A Study of the Psychosexual Characteristics of Sex Killers: Can we Identify them Before it is Too Late?
Bibliographic record
Abstract
Thirty-three sex killers were compared to 80 sexual aggressives, 23 sadists, and 611 general sex offenders on sexual history and preferences, substance abuse crime, violence, mental illness, personality, neurological and endocrine abnormalities. Compared to other groups, sex killers started their criminal careers earlier, more often had been to reform school, were members of criminal gangs, set fires, and were cruel to animals. They tended so show more sadism, fetishism, and voyeurism. They more often collected pornography, but they did not use it in their offenses. They more often abused drugs and some suffered from drug induced psychoses. Their most common diagnosis was antisocial personality disorder, but only 15.2% met criteria for psychopathy. Sex killers showed most signs of neuropsychological impairment, grades failure, and learning disabilities. Results suggest that greater emphasis be placed on studying adolescent sex offenders and conduct disordered children which may help identify potential sex killers.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".