Through thick and thin: Storying queer women’s experiences of idealised body images and expected body management practices
Bibliographic record
Abstract
In this study we examine how discourses of obesity and eating disorders reinforce cissexist and heteronormative body standards. Sixteen queer women in Canada produced autobiographical micro-documentaries over the course of two workshops. We identified three major themes across these films: bodily control, bodies as sites of metamorphosis, and celebration of bodies. Such films can be memorable, cultivate empathy, disrupt misunderstanding of queer bodies, and inform medical practice. Our analysis suggests that research and policy on ‘disordered’ bodies must better account for how people negotiate discourses around body shape and size, how shaming is internalised, how regulation can function as resistance, and how variant bodies can be embraced, desired, and celebrated. Community-grounded, arts-based research points to new ways of gathering and producing knowledge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".