Cut-and-Paste Justice: A Case Comment on Cojocaru v. British Columbia Women's Hospital and Health Centre
Bibliographic record
Abstract
Can judges simply copy-and-paste, without attribution, vast portions of a party’s factum in their own reasons? At what point does this practice become so egregious that it risks rebutting the presumption of integrity and impartiality from which all judges benefit? This question was put before the Supreme Court of Canada in Cojocaru v. British Columbia Women’s Hospital and Health Centre (2013 SCC 30, [2013] 2 SCR 357). In this case comment, the author reviews the Cojocaru decision and the Court’s analysis, discusses the decision’s shortcomings, considers the main takeaways for various parties, and examines a surprising comment contained in the decision.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.056 | 0.020 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.038 | 0.037 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".