Sexual Assault Law Reform in NSW: Issues of Consent and Objective Fault
Bibliographic record
Abstract
The purpose of this paper is to assess the recent reforms to the Crimes Act 1900 (NSW) in relation to sexual assault. Two of the main reasons for reform were to increase the reporting of sexual assault and to increase conviction rates for sexual assault. It is not possible to assess the impact of the reforms on these two factors, as such the paper focuses on the legal changes and their predictive impact upon the proof of liability for sexual assault offences. Specifically, the paper assesses the statutory definition of consent, the expansion of the circumstances whereby consent would be negated or vitiated, and the adoption of an objective fault element. As part of this assessment, the paper also considers, where relevant, the current law on sexual assault in other Australian jurisdictions, as well the UK and Canada, from which NSW has ‘borrowed’. We add to this context a consideration of the law in New Zealand.
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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 | 0.000 | 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".