<i>Trailer Park Boys</i> and the Promotional Cultures of Cannabis in Canada: Audiences, Influencers, and Imminent Commodities
Bibliographic record
Abstract
While Canada, like most other nation states, has adopted various aspects of neoliberalism, the recent Cannabis Act presents ideological tensions and practical concerns given its advertising and promotional restrictions. Given the rise of neoliberalism within the dominant social, economic, and cultural system of consumer capitalism, it seems contradictory for the Canadian state to develop legislation that creates (or at least, legalizes) a new market wherein advertising and promotions (i.e., the driving forces of consumer capitalism) are effectively made absent. This article identifies and interrogates the existing tensions and contradictions between the Cannabis Act and the promotional cultures of consumer capitalism, as well as the ways in which the Trailer Park Boys (TPB) “brand” and performers (as promotional intermediaries) have attempted to circumvent the existing promotional restrictions. Beginning with a review of the existing literature regarding relevant theoretical perspectives and key concepts, the article provides a brief overview of the Cannabis Act, its promotional restrictions, and the exemptions and legal loopholes thereof. Finally, in presenting and engaging with a case study, this article concludes that the TPB brand has, effectively, circumvented the Cannabis Act’s existing restrictions and subsequently become a multi-platform promotional intermediary.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".