Do We Throw Our Privacy Rights Out With the Trash? The Alberta Court of Appeal’s Decision in <i>R. v. Patrick</i>
Bibliographic record
Abstract
Grocery lists, birth control information, bank records, and intimate letters to friends past: all are personal items that find their way into the garbage bins of Canadians on a daily basis.1 Canadians have come to expect that once a garbage bag is thrown in a bin behind a home, it makes a direct uninterrupted trip to a landfill, a place where its contents will remain private through the decomposition process. Few realize that, quite frequently, the police, as state agents charged with the responsibility of solving criminal cases, sift through the discarded items of Canadians in the hunt for valuable information. This police behaviour raises two important constitutional questions...
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".