Cannabis in Cascadia: Impacts of Legalization in the Region
Bibliographic record
Abstract
The policies regulating the use and sale of cannabis have historically been constructed differently in the United States and Canada, yet both countries had deemed recreational use to be illegal. Beginning in 2012, however, individual states in the U.S. began to legalize recreational cannabis, including Washington, Oregon, and most recently, California. In 2017, the Government of Canada passed similar legislation. If Canada’s legislation goes into effect in mid-2018, the West Coast of North America will become the only contiguous region where recreational consumption and sale of cannabis are permitted across multiple jurisdictions (see Map 1, next page). However, because cannabis remains federally illegal in the U.S., the Canada - U.S. border presents both legal and social challenges that are continually emerging as the recreational cannabis industry expands. This Border Policy Brief examines the development of the recreational cannabis industry in the ‘Cascadia’ region of western British Columbia and Washington State, highlighting the strong regional nature of its legalization, as well as the implications of legalization for the Canada-U.S. border.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".