A map of desire: multidimensional scaling of men's sexual interest in male and female children and adults
Bibliographic record
Abstract
BACKGROUND: Men sexually interested in children of a specific combination of maturity and sex tend to show some lesser interest in other categories of persons. Patterns of men's sexual interest across erotic targets' categories of maturity and sex have both clinical and basic scientific implications. METHOD: We examined the structure of men's sexual interest in adult, pubescent, and prepubescent males and females using multidimensional scaling (MDS) across four datasets, using three large samples and three indicators of sexual interest: phallometric response to erotic stimuli, sexual offense history, and self-reported sexual attraction. The samples were highly enriched for men sexually interested in children and men accused of sexual offenses. RESULTS: Results supported a two-dimensional MDS solution, with one dimension representing erotic targets' biological sex and the other dimension representing their sexual maturity. The dimension of sexual maturity placed adults and prepubescent children on opposite ends, and pubescent children intermediate. Differences between men's sexual interest in adults and prepubescent children of the same sex were similar in magnitude to the differences between their sexual interest in adult men and women. Sexual interest in adult men was no more associated with sexual interest in boys than sexual interest in adult women was associated with sexual interest in girls. CONCLUSIONS: Erotic targets' sexual maturity and biological sex play important roles in men's preferences, which are predictive of sexual offending. The magnitude of men's preferences for prepubescent children v. adults of their preferred sex is large.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".