The Discriminatory Use of the “KGB Procedure” by Police Against Women in Canada
Bibliographic record
Abstract
In R. v. B. (K.G.) (KGB), the Supreme Court identified the procedural criteria necessary to ensure sufficient reliability of certain types of witnesses’ police statements, such that they can be introduced for the truth of their contents. The criteria include that the statement be videotaped, taken under oath, and that the witness be cautioned regarding the severe penal sanctions they could face if they lie. The type of witnesses contemplated are accomplices, coaccused, or others whose character makes them presumptively untrustworthy, and whose statement may become necessary because of the likelihood that they will recant at trial. The Court did not intend for KGB to be used generally, and the police do not typically impose this protocol on people who report crimes. Indeed, there are two types of witnesses subjected to KGB when they give statements to the police: those the Court intended (criminally implicated, coaccused or presumptively untrustworthy witnesses) and women who allege sexual or gender-based violence. A close examination of case law, the rules of evidence, and Crown prosecution standards reveal that imposing this protocol on women who allege sexual and other gender-based violence is, in the vast majority of cases, pointless, rooted in discriminatory assumptions about women and rape, and likely to impose unnecessary harms on those who turn to the criminal justice system to respond to experiences of sexualized violence.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".