Judicial approaches to combating ‘revenge porn’: a multi-jurisdictional perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article aims to provide a nuanced articulation of the challenges and complexities associated with the various judicial approaches countenanced across multiple jurisdictions to date toward combating the phenomenon colloquially referred to as ‘revenge porn’. The article’s central argument is that although the scope of several civil causes of action, such as breach of confidence, defamation, copyright and invasion of privacy, have been expanded in recent years to accommodate the evolving dynamics of revenge porn, a number of theoretical and practical issues nonetheless arise, which courts across various jurisdictions, including Australia, Canada, the UK, the USA, New Zealand and the Commonwealth Caribbean, have struggled to treat with. The article concludes by asserting that notwithstanding the important role played by civil causes of action in vindicating the rights of victims of revenge porn, legislative intervention remains invaluable.
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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 | 0.003 | 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) | 0.001 | 0.001 |
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 it