The Development of Sexual Aggression through the Life Span
Bibliographic record
Abstract
Abstract: There is a strong belief in the field that sexual aggression persists unabated into old age. If libido is one of the important determinants of sexual aggression, as has been theorized, and if libido decreases with aging, then it follows that sexual aggression should show similar aging effects. The present study examines the effects of age on sexual arousal and sexual recidivism in sex offenders. In the first study, 1431 sex offenders' erectile responses were measured using volumetric phallometry during presentations of visual and auditory depictions of prepubescent, pubescent, and adult males and females. The maximum degree of arousal was plotted over the age of the offender at the time of the test. Age was a powerful determinant of sexual arousal and a line‐of‐best‐fit indicated that arousal decreased as a reciprocal of the age‐at‐test. In the second study, 468 sex offenders released into the community were followed for an average period of over five years. The effects of age‐at‐release were examined using Kaplan‐Meier survival curves plotted for subjects in different age‐at‐release cohorts. Results indicated that offenders released at an older age were less likely to recommit sexual offenses and that sexual recidivism decreased as a linear function of age‐at‐release. Age‐related decreases were confirmed while controlling for other risk factors using Cox regression analysis. The implications of reductions in sexual aggression with age are discussed in relation to our understanding of the etiology of sexual aggression and our use of actuarial risk assessments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".