Predictors of men's genital self-image across sexual orientation and geographic region
Bibliographic record
Abstract
Factors that contribute to men's genital self-image are not well known, despite the documented psychological importance of body image more broadly. The current study used a simultaneous multiple regression to examine the relationship(s) between genital self-image, body image, pornography use, circumcision status, age, and social appearance anxiety among men from different geographic locations, and of differing sexual orientations (N=674). Participants were recruited from Canada (n=285), the United States (n=214), and Western Europe (n=121) through online recruitment methods. A total of 372 gay men/other men who have sex with men (MSM) and 302 heterosexual men were included in the present analyses. Men's genital self-image was significantly predicted by self-perceived body image and social appearance anxiety. Further univariate and multivariate analyses discussed include age, sexual orientation, country of origin, solo porn use, and circumcision status. Implications of the continued importance of parsing the differences between genital self-image and related variables for understanding sexual functioning and overall self-esteem are discussed.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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 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".