Tackling bisexual erasure: An explorative comparison of bisexual, gay and straight cisgender men’s body image
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous body image research often grouped both gay and bisexual men into a single category: sexual minoritised men, limiting our understanding of how sexual identity influences body image. However, there is strong reason to believe that bisexual and gay men experience distinct body image concerns. Here, we explored motivations to alter one’s leanness and muscularity, as well as (dis)satisfaction with body fat, muscularity, height and penis size, and functionality appreciation across gay, bisexual, and straight cisgender men. We sampled 378 white participants aged 18 to 85 (nbisexual = 125, ngay = 128, nstraight = 125). We found that bisexual men were significantly less motivated to be lean and showed lower muscularity dissatisfaction relative to gay men but showed comparable levels to straight men. Our findings demonstrate that despite research perceiving the body image of bisexual and gay men as homogenous, they experience differences in their body image concerning leanness and muscularity dissatisfaction. Future body image research should incorporate this understanding by not artificially grouping bisexual and gay cisgender men and instead acknowledging the potential uniqueness in their experiences.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it