Attraction to Physical and Psychological Features of Children in Child-Attracted Persons
Bibliographic record
Abstract
In an online survey of 274 self-identified child-attracted persons (CAPs), we examined the attraction ratings given to sets of 9 physical and 12 psychological features of children, and asked CAPs to identify additional features that were not listed. We also examined the relationships between these attraction ratings and attraction to children dimensions (age mono-/polymorphism, exclusivity of attraction to children, and gender attraction), history of falling in love with a child, and detected sexual offending history. There was relatively little differentiation across physical features and psychological features; all averages were approximately 4 or higher on a 5-point scale. Attraction ratings were mostly weakly and inconsistently related to our other study variables. The exception was that CAPs who had fallen in love with a child rated 11 out of 12 psychological features as more attractive than CAPs who had not fallen in love with a child, with small to moderate effect sizes. These two groups did not differ in ratings for physical features. Our qualitative content analysis of participant-suggested features revealed six physical themes (inter alia, face and head, children's bodies) and five psychological themes (inter alia, personality, harmlessness) that were important to CAPs' attraction to children.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".