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Record W4241831832 · doi:10.31234/osf.io/xmk7h

Testing the Confluence Model of the Association between Pornography Use and Sexual Aggression: A Longitudinal Assessment in Two Independent Adolescent Samples

2019· preprint· en· W4241831832 on OpenAlexaff
Taylor Kohut, Ivan Landripet, Aleksandar Štulhofer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsPornographyAggressionPsychologyHuman sexualityOddsMasculinityAssociation (psychology)Developmental psychologySocial psychologyPoison controlClinical psychologyMedicineLogistic regressionGender studiesSociologyMedical emergency

Abstract

fetched live from OpenAlex

According to Confluence Model theorizing, pornography use contributes to sexual violence, but only among men who are predisposed to sexual aggression. Support for this assertion is limited to cross-sectional research, which cannot speak to the temporal ordering of assumed causes and consequences. To address this issue we employed generalized linear mixed modeling to determine if hostile masculinity, impersonal sexuality, and pornography, and their interactions, predicted change in the odds of subsequently reported sexual aggression in two independent panel samples of male Croatian adolescents. While we observed the link between hostile masculinity and self-reported sexual aggression in both panels, we found no evidence that impersonal sexuality and pornography use increased the odds of subsequently reporting sexual aggression—regardless of participants’ predisposed risk. This study’s findings are difficult to reconcile with view that pornography use plays a causal role in male sexual violence.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.181
GPT teacher head0.403
Teacher spread0.221 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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