Bibliographic record
Abstract
This paper asks whether the technological changes wrought by the digital revolution require concomitantly dramatic changes to the Supreme Court of Canada’s section 8 jurisprudence. The author answers “no”. While technological change inevitably influences constitutional interpretation and application, the foundation set out by the Court in digital (and other) section 8 cases over the past two decades provides the conceptual and doctrinal tools needed to achieve reasonable accommodations between competing privacy and law enforcement interests in the digital era. The paper begins with a brief overview of the basic elements of section 8 law. Next, it chronologically surveys the Supreme Court’s existing “digital section 8” jurisprudence, that is, each decision that has addressed allegations that the state has violated section 8 in a digital realm. The next part distils three key doctrines from these cases that are likely to animate future digital section 8 decisions: (i) the notion that “computers are different”; (ii) the role of contract, statute and other exogenous norms in shaping privacy expectations over information obtained or held by third parties; and (iii) the application of the “biographical core” test to “low resolution” private information. While there is consensus as to the core meanings of each of these doctrines, to varying degrees each suffers from indeterminacy in application. The author therefore proposes refinements to minimize that indeterminacy. The following part examines, from both descriptive and prescriptive perspectives, how these doctrines played out in the Court’s most recent digital section 8 decision: R. v. Spencer .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| 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".