Ignoring Implementation: Defects in Canada’s “Rape Shield” Policy Cycle
Bibliographic record
Abstract
Abstract This article employs a “policy cycle” framework to explore Bill C-51, legislation which contains Canada’s latest amendments to the “rape shield.” Through an in-depth evaluation of earlier rape shield reforms, as well as a content analysis of the legislative proceedings of Bill C-51, this paper reveals that, while the impetus for introducing rape shield legislation is to protect the equality and privacy rights of sexual assault complainants, the legislative process of these “policy cycles” focuses disproportionately on remedying due process concerns and less on the problems that arise in judicial implementation of the provisions. We situate this finding within the larger trend towards the “judicialization of politics,” and trace some of the institutional and structural obstacles that impede Parliamentarians from more effectively legislating to improve sexual assault trials for complainants.
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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 | 0.051 | 0.127 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".