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Record W1584517025 · doi:10.1002/cbm.809

Child pornography offenders detected by surveillance of the Internet and by other methods

2011· article· en· W1584517025 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCriminal Behaviour and Mental Health · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsChild pornographyPornographyPsychiatryThe InternetSexual abuseReferralPossession (linguistics)PsychologyClinical psychologyChild abuseChild sexual abuseMedicineSuicide preventionPoison controlCriminologyMedical emergencyFamily medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Availability of child pornography on the Internet has created new opportunities for offending. It has been noted that many people charged with offences relating to this had not previously been identified as sexual offenders against children. AIM: Our aim was to compare the characteristics of people charged with child pornography offences as a result of police monitoring of the Internet with those detected by other means. We hypothesised that those apprehended via the Internet would be more likely to be older and less likely to have severe psychiatric disorder or to have been previously charged with a sexual offence involving contact with a child than those identified by other means. METHODS: Data were extracted from the findings of clinical examinations by the authors either in the course of preparing reports for court, or in the course of providing treatment. RESULTS: There were 52 men detected by police Internet surveillance and 53 men detected by other means, the latter including 16 men who had not been charged with an offence at the time of referral. Those detected via the Internet were more likely to be in possession of very large quantities of child pornography. Those detected by other means were more likely to have major psychiatric and substance abuse disorders and to report childhood sexual abuse. A subgroup analysis of the 89 people who were facing charges at the time of the assessment found that the only significant differences were in the amount of material and the history of sexual abuse. CONCLUSIONS: The men recruited to this study, conducted over a period of nearly 10 years, reflect the changing nature of the technology used to commit this type of offence in that time. The characteristics of the subjects did not confirm the stereotype of an Internet child pornography offender who was high functioning and otherwise well adjusted and carried a low risk of other types of offences.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

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

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 head0.047
GPT teacher head0.356
Teacher spread0.309 · 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