Feminist legal geographies of intimate-image sexual abuse: Using copyright logic to combat the unauthorized distribution of celebrity intimate images in cyberspaces
Bibliographic record
Abstract
Women’s rights are often curtailed online due to the pervasive internet atmosphere of cybermisogyny. Extreme examples include ‘image-based sexual abuse’, a term which encompasses the non-consensual creation and/or distribution of private sexual images. The harms attached to this phenomenon are well documented. In this paper, we explore how copyright logic, despite its male-centric and property oriented worldview, presents one legal solution to this problem. We assert that Digital Millennium Copyright Act Takedown Notices, a copyright mechanism that notifies websites they are hosting infringing content and requires the prompt removal of the content, represents a novel legal mechanism to force websites to remove image-based sexual abuse from women’s online spaces. By using critical discourse analysis to review how Digital Millennium Copyright Act Takedown Notices attempt to provide solutions to the socio-spatial problem of image-based sexual abuse, we argue that copyright can subvert its current leanings to return to its original purpose: supporting creativity. Supporting creativity also helps to protect against the reproduction of gendered harms, from the real world to virtual spaces. This theorization represents not just legal geography but a feminist legal geography, in that it recognizes the internet should be a safe and legal space for women. In endorsing a pragmatic legal solution for women to regulate the sexually violent and nonconsensual distribution of their intimate images online, copyright is one mechanism that affirms women’s right to cyberspaces.
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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".