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Pornography and Sexual Aggression: Are There Reliable Effects and Can We Understand Them?

2000· article· en· W1767718732 on OpenAlex

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

VenueAnnual Review of Sex Research · 2000
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPornographyAggressionPsychologyPerspective (graphical)Social psychologyDevelopmental psychologyComputer sciencePsychoanalysis

Abstract

fetched live from OpenAlex

In response to some recent critiques, we (a) analyze the arguments and data presented in those commentaries, (b) integrate the findings of several metaanalytic summaries of experimental and naturalistic research, and (c) conduct statistical analyses on a large representative sample. All three steps support the existence of reliable associations between frequent pornography use and sexually aggressive behaviors, particularly for violent pornography and/or for men at high risk for sexual aggression. We suggest that the way relatively aggressive men interpret and react to the same pornography may differ from that of nonaggressive men, a perspective that helps integrate the current analyses with studies comparing rapists and nonrapists as well as with cross-cultural research.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.426
Teacher spread0.339 · 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