Celebrity ‘rape-rape’: An analysis of feminist and media definitions of sexual violence
Bibliographic record
Abstract
In 2009 a US-based television programme, The View , discussed the arrest of film director Roman Polanski. Polanski was wanted for six outstanding charges related to the rape of Samantha Gailey in 1977. During this episode of the The View , Whoopi Goldberg made a controversial statement that Polanksi was not guilty of ‘rape-rape’. This statement along with the long history of Polanski’s avoidance of incarceration, illustrates the ongoing challenges for feminists to confront the trivialisation of sexual coercion and violence. Goldberg’s comments initiated an enthusiastic response on online forums and reinvigorated debates around definitions of rape. In this paper, I analyse online discussions on a feminist blog using discourse analysis (Parker, 2014) and the importance of considering the interrelated concepts of consent/non-consent, pleasure/distress and power in understanding the complexity and diversity of experiences of sexual violence.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".