Legalization Is Only the Start: Canada Must Do Right by Its ‘Cannabis Criminals’
Bibliographic record
Abstract
I started practising criminal law in 1984. I felt relieved that I was not starting my career within the dystopia of repression and fear prophesized for that year by George Orwell. However, I quickly discovered that the war on drugs had reached a fevered pitch by 1984, and that this futile war was fostering repression and a slow movement toward the Orwellian society of rampant state surveillance. Cannabis was still being demonized as the “smoke from hell” and billions of dollars were being wasted manufacturing cannabis criminals out of ordinary, law-abiding and productive citizens. Orwell’s prophecy may have been just a literary vision, but as a young lawyer, it seemed to me that only in a world of science fiction could a plant become public enemy No. 1.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.022 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 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".