Three Years In: A Consideration of the Impacts of Canada’s Legalization of Cannabis on Law Enforcement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In October 2018, Canada legalized recreational cannabis. Key goals of legalization included reducing access by minors and eliminating the illicit market. Now, three years into the legal regime, important public policy questions are beginning to emerge. With police being tasked to enforce the Cannabis Act and associated provincial/territorial legislation, there is a critical need to understand their experiences, including the successes they have had, challenges they have experienced, and issues that remain unresolved. This paper begins to address these issues by presenting results from a qualitative study involving law enforcement personnel who, through their primary roles and responsibilities, have been actively involved in overseeing cannabis enforcement (in supervisory roles) since legalization in October 2018. Three key findings emerged from the analyses, and all were tied to the overarching perception that the illicit cannabis market has persisted since legalization: 1) there is a small but significant pattern of abuse of the medical system of production and distribution, specifically tied to designated grower provisions; 2) there are many challenges associated with halting online sales of illicit cannabis; and 3) the issue of unregulated sales of cannabis from Indigenous reserves remains a “hot button” political issue, in need of resolution.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it