Singing In Harmony: Conceptualizing Queer Feminist Musicking
Bibliographic record
Abstract
This thesis explores queer-feminist musicking within In Harmony: A Women's Choir, based in Ottawa, Ontario.In Harmony: A Women's Choir, founded in 1991 is dedicated to performing the richness and diversity of women's experience.Originally a lesbian chorus, the choir has expanded its membership to include trans women, genderqueer and nonbinary people.By situating In Harmony within the broader histories of queer and feminist choral movements, this study examines the cultural shifts and evolving dynamics within these communities, particularly how they inform the choir's value system and ethos.In my research I employed queer and feminist methodologies that centred relationality, reflexivity and care ethics.I also participated in the choir as a member during the 2023-2024 season and draw on my experiences and observations as a member.Drawing on José Esteban Muñoz's concept of queer utopia (2009), I conceptualize how queer-feminist musicking shapes the choir's inclusive practices.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.068 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".