A Proposal for Police Acquisition of ISP Subscriber Information on Administrative Demand in Child Pornography Investigations
Bibliographic record
Abstract
The Supreme Court of Canada concluded in R v Spencer that police acquisition of subscriber information from an internet service provider engages a reasonable expectation of privacy. Although this conclusion is principled, it has also resulted in significant obstacles for police investigating child pornography offences. Applying for a production order is not, however, the only option that would pass constitutional muster. By focusing on the way in which information is revealed when combining internet subscriber information with a user’s Internet Protocol address, it is possible to significantly mitigate the seriousness of any invasion of privacy. This in turn can be used to justify significantly lower requirements for police conducting investigations into at least some online crimes.
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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 | 0.037 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.064 | 0.021 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".