Forbidden Fantasies: A Qualitative Exploration of the Content of Sexual Fantasies of Adults Reporting Sexual Attraction to Minors
Bibliographic record
Abstract
While a few studies have investigated the sexual fantasies of adults reporting sexual attraction to minor, none, to the best of our knowledge, have focused on the specific types of content of these fantasies. In this qualitative study, we conducted content and thematic analyses of the sexual fantasies reported by an international sample of 112 adults reporting sexual attraction to minors recruited online. Seven themes were found: Minor-focused fantasies, Other paraphilic fantasies, Unrealistic fantasies, Incestuous fantasies, Adult-focused fantasies, Promiscuous fantasies, and Group sex fantasies. The sexual fantasies of adults reporting sexual attraction to minors exhibited diversity both in terms of the individuals involved and in the range of sexual practices imagined. However, much of the sexual fantasy content shared by participants was predominantly of a paraphilic nature. Approximately one-third of the fantasies involved minor as sexual partners, romantic partners, or featured participants imagining themselves as minors. Additionally, nearly half of the disclosed sexual fantasies referenced other paraphilic sexual interests, such as violence, fetishism, exhibitionism/voyeurism, body fluids, and zoophilia. Results of our research highlight the possibility of co-occurring paraphilic interests in adults reporting sexual attraction to minors.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".