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Record W4220947831 · doi:10.4324/9781003092032-4

Locating lesbians, finding “gay women”, writing queer histories

2022· book-chapter· en· W4220947831 on OpenAlexaboutno aff
Valerie J. Korinek

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQueerGender studiesPsychologySociology

Abstract

fetched live from OpenAlex

This chapter explores the challenges of oral history work within the lesbian/queer communities of western Canada. It grapples with questions of consciousness and identity formation and provides valuable perspectives on the methodological and theoretical challenges sexualities historians face when historicising women who loved, lived, or had sex with women. Drawing upon extensive research and oral history collections within prairie gay and lesbian communities, the chapter provides an overview of how the many layers of identity politics, varying “labels”, notions of visibility, and issues of framing histories that honour those who spoke, and those who chose to remain silent, were negotiated throughout the research project and, ultimately, in publications derived from this work. Ultimately, the talkers triumph. Their histories predominate, their voices are strong, and their stories resonate. This chapter is an abridged version of an essay that originally appeared in Beyond Women’s Words: Feminisms and the Practice of Oral Histories in the 21st Century (Routledge, 2018).

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.429
Threshold uncertainty score0.854

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0220.023
Scholarly communication0.0120.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.062
GPT teacher head0.239
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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