The Emergence, Development and Survival of Four Lesbian and Gay Archives
Bibliographic record
Abstract
Lesbian and gay archives, particularly those established within the context of the homophile, gay liberation, and lesbian feminist movements, serve as social movement organizations (SMOs). That is, they are organizational and administrative members of activist communities that acquire, manage, and share resources for the purpose of collective action for social change. Archives are nevertheless absent from literature on social movements and social movement theory. This project was designed to expand on current research in the fields of archival studies, social movement studies, and sexuality studies to better understand the experiences of lesbian and gay archives. A multiple case study was conducted at four community grown archives: The Canadian Lesbian and Gay Archives, the ONE National Gay and Lesbian Archives, The June L. Mazer Lesbian Archives, and the Lesbian Herstory Archives. Site visits took place over six months in 2013 and 2014, during which time interviews were conducted with 33 community archivists, volunteers, and community partners. In addition, more than 20,000 pages of organizational records related to the founding and development of these archives were reviewed. By tracing the emergence, development, and resource struggles of four lesbian and gay archives, this dissertation shows how these organizations have been shaped by broader movement goals, local geographies, socio-political structures, and the particular interests and energies of those who have nurtured their collections over the years. I examine how these archives have sustained themselves over time. Discussions with community archivists, volunteers, and community partners have generally confirmed that the four archives that inform this study are SMOs, but have also raised important questions about the sustainability of archives established by and for social movements. The dissertation tells a history of each archives and comments on the common challenges that they have faced over the past forty-plus years. Engagements between these archives and their local academic institutions are also explored, as are their continuing relationships with the communities they serve. By tracing the emergence and development of these organizations, this project uncovers representational politics, institutional pluralism, generational divides, shifting national politics, interpersonal relations, and challenges with sustainability, both financial and otherwise.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".