Bridging the gap: Exploring consumer experiences and motivations for transitioning between illicit and regulated cannabis markets
Bibliographic record
Abstract
BACKGROUND: Canada pioneered the non-medical legalization of cannabis production and sales, witnessing substantial growth in the regulated market over the last five years, post-legalization. However, persistent barriers hinder many consumers from transitioning to the legal market, necessitating a nuanced understanding of their behaviors for targeted policy interventions. This study aims to improve understanding of cannabis consumers' unregulated purchase decisions in British Columbia (B.C.), and to explore motivational factors for transitioning to the legal market. METHODS: We conducted semi-structured interviews with cannabis consumers in B.C., who were at least 19 years old and purchased some or all of their cannabis through unregulated sources. Interviews were transcribed and an inductive thematic analysis was conducted using NVivo. Through coding iterations, we moved from descriptive to analytic codes, and finally mapped the codes to themes aligned with the Five Stages of Consumer Decision Making model. RESULTS: Participants (N = 31) represented a broad range of demographic characteristics (i.e., gender, age, education, income). Four themes were identified: seeking information, evaluation of alternatives, purchase decision, and post purchase evaluation. Despite purchasing all or some of their cannabis from the unregulated market, most participants were supportive of legalization and felt that legal cannabis is safe, accessible, and of reasonable quality. However, several barriers prevent consumers from regularly accessing the regulated market, including: price, lack of sales and promotions, potency, limited product variety, and inadequate product interaction. CONCLUSION: This study delineates barriers that obstruct consumers' transition to the regulated market. These findings, aligned with considerations for public health and safety, offer valuable insights to inform cannabis policy and promote a more effective and consumer-oriented regulatory framework.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".