Open Courts, Privacy and Equality in a Digital Era: The Supreme Court of Canada’s 2021 Open Court Jurisprudence
Bibliographic record
Abstract
This paper analyzes the Supreme Court of Canada’s 2021 open court jurisprudence: Sherman Estate v. Donovan, Canadian Broadcasting Corp. v. Manitoba and MediaQMI inc. v. Kamel. At the heart of our analysis is the exploration of several more latent dynamics found in the cases which, in our view, pose foundational and continuing challenges for open court jurisprudence. Underlying MediaQMI are concerns about the appropriate level of party control over court records. CBC v. Manitoba invites questions about who constitutes the “media” with the increasing democratization and digitalization of information exchange. In Sherman, the concept of privacy — rooted in the section 8 notion of a “biographical core” — encounters tensions with the “default to openness” and potential fluidity that characterizes the open court context. We also identify two broader themes. First, we raise questions as to whether the Court’s open court jurisprudence is “fit for purpose” in an increasingly digitized world of court operations and information exchange. Second, notwithstanding a body of scholarship advocating for equality-infused concepts of privacy, we contend that the Court does not suffıciently address how decisions about court record control, media access and privacy protections are likely to have a disproportionate impact on marginalized people, particularly in an increasingly digital context. We conclude that ultimately, the Court will need to squarely address the challenges posed by digitization and equality-related dynamics in its open court jurisprudence.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.039 |
| Scholarly communication | 0.025 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.011 |
| 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".