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Record W4221024663 · doi:10.1177/10790632211070797

“It was in Control of Me”: Notions of Addiction and Online Child Sexual Exploitation Material Offending

2022· article· en· W4221024663 on OpenAlexfundno aff
Jonah Rimer, Karen Holt

Bibliographic record

VenueSexual Abuse · 2022
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCommonwealth Scholarship CommissionRoyal Anthropological Institute
KeywordsAddictionPornographyPsychologyNarrativeChild pornographyQualitative researchIntervention (counseling)PrisonFocus groupParticipant observationSocial psychologyDevelopmental psychologyCriminologyThe InternetSociologyPsychiatryPsychoanalysisSocial science

Abstract

fetched live from OpenAlex

This paper focuses on notions of "addiction" among users of online child sexual exploitation material (CSEM) through a comparative analysis of two qualitative studies. The first is a 17-month anthropological ethnography (participant observation, interviews, and focus groups) in UK group programs for CSEM users, and the second is based on interviews with individuals in sexual offense treatment units of a US prison. We thematically analyze the narratives of 103 CSEM users at different timepoints and settings from pre-trial to incarceration. Those citing "addiction" focused on three areas. First was pornography progression. Second were perceived indicators of "addiction" and alignment/analogy to other addictions, including ideas about losing control; ignoring detrimental consequences and continuing; physiological signs similar to withdrawal; likening to substances; and progression from "softer" to "harder" material. Third, less common was rejecting the "addiction" label, citing choice and responsibility. We situate these results within debates and literature regarding pornography and Internet "addiction"; implications of the label; societal conceptions of sexual offending; harms of CSEM; and treatment/prevention considerations. Lastly, highlighting the merit of interdisciplinary comparative qualitative analysis, we demonstrate similarities in narratives despite differences in location, timeframe, setting, conviction status, intervention programming, and research methods.

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 categoriesInsufficient 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 score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.035
GPT teacher head0.318
Teacher spread0.283 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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