Talking to Strangers: A Critical Analysis of the Supreme Court of Canada’s Decision in R v Mills
Bibliographic record
Abstract
In R v Mills, an undercover officer acting without a warrant posed as a 14-year-old girl online and communicated with Mr. Mills through Facebook messages. The officer eventually arranged a meeting with, and arrested Mr. Mills who sought to have the message evidence excluded. The Supreme Court unanimously ruled to allow the evidence. However, only Justice Martin agreed that Mr. Mills’ s. 8 rights were engaged and infringed. This paper takes the position that the Mills decision is inconsistent with prior s. 8 jurisprudence regarding content neutrality and expectation of privacy in conversations. The type of sting operation used in Mills should have been classified as participant surveillance requiring a warrant. In Mills, the Supreme Court unduly adjusted the balance of power to favour law enforcement. The result of the Mills decision is that law enforcement may continue to use this investigative technique unregulated, and unencumbered. Such an adjustment in favour of law-enforcement is not justified. Other investigative techniques are available to law enforcement and obtaining a warrant would not unduly hinder child luring investigations. Failure to oversee these operations could have a potential chilling effect on legitimate online relationships and reinforce stereotypes about hypersexualized youth online.
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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 | 0.032 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.095 | 0.039 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.038 | 0.049 |
| 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".