The Development of Medical Marihuana Law in Canada and its Effect on Michigan Marihuana Statutes
Bibliographic record
Abstract
incarcerated, and subjected to untold damage to his social life and career."6 Recreational use of marihuana has been criminalized in both Canada and the United States for decades.However, the medical use of marihuana has been decriminalized in Canada since 2001, defensible in areas of the United States beginning in 1996, and defendable in Michigan following the passing of a voter initiative in 2008.7 Due to the close proximity and inevitable social comingling of Canada and Michigan, the evolution of Canadian medical and recreational marihuana regulations may impact parallel statutes in Michigan specifically, as well as the United States generally.Similarly, the accessibility of Canadians to Michigan and Michiganders to Canada creates an undeniable relationship between marihuana regulations in either location and marihuana consumption in the other.The question remains, will Canada's medical marihuana reforms and movement towards federal decriminalization shift Michigan's regulations along with the United States' federal statutes in a similar direction?II.THE LAW A. Canada The recreational use of marihuana is not permitted in Canada; however, residents are permitted to use cannabis for medical purposes.8 Cannabis is prescribed in Canada "for conditions such as cancer, multiple sclerosis, spinal cord injury, hepatitis, and arthritis . . .[as well as] anxiety, stress, depression, and pain." 9 6.Ruth C. Stern & J. Herbie DiFonzo, The End of the Red Queen's Race:
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".