Taxing Disability: A Critical Look into the Medical Cannabis Regime under the New Cannabis Act, 2018
Bibliographic record
Abstract
Medical marijuana users represent many people with disabilities in Canada. Recent legislative attempts have allowed people with disabilities to access cannabis as medicine, however the landscape is ever changing. The Cannabis Act was recently introduced, legalizing marijuana for all; however, people with disabilities have not been accounted for when it comes to the issue of access to medicine. Those who rely on cannabis as medicine and those who enjoy it recreationally are now part of the same system, for better or worse. The new medical marijuana regime, under the new Cannabis Act, boasts a “two-stream” process, and it claims that it will be maintaining and improving the old medical regime alongside the new recreational regime. The applicable taxes tell a different story. Medical marijuana has always been subject to sales tax despite being effectively prescribed by doctors to manage and treat many disabilities and illnesses. Now, with the enactment of the Cannabis Act, medical marijuana is subject to an excise tax too—colloquially known as the “sin tax.” Recreational and medical marijuana are subject to the same taxation scheme, making any notion of a “two-stream” process nonsensical and blatantly unfair. The purpose of this article is to provide insight into the varying faults concerning the medical marijuana regime in Canada, with specific emphasis on the issue of taxation. In the simplest terms, taxing medical marijuana is taxing medicine and effectively taxing people with disabilities. Broken down into five parts, this article discusses the underlying reasons for the taxes surrounding medical marijuana, provides a case study of the most important tax case for medical marijuana users, scrutinizes the lack of recognition of medical marijuana as a proper prescription, outlines the ways to improve legislation, and, finally, explores a potential Charter challenge that can be effectively brought against this taxation.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.017 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".