Media representations of sexuality in an era of pornification
Bibliographic record
Abstract
As a result of digitalization, sexually explicit media content is now produced and distributed in much greater quantity and variety in private, public, and commercial contexts. Increased normalization of pornography, greater sexualization of media content, and the public debates associated with these developments are indicative of a trend towards pornification. At the same time, interdisciplinary pornography research has been evolving in recent decades, with communication science making important contributions to this area. However, in contrast to gaming research, pornography research is institutionalized to a much lesser extent. There is a “Game Studies” division within the International Communication Association (ICA), but no equivalent “Porn Studies” division. And to our knowledge, this Special Issue is the first Special Issue of an ICA-associated journal dedicated to pornography. The five empirical articles in this issue deal with different aspects of pornification, namely press coverage of OnlyFans.com, non-commercial production and distribution of pornographic images among gay, bisexual, and queer men, different preferences for pornographic content when viewed alone or in a partnership, computer-generated rough sex pornography, and an intervention to promote pornography literacy. This Special Issue aims to encourage communication science to devote more attention to sexually explicit communication and to help close existing gaps in research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".