“Porn is blunt […] I had way more LGBTQ+ friendly education through porn”: The experiences of LGBTQ+ individuals with online pornography
Bibliographic record
Abstract
While public and academic discussions on pornography’s effects are often plagued by moralistic claims, research on the self-perceived preferences and effects of pornography has been growing in recent years. Yet, we still do not know enough about the role pornography plays in the lives of regular viewers, particularly LGBTQ+ individuals. In this study, we examine the perceptions and views of 87 regular pornography viewers who identified as non-heterosexual, non-cis-gendered, or both (these 87 were part of a larger sample of 302 regular pornography viewers). Our study joins a growing body of work that explores the views, experiences, and preferences of individuals who consume pornography. We found that pornography played a crucial role for LGBTQ+ individuals, helping them to form their gender and sexual identities, serving as a practical guide for the technical aspects of engaging in non-heterosexual sex, and normalizing non-heterosexual orientations, acts, and identities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".