Bibliographic record
Abstract
In this paper, I explore the complexities associated with sexual assault in Canadian law and society by analyzing significant or sensationalized sexual assault cases, including: the leading Supreme Court of Canada case R v Ewanchuk (1999) on sexual assault and implied consent; the murder trial of British Columbia serial killer Robert Picton (2003); and assaults occurring on the campus of York University (Toronto). The concept of Implied consent is central to the assumptions underpinning many rape myths that blame victims for the violent actions of perpetrators (e.g., a woman who is deemed to be dressed inappropriately is held to be responsible, in some way, for her own assault). I situate my arguments within feminist socio-legal studies and contend that rape myths unduly sanction discrimination against victims. Hegemonic masculinity, which is based on a mythical norm, emerges as problematic in (re)constructing sexual violence. Hegemonic femininity also engages in a process of “othering,” which locates specific women as more “rapable” than others. Moreover, these gendered constructions are heightened by and interconnected with race and class inequalities. The use of sexual assault litigation as a tool for justice is debatable, at best, given the issue of reasonable doubt in criminal law and the re-traumatization of victims. Both Canadian law and society can be implicated in the problems associated with the trying of sexual assault cases, problems which cannot be adequately addressed without a deeper, contextualized analysis of discrimination as well as further activism.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.065 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".