Testing the Confluence Model of the Association between Pornography Use and Sexual Aggression: A Longitudinal Assessment in Two Independent Adolescent Samples
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".