Bibliographic record
Abstract
Following a number of acquittals based on a strict interpretation of the terms of the Food and Drugs Act, the Supreme Court of Canada recently had to determine, in Dunn, if a mushroom containing « psilocybin » was a restricted drug despite the fact that the legislation was referring only to the chemical substance and not to the plant itself The Supreme Court found that the text was clear and that the fact that « psilocybin » may be contained within a mushroom does not destroy its character as a restricted drug. Drug traffic must naturally be condemned, but that is not the problem for the moment. The problem is that the Supreme Court of Canada adopted, in Dunn, the rule of the liberal interpretation of a penal statute despite the fact that, not so long ago, it chose a different approach when dealing with a different statute. We are critical of both the way the inferior courts treated the cases before them and the way the legislator treated the problem. We think that it was possible for the lower courts to find the accused guilty of attempting to commit the offense. We think also that it was possible for the legislator to anticipate those situations and take some precautions by deliberately adopting a text capable of embracing these cases.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".