Bibliographic record
Abstract
Little research has been conducted to examine paraphilic sexual interests in nonclinical samples. The little that exists suggests that atypical sexual interests are more common in men than in women, but the reasons for this difference are unknown. In this study, we explored the prevalence of paraphilic interests in a nonclinical sample of men and women. We expected that men would report greater arousal (or less repulsion) toward various paraphilic acts than women. We also examined putative correlates of paraphilias in an attempt to explain the sex difference. In all, 305 men and 710 women completed an online survey assessing sexual experiences, sexual interests, as well as indicators of neurodevelopmental stress, sex drive, mating effort, impulsivity, masculinity/femininity, and socially desirable responding. As expected, significant sex differences were found, with men reporting significantly less repulsion (or more arousal) to the majority of paraphilic acts than women. Using mediation analysis, sex drive was the only correlate to significantly and fully mediate the sex difference in paraphilic interests. In other words, sex drive fully accounted for the sex difference in paraphilic interests. The implications of these findings for understanding the etiology of atypical sexual interests are discussed.
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.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".