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Record W1975945847 · doi:10.1080/10538712.2013.781091

Sexual Abuse Images in Cyberspace: Expanding the Ecology of the Child

2013· review· en· W1975945847 on OpenAlex
Jennifer Martin, Ramona Alaggia

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

VenueJournal of Child Sexual Abuse · 2013
Typereview
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsCyberspaceSexual abuseChild sexual abuseChild abusePsychologyPoint (geometry)Sexual violencePoison controlThe InternetInternet privacyComputer securitySuicide preventionCriminologyMedicineComputer scienceMedical emergencyWorld Wide Web

Abstract

fetched live from OpenAlex

Cyberspace has added a new dimension to the ecology of children made the subjects of sexual abuse images distributed online. These images cannot be permanently removed and can continue to circulate in cyberspace forever. A review of the current literature suggests that helping professionals are not consistently aware of or do not probe possibilities of online sexual victimization in the investigation, assessment, and treatment of child sexual abuse. Nor is this issue adequately addressed in their education and training. There are gaps in the literature regarding how to identify and provide treatment for these children. New assessment and treatment targets are needed to enhance existing practice approaches. A contemporary ecological model that incorporates an explicit consideration of the cybersystem is provided as a starting point for practitioners to be aware of the possibility that images of child sexual abuse were recorded and distributed online.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.341
Teacher spread0.305 · 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