A "Reasonable" Expectation of Sexual Privacy inthe\nDigital Age
Bibliographic record
Abstract
Two Criminal Code offences, voyeurism, and the publication of intimate images without consent, were enacted toprotect Canadians' right to sexual privacy in light of invasive digital technologies. Women and girls are overwhelmingly targeted as victims for both of these offences, given the higher value placed on their non-consensual, sexualised images in an unequal society.Both offences require an analysis ofwhether the complainant was in circumstances giving rise to a reasonable expectation of privacy, and the use of this standard is potentially problematic both from a feminist standpoint and in light of the rapidly evolving technological realities of the digital age. This article proposes a feminist-inspired, technology-informed approach to the reasonable expectation of privacy standard in relation to these offences, and examines the extent to which the Supreme Court of Canada's recent voyeurism decision, R.v. Jarvis, aligns with this approach.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.033 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| 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".