Transitioning to The New Rural Cannabis Economy – Using Transitioning Economies and Stakeholder Participation as a Theoretical Basis
Bibliographic record
Abstract
On October 17th, 2018, recreational cannabis was legalized in Canada under Bill C-45, the Cannabis Act. While British Columbia (B.C.) was recognized for illicit cannabis production in the prohibition era, detailed and accurate information remained unknown, persisting a lack of consideration during federal and provincial policy formulation. Now historically producing rural regions in B.C., like the Kootenays, are forced to transition to the legal regime, treading on uncharted territory. Prohibition-era participants are key stakeholders of cannabis legalization but they remain underrepresented and largely hidden partly because of continued repercussions with speaking out. Theorizing the pre-legalization cannabis industry employed a substantial component of the workforce in many parts of rural B.C., this transition is important and complex, and has the potential to yield grave consequences for many small communities if left unaddressed. In order to identify socioeconomic risks that historically producing rural regions in B.C. are likely to face during the transition to legalization, as well as to formulate strategies that can be used to adapt to this policy change that appropriately addresses hidden populations, literature around transitioning economies and stakeholder participation is examined. This paper outlines these two traditions providing a theoretical lens from which to reliably examine legalization in rural parts of B.C., using the Kootenay region as the case study, in order to illuminate challenges and opportunities.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".