Perspectives on “Pornography”: Exploring sexually explicit Internet movies' influences on Canadian young adults' holistic sexual health
Bibliographic record
Abstract
Despite the vast number of Canadian young adults who consume sexually explicit Internet movies (SEIM), the potential influences SEIM consumption has on overall sexual health remains understudied. This study aimed to develop insight into what Canadian young adults perceive to be the influences of consuming SEIM on six components of sexual health: Sexual Knowledge, Sexual Self-Perception, Sexual Activity, Sexual Partner Relations, Perceptions of Sexuality, and Overall Wellbeing. Employing an exploratory qualitative approach, data were collected through semi-structured interviews with 12 urban, heterosexual young adults (ages 19–29), who self-identified as having consumed SEIM for a period of at least one year. All interviews were audio-taped with permission, transcribed verbatim and analyzed using principles of constructivist grounded theory. Young adults described a wide range of influences that encompassed topics beyond physical reactions, to include experiences with overall sexuality and sexual self. These influences were perceived to result in both health benefits and health challenges. The disparities between this study's findings and other empirical SEIM studies suggest that conceptualizing SEIM consumption using person-centred, holistic perspectives may help researchers more effectively capture the multitude of diverse ways SEIM can influence Canadians' sexual health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".