How the popular media rushes to judgment about pornography and relationships while research lags behind
Bibliographic record
Abstract
Pornography has been a major source of public concern for decades. In recent years, apprehension about the deleterious impact of pornography on romantic and marital relationships has joined a list of previously asserted harms, including claimed associations of pornography with communism, organized crime, aggression against women, and sex addiction. The current research systematically sampled public discourse in the media concerning the impact of pornography on the couple relationship and compared media assertions and conclusions with available evidence of academic research in this area. Magazine features, newspaper articles, and Internet postings mentioning the impact of pornography on heterosexual couples were systematically sampled and analyzed with Thematic Analysis (Braun & Clarke, 2006). Five prominent themes emerged in media discussions of the impact of pornography on relationships: (1) pornography addiction; (2) pornography is good for sexual relationships; (3) pornography use is a form of adultery; (4) partner's pornography use makes one feel inadequate; and (5) pornography use changes expectations about sexual behaviour. Academic research was then reviewed that addressed these identified themes. Two of five identified popular media themes were in accord with the academic literature. The extent to which popular media and academic research are having the same discussions and reaching the same, or different, conclusions was explored, and we discuss implications for future 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.
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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".