Patterns of Genital and Subjective Sexual Arousal in Cisgender Asexual Men
Bibliographic record
Abstract
Human asexuality has been defined as a lack of sexual attraction to others, although its nature is not well understood. Asexual men’s genital and subjective sexual arousal patterns were compared to sexual men’s to better understand asexual men’s sexual response patterns. Using a penile plethysmograph to measure genital arousal, 20 asexual, 27 heterosexual, and 22 gay cisgender men (M age = 28.28, SD = 9.41) viewed erotic films depicting sexual activity or masturbation, and a subsample engaged in sexual fantasy of their choosing. Questionnaires assessing sexual function and behavior were also completed. Asexual men scored lower on sexual desire and orgasmic function, higher on sexual aversion, and did not differ on overall sexual satisfaction. Compared with gay and heterosexual men, asexual men demonstrated lower genital and subjective sexual arousal to the erotic films but displayed similar sexual arousal when engaging in sexual fantasy. Asexual men’s lower levels of sexual excitation rather than their higher levels of sexual inhibition were associated with lower responses to the erotic films. These findings suggest asexual men have preferred sexual stimuli that differ from sexual men and have a similar capacity for sexual arousal as sexual men. Collectively these findings add to a growing literature aiming to understand the nature of asexuality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".