How a digital archive is preserving Canada’s history of LGBTQ+ activism
Bibliographic record
Abstract
LGBTQ+ organizations in Canada are gearing up for a “Rainbow Week of Action” that will feature rallies across the country calling on governments to do more to support LGBTQ+ communities. Such events are part of a long history of LGBTQ+ campaigning and protest. However, in a time when anti-LGBTQ+ movements are growing, recording that history is as important as ever. As increasingly advanced digital technologies pervade every aspect of our lives, making that history easily accessible online can help contemporary movements learn from previous generations of activists. At the Lesbian and Gay Liberation in Canada project (LGLC), we are aiming to learn from lesbian activists of the past to uncover which of their practices can inform the creation of online history resources today. Our project, working alongside the University of Ottawa’s Digital Humanities Lab and Toronto Metropolitan University Libraries’ Collaboratory, highlights how feminist and queer practices can create meaningful change using digital methods and tools.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.053 | 0.025 |
| Scholarly communication | 0.041 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 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".