Picturing the dance: intersections of gender, sexuality, and age in older women queer square dancers
Bibliographic record
Abstract
A dearth of research has focused on the diverse experiences of aging sexual minority populations and, in particular, older sexual minority women. Studies that have disaggregated the population of lesbian, gay, bisexual, transgender, questioning, queer, intersex and two-spirit (LGBTQIS+) older adults reveal that due to minority stress and a lifetime of disadvantage. Lesbians experience higher rates of chronic health conditions and mental health problems (including loneliness) than heterosexual women and greater financial inequalities compared to gay men or heterosexual women. Despite this, limited inquiry has explored the everyday lives of older queer women and fewer still draws upon women's commentary on their own lived experiences or centers older women as authoritative agents and experts on their own lives. In response to this knowledge deficit, this research traverses the aging experiences of female-identified members of a gay square dance (GSD) club in Toronto, Canada. We apply queer theory to explicate the unique ways in which a GSD club queers the aging process for 14 older women dancers. Findings of the inquiry highlight the ways in which these dancers confront and reject heteronormativity, while illuminating pathways to successful aging for older sexual diverse women. The older women dancers in this study perform gender in ways that challenged heteronormativity and gender binaries, enhanced belongingness and acceptance, embodied joy, and fostered wellness. These concepts have been identified as critical factors in successful aging and highlight what queering aging might look like for this resilient population who have overcome a lifetime of disadvantage.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".