism in Canada. While there are many ways to share the findings of archival research, we chose to teach our students how to create dramatic verbatim monologues as the arts-based research method of verbatim theatre required students to use the words of activists themselves to explain why a particular moment of activism and care was needed. Students attended three different workshops during the full-year course from September 2022 to March 2023: a workshop in conducting archival research, a workshop about centring themselves and their communities in their research, and a workshop in verbatim monologue writing. Here, we reflect upon what these workshops taught us about archival research, working with Indigenous archival material, and rupturing systems of oppression in our own bodies. At the end of the course, students reported their take-aways from the course. This included a new understanding that it was possible to conduct research on topics they felt passionate about and that theatre-based research provided them with a way to express the findings of their research in forms other than writing essays. This new-found freedom was life-changing.
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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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.017 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".