The Rape of a Label Why it Would Be Wrong to Follow Canada in Having a Single Offence of Unlawful Sexual Assault
Bibliographic record
Abstract
With the enactment of the Sexual Offences Act 2003, the UK has just had its biggest shake-up of the existing law on sexual offences. Rape has been widened to include oral sex, a new offence of assault by penetration has been created, and what was indecent assault has been renamed sexual assault. Twenty-one years ago the Canadians did away altogether with the legal term of rape and created an all-encompassing offence of sexual assault. While the UK is experiencing an all-time low in securing convictions for rape, this article asks what can be done to reverse this. Could doing away with the label of rape make it easier to obtain a conviction in rape trials? Perhaps reversing the burden of proof, or tightening up the requirements for obtaining consent, or tackling the biggest new phenomenon in sexual offences, date rape, is the way forward. What we call something may not seem all that important, but this article aims to show that the social stigma attached to the word rape is as important as the sentence itself.
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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 | 0.001 |
| 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 | 0.000 |
| 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".