Affirmative Sexual Consent in Canadian Law, Jurisprudence, and Legal Theory
Bibliographic record
Abstract
This article examines the development of affirmative sexual consent in Canadian jurisprudence and legal theory and its adoption in Canadian law. Affirmative sexual consent requirements were explicitly proposed in Canadian legal literature in 1986, codified in the 1992 Criminal Code amendments, and recognized as an essential element of the common law and statutory definitions of sexual consent by the Supreme Court of Canada in a series of cases decided since 1994. Although sexual violence and non-enforcement of sexual assault laws are worldwide phenomena, the international scholarly literature reflects limited awareness of these developments in Canadian law. This article remedies that gap in the literature. The Canadian experience with the definition of sexual consent as communicated “voluntary agreement” demonstrates the value of this conceptualization of consent; the definition provides a well-defined set of nondiscretionary reference points for legal analysis of the facts in sexual assault offenses. The effect is to facilitate effective enforcement of the sexual assault laws and affirm the right to sexual autonomy, sexual self-determination, and equality, consistent with fundamental principles of individual human rights. For all these reasons, familiarity with the Canadian experience may be useful to those engaged with the reform of rape and sexual assault laws in other jurisdictions.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.025 | 0.074 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".