Out of Sync: Section 8 and Technological Advancement in Supreme Court Jurisprudence
Bibliographic record
Abstract
This article offers a review of recent Supreme Court of Canada search and seizure cases to demonstrate the challenges facing courts, lawyers and law enforcement in applying existing Charter jurisprudence to new technological landscapes. R. v. Vu; R. v. TELUS Communications Co.; R. v. Spencer; and R. v. Fearon highlight the difficulties in drawing boundaries of privacy in computers, mobile devices, “intercepts” and online activity. Our changing social understanding of privacy impacts the sphere of activity and information encompassed by section 8 of the Charter, but easy public and remote access to digital data make drawing lines impractical. The article explores issues of digital security, police search protocols for computer and cell phone evidence, old and new statutory tools for access to information and the role of third parties in information control and disclosure.
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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 | 0.033 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.013 | 0.048 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".