Case comment: a critique of the Supreme Court of Canada's use of statistical reasoning in R v. Mabior
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This case comment critiques the Supreme Court of Canada’s decision in R v. Mabior. In Mabior, Chief Justice McLachlin affirmed the criminalization of human immunodeficiency virus (HIV) non-disclosure to sexual partners, and sought to clarify exactly when criminal sanctions apply. Citing expert evidence, McLachlin CJC held that criminal liability is appropriate for HIV non-disclosure when there is a ‘realistic possibility of transmission’ and that only condom use combined with antiretroviral therapy reduces this risk enough to preclude liability. Using the same expert evidence, I calculate the transmission rates underlying this argument and show that McLachlin CJC’s use of statistics results in logical contradictions and uncertain liability. I argue that her statistical approach is unworkable and I propose an alternative non-disclosure regime.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it