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Record W2085839724 · doi:10.1080/009262302760328253

Age as a Differential Characteristic of Rapists, Pedophiles, and Sexual Sadists

2002· article· en· W2085839724 on OpenAlexaff
Robert Dickey, David Nussbaum, Kelley Chevolleau, Hannah Davidson

Bibliographic record

VenueJournal of Sex & Marital Therapy · 2002
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCentre for Addiction and Mental HealthYork UniversityUniversity of Toronto
Fundersnot available
KeywordsPedophiliaPsychologySadistic personality disorderSex offenseRecidivismPoison controlInjury preventionCategorizationSexual abuseClinical psychologySocial psychologyMedical emergencyPersonalityPersonality disordersMedicine

Abstract

fetched live from OpenAlex

In this study, we investigated the role of age in three categories of 168 sex offenders, including 53 rapists, 62 pedophiles, and 53 sadists. On the basis of the match between requisites of completing each type of sexual offense, we hypothesized that rapists would be less represented in the older age group, whereas pedophilic and sexually sadistic offenders would show a more muted decline with age. This hypothesis was supported by the data, clearly a showing smaller number of rapists in the over 40 group relative to the number of pedophiles and sadists (p = 0.0009.) Further examination of the files eliminated the alternate explanation ascribing this pattern to lack of opportunity in older rapists because of incarceration. These results suggest that age over 40 may mitigate incidence of recidivism in rapists, but not in pedophiles or sexual sadists. Approximately one third of the sexual sadists had committed either first- or second-degree murder, whereas none of the nonsadistic rapists or pedophiles had these crimes on their records. The data further justify categorization of sex offenders into nonsadistic rapist, sadistic rapist, and pedophilic offenders in future research to enhance precision in delineating demographic characteristics and putative causal explanations for sexual offending.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.036
GPT teacher head0.295
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations55
Published2002
Admission routes1
Has abstractyes

Explore more

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