Pornography as a Source of Education About Sex and Sexuality Among a Sample of 15–29 Year Old Australians
Bibliographic record
Abstract
Most young Australians are exposed to online pornography by the age of 16. Little is known of the impact of this on their sexual development and health. In this study we explored how young people use pornography as a source of education and information about sex, and the impact of this on their sexual development and health. 1029 young Australians (15–29 years), recruited via Facebook, completed an online survey in which 10 questions related to pornography. Those who had ever viewed pornography (n=856) were asked the open-ended question ‘How has pornography influenced your life?’. Qualitative responses (n=734) were thematically analysed. Results showed many participants saw pornography as a form of sexual education, by providing a first opportunity to “see genitals” and the “mechanics of sex”. Others used pornography to find “new positions” and “techniques” to practice in real life. Some found this education “helpful” and “liberating”; others noted it created problems in sexual expectations. Exposure to pornography both consciously and subconsciously influenced the development of sexual identities and preferences for many respondents. Viewing pornography had an impact on expectations of sex, pleasure, identity and on body image. For some this occurred as a result of a sexual partner’s expectations; however, for many this was a result of their own exposure. Many had a complex relationship with pornography, simultaneously recognising its utility for learning about sex and its negative impacts on their sexuality and wellbeing. The data illustrate the various ways in which pornography acts as a source of sex education for young people, particularly in the context of inadequate formal sex education.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".