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Record W2315718350 · doi:10.1177/1079063216637857

Do Sex Offenders Have Higher Levels of Testosterone? Results From a Meta-Analysis

2016· review· en· W2315718350 on OpenAlexaff
Jennifer S. Wong, Jason Gravel

Bibliographic record

VenueSexual Abuse · 2016
Typereview
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTestosterone (patch)AggressionPsychologyMeta-analysisInclusion and exclusion criteriaSex offenderParaphiliaClinical psychologyDemographyDevelopmental psychologyMedicineSexual behaviorInternal medicine

Abstract

fetched live from OpenAlex

The purpose of the current study is to review the available scientific evidence on the relationship between testosterone and sexual aggression. A systematic search for all primary studies comparing basal testosterone levels in sex offenders and non-sex offenders was undertaken across 20 electronic databases using an explicit search strategy and inclusion/exclusion criteria. A total of seven studies were identified and 11 effect sizes were computed; effects were pooled using both fixed and random effects meta-analysis models. Although individual study findings present a mix of results wherein sex offenders have higher or lower baseline levels of testosterone than non-sex offenders, pooled results indicate no overall difference between groups. Moderators of the analyses suggest possibly lower rates of testosterone in child molesters than controls; however, results are dependent on study weighting. Limitations, policy implications with respect to chemical castration laws, and future directions for research are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.736
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.355
GPT teacher head0.434
Teacher spread0.079 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2016
Admission routes1
Has abstractyes

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