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Record W2796039028 · doi:10.20381/ruor-4788

Online Child Pornography Offenders and Risk Assessment: How Online Offenders Compare to Contact Offenders Using Common Risk Assessment Variables

2011· dissertation· en· W2796039028 on OpenAlexvenueno aff
Andrew McWhaw

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2011
Typedissertation
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsChild pornographyRisk assessmentPornographyPsychologyRecidivismSex offenderClinical psychologyThe InternetComputer securityComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The aim of this study was to compare online child pornography offenders and contact offenders along the predictive items of the Static-2002 actuarial risk assessment tool, as well as, several other items and scales predictive of recidivism. In addition, the study wished to determine if the Static-2002 was a well-equipped to assess online offenders. 120 subjects were assessed in this study, 53 online child pornography offenders, 53 child molesters, and 7 offenders who committed both a contact and online offense. The research identified a number of similarities between the two groups of offenders, including a finding that the two groups did not significantly differ in age. The most pronounced differences were found on the several measures of criminality used in the study where contact offenders scored significantly higher. The Static-2002 was found to not be well suited for use with online offenders as the tool had difficulty assessing their sexual deviancy.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.253
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2011
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicSexuality, Behavior, and TechnologyFrench-language works237,207