Sexual Assault Law, Credibility, and 'Ideal Victims': Consent, Resistance, and Victim Blaming
Bibliographic record
Abstract
The archetype of the sexual assault still functions to disqualify many complainants' accounts of their sexual assault experiences. To this extent, the victim myth continues to undermine the credibility of those women who are seen to deviate too far from stereotypical notions of authentic victims and too far from what are assumed to be predictable and reasonable responses. Credibility assessments, which are absolutely pivotal in sexual assault trials, remain deeply influenced by myths and stereotypes surrounding ideal, real, or genuine victims of sexual assault. Despite progressive Canadian sexual assault law reform with regard to consent, the onus of proof and credibility of consent in practice remains with the and plays out in often harmful and discriminatory ways. The persistence of the idea that real victims of sexual assault resist remains inextricably bound up with the myth that ideal or real victims can prove their status and establish the credibility of their rape claims by demonstrating that they resisted the assault and that their resistance took a socially expected form, by preferably vigorous physical fighting back. In this article, I assess some of the key problems that remain deeply in need of redress with regard to the law's response to sexual assault, analyzing the tenacity of distorted legal images of ideal or real sexual assault victims, the tendency still to blame sexual assault victims and disappear perpetrators, and the persistence of a kind of psychological illiteracy in law about the nature, complexities, and range of ways in which women cope with the violation and trauma of sexual assaults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.054 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".