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Human Rights Litigation and the Medicalization of Cannabis in Canada, ca. 2000–Present

2019· article· en· W2998785239 on OpenAlexaboutno aff
DeCloedt

Bibliographic record

VenuePharmacy in History · 2019
Typearticle
Languageen
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLegalizationCannabisLawDecriminalizationPolitical scienceHuman rightsCriminalizationRecreationMedicinePsychiatry

Abstract

fetched live from OpenAlex

Cannabis was legalized for recreational purposes in Canada on October 17, 2018. The push to overturn nearly a century of prohibition seemingly took place overnight after Justin Trudeau promised legalization as part of his 2015 federal election platform. Canadians were already familiar with debates for and against a policy change. Starting in the early 2000s, cannabis advocates challenged its criminalization in Canadian courts from a health and human rights perspective. Part of this strategy included proving cannabis’s relative harmlessness from both social and scientific points of view, something widely accepted by the courts. Nonetheless, it took several legal decisions to create and open a market for medical cannabis. Its consequent availability, however limited, introduced Canadians to its medical value. Recreational cannabis was a separate, yet entwined, issue. The Canadian government refused to allow cannabis use for anything other than therapeutic purposes. Courts were not as receptive to arguments related to liberty and autonomy without a healthcare angle and would not force the federal government to change its prohibitionist tack. This article tracks how litigants wore away at prohibition by articulating their claims in the language of constitutional rights and freedoms. It then evaluates the courtroom adjudication of science and medicine in light of the legal interpretation of John Stuart Mill’s “harm principle.” These discourses were key in framing how professionals and the public came to know cannabis as a medicine to which they had a right to use and paved the way for its legalization and regulation for recreational purposes in 2018.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.272
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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