The effects of sex drive and paraphilic interests on paraphilic behaviours in a nonclinical sample of men and women
Bibliographic record
Abstract
Research on samples of men and women from the general population suggests that paraphilic interests and behaviours are more common in men than in women, but the reasons for this sex difference are unclear. In addition, there is little research on how paraphilic interests lead to engagement in paraphilic behaviours. In this study, we assessed the frequency of engagement in a broad range of paraphilic behaviours in a nonclinical sample of men and women. We expected that men would report engaging in paraphilic behaviours more frequently than women. We also examined whether sex drive explained the sex difference in the frequency of engagement in paraphilic behaviours, as well as whether the relationship between paraphilic interests and frequency of engagement in paraphilic behaviours was stronger at high levels of sex drive. A sample of 305 men and 710 women completed an online survey assessing paraphilic interests and behaviours as well as three measures of sex drive. As expected, sex differences were found, with men reporting more frequent engagement in most paraphilic behaviours. After controlling for socially desirable responding, sex drive fully accounted for the male-biased sex differences. One measure of sex drive–the Sexual Behaviour and Desire Questionnaire–moderated the relationship between paraphilic interests and frequency of engagement in paraphilic behaviours, such that paraphilic interests were most strongly associated with paraphilic behaviours at high levels of sex drive. Taken together, these findings provide further support for the importance of sex drive in understanding the paraphilias.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".