Coming Out of the Archive: Intergenerational archival temporalities in the digitization of the LOOT oral history tapes
Bibliographic record
Abstract
The genre of oral history tapes is a powerful form of mediated oral transmission of knowledge between geographically dispersed communities and generations. The act of listening to recordings of stories of survival and joy, forms affective bonds akin to kinship networks for listeners who identify with marginalized sexualities or genders (Chenier 2014). This talk will explore the case of the Lesbian Organization of Toronto (LOOT) oral history tapes as an example of queer intergenerational memory transmission. The LOOT Oral History Project interview tapes were recorded during 1988-1990 by sociologist Becki Ross and are extensively quoted in The House that Jill Built: A Lesbian Nation in Formation. Each of the interviews provides a unique perspective on LOOT’s four-year existence (1976-1980) and the politics of a particular Lesbian community located in Toronto (Ross 1995), that overlaps with poetic and publishing communities in the Spoken Web network. The stakes of intellectual property and privacy such as these tapes are perceived as high risk in digital environments, particularly when working with analogue materials that pre-date digitization and the Internet. While approaching the digitization of the LOOT tapes, we have taken into mind the historical, structural and harm that privacy law and intellectual property law now continue to perpetuate in the environment of digital archives. This talk will explore our approach through a framework of archival temporalities (Caswell 2021), as we work to navigate intergenerational contexts and reconcile them with our own contexts and identities as queer researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.024 | 0.031 |
| Scholarly communication | 0.023 | 0.021 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".