Overlap in erotic age preferences: Support for the chronophilia theory in a community self-report sample of males
Bibliographic record
Abstract
Seto (2017) proposes sexual orientation not only varies as a function of gender, but also as a function of age. Few studies have examined the conceptualization of sexual age orientation. The current study evaluates the polymorphism of sexual interest in children (i.e., simultaneous attraction to multiple age categories), the exclusivity of sexual interest (i.e., attraction to children only or children and adults), and gender preference (i.e., preference for males or females) in the general population. Data were obtained through adult males (N = 170) using online self-reports (overlapping sample from Mundy & Cioe, 2019). Findings revealed that most individuals reporting sexual attraction to multiple age categories had a higher degree of preference for one age group over others. When looking at sexual interest in children among teleiophilic individuals, the concordance indices were higher between adjacent age groups compared to distant age groups. Specifically, among individuals who reported teleiophilic sexual interest, 36% were also reporting hebephilic sexual interest (adjacent category), while 17.7% reported pedophilic sexual interest (non-adjacent category). Finally, there was a significant positive correlation between pedophilic interest and hebephilic interest (τb = .602, p < .001). Together, results provide support for the chronophilia theory. Concordance indices in future studies may inform differences between exclusive and nonexclusive interest in children and aid the development of informed risk assessment tools and destigmatized prevention programs.
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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 | 0.006 |
| 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) | 0.004 | 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".