The Role of Pornography in the “Rough Sex” Defence in Canada
Bibliographic record
Abstract
Drawing upon the authors’ earlier research studying the consent defence when it is used to suggest that the complainant agreed to “rough sex” involving violence, this paper develops an extended analysis of the complex role of pornography in these decisions. This paper focuses on a subset of “rough sex” cases, where pornography played a role in “scripting” the accused’s behaviour. Thematically, these cases included: those where the accused had a substantial history of consumption of violent pornography; cases in which the accused forced the complainant to view pornography as part of the assault; cases where the accused recorded the attack, engaging in the making of pornography themselves; and finally those cases where the airing of the “rough sex” defence in the courtroom, including cross-examination based on the re-playing of the recordings made by the accused, creates a “theatre of pornography.” The authors underline concerns about the growing role of pornography in sexual violence against women, and propose both legal and non-legal strategies in response.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".