Medical Marijuana: Canada's Regulations, Pharmacology, and Social Policy
Bibliographic record
Abstract
Introduction: This paper gives an introduction to important aspects of Canada's medical marijuana policy. It reviews the history and the physiological effects of marijuana, as well as four social theories that have contributed to the traditional view of marijuana use as “drug abuse.” Methods: A PubMed search was conducted using the search words “medical marijuana Canada” for the period 1980 to 2002. Articles were included if they contained information on marijuana's physiological effects or social issues. An internet search using www.Google.com and the same search words was conducted. Websites were included if they contained information on medical marijuana policy in Canada. Secondary literature provided background on social theory. Setting: Canada's federal policy on medical marijuana. Results and Discussion: In 2001, Canada became the first nation to implement a national policy allowing for the use and paid supply of marijuana for medicinal purposes, and this policy generated both vigorous debate and general public support. The new policy has been accompanied by a cooperative research effort between Health Canada and the Canadian Institutes of Health Research to prove marijuana's therapeutic efficacy.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".