An Analysis of Third Party Record Applications Under the Mills Scheme, 2012-2017: The Right to Full Answer and Defence versus Rights to Privacy and Equality
Bibliographic record
Abstract
Over the last several decades, third-party record applications have begun to eclipse the use of prior sexual history as the main tool for challenging the credibility of sexual assault complainants in criminal trials.This article outlines the early common law and statutory developments governing the use of third-party record applications, identified as the "Mills scheme," and analyzes these cases through the lens of how they balance the privacy and equality rights of complainants with the right to full answer and defence of accused persons.The author then examines the decisions of 22 cases at the Ontario Superior Court during the period of 2012-2017 that applied the "Mills scheme," finding that in nearly 50% of those cases, disclosure of records in which the complainant had a high privacy interest was ordered by the court.The author argues that the s.278 provisions of the Criminal Code direct judges to weigh defendant's legal rights against both the privacy and security of the person rights of complainants, in light of the equality context, while * Heather is a JD Candidate (2019) at Osgoode Hall Law School in Toronto, Ontario.A former United Nations intern, Heather was the co-winner of the Aird & Berlis and Women's Law Association of Ontario 2018 Equality Award, for her efforts in combatting gender-based violence and championing diversity in the legal profession.She is the current President of the Law Students' Society of Ontario and the President of the Osgoode chapter of Canadian Lawyers for International Human Rights.Heather intends to pursue a career working in criminal, constitutional, and international law.You can follow her on Twitter at @HeatherDonkers.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".