Protecting Research Confidentiality via the Wigmore Criteria: Some Implications of Parent and Bruckert v The Queen and Luka Rocco Magnotta
Bibliographic record
Abstract
Abstract There have been two significant legal challenges to research confidentiality in Canada. The first occurred because of a Coroner’s subpoena, with the researcher invoking the Wigmore criteria and winning a researcher-participant privilege. A second case saw two University of Ottawa researchers served with a search warrant for the tape and transcript of an interview they had conducted years earlier with an individual subsequently accused of murder. The researchers defended research confidentiality in Quebec Superior Court, winning a qualified researcher-participant privilege in the process. This article discusses implications of the court’s decision for researchers, research ethics boards, and universities for the future defence of research confidences. All have a role to play in designing research that anticipates the court’s evidentiary requirements when a claim of privilege is invoked to help ensure future jurisprudence is as favourable to research participants and as respectful of academic freedom as possible.
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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 | 0.130 | 0.220 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.045 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.023 | 0.021 |
| Insufficient payload (model declined to judge) | 0.002 | 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".