The Use of Arguments about Myths and Stereotypes to Appeal Sexual Assault Convictions in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Canadian defence counsel have recently begun appealing sexual assault convictions by arguing that a trial judge applied myths and stereotypes (M&S) against the accused. This phenomenon is surprising because this country’s focus on M&S in sexual assault law has almost exclusively concerned improper assumptions that operate against the complainant and the Crown and risk producing perverse acquittals. This thesis reviews this new defence strategy with reference to three decades of appellate case law and scholarship. It advances definitions of M&S as well as principles for understanding the evidentiary effects of their recognition as such, and it categorizes various defence attempts to invoke M&S in conviction appeals, concluding that some have more merit than others. Emerging from this analysis is a more consistent, coherent role for the M&S doctrine in sexual assault law – one which should assist the Canadian bench, bar and academy in distinguishing legitimate M&S arguments from strained ones.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 it