Schoolgirls and Soccer Moms: A Content Analysis of Free “Teen” and “MILF” Online Pornography
Bibliographic record
Abstract
Viewing free online pornographic videos has increasingly become a common behavior among young people, although little is known about the content of these videos. The current study analyzed the content of two popular female-age-based types of free, online pornography (teen and MILF) and examined nuances in the portrayal of gender and access to power in relation to the age of the female actor. A total of 100 videos were selected from 10 popular Web sites, and their content was coded using independent raters. Vaginal intercourse and fellatio were the most frequently depicted sexual acts. The use of sex toys, paraphilias, cuddling, and condom use were rare, as were depictions of coercion. Control of the pace and direction of sexual activity was typically shared by the male and female actors. Moreover, there were no gender differences in initiation of sexual activity, use of persuasion, portrayals of sexual experience, or in professional status. However, female actors in MILF videos were portrayed as more agentic and were more likely to initiate sexual activity, control the pace of sexual activity, and have a higher professional status. Implications regarding the role of pornography in generating or reinforcing sexual norms or scripts are discussed.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".