REBECKA TAVES SHEFFIELD, Documenting Rebellions: A Study of Four Lesbian and Gay Archives in Queer Times
Bibliographic record
Abstract
In Documenting Rebellions, Rebecka Taves Sheffield presents well-researched and thoughtful histories of four archives that emerged out of the gay and lesbian movement in North America: two in California, one in New York, and one in Toronto, where the author lived, studied, and worked in the lead-up to this study.She traces the archives' origins and development, de-radicalization and strategic neutrality, and transitions from volunteer-run to professionally staffed organizations.She then analyzes and compares these histories in order to assess the archives as going concerns, considering their sustainability strategies over time, their volunteer and paid labour, their material needs for space and stable funding over time, their independence from (or domination by) large academic institutions, and their success (or failure) in changing along with the communities they attempt to serve and represent with their collecting and outreach activities.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.041 | 0.011 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".