The Age of Innocence: A Cautious Defense of Raising the Age of Consent in Canadian Sexual Assault Law
Bibliographic record
Abstract
In 2008, Canada raised the age of consent to sexual activity with an adult from 14 years of age to 16. Tis change was motivated, in part, by several high-profile cases of Internet "luring" of younger teenagers. Tis article considers whether raising the age of consent has had any benefits. It begins by discussing the history and development of age of consent laws in Canada. Te justification for a statutory age of consent has shifted from one based on the age at which a girl is deemed to be sexually available to one based on her capacity to give a valid consent to sexual activity. Te article examines the arguments made by groups who opposed raising the age of consent, but finds those arguments unconvincing. It concludes by cautiously supporting a higher age of consent. Te higher age limit captures exploitation of young people that was not subject to criminalization in the past. However, a formal age of consent may also normalize exploitative sexual relationships that contain a significant age disparity, where the younger party is only marginally over the age of consent. It is argued that age should be a factor in determining whether a relationship is exploitative even where both parties are over the age of consent. Te fact that both parties in a relationship are over the formal age of consent should not relieve the courts from the responsibility to consider whether there was coercion or an abuse of power or trust.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.033 | 0.038 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.013 | 0.017 |
| 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".