The Strains of Inequality: An Exploration of the Effects of Cannabis Legalization on Black and Indigenous Peoples in Canada
Bibliographic record
Abstract
This thesis presents the lived experiences of 19 Black, Indigenous, and white individuals in the new age of cannabis legalization within Canada, to demonstrate the long-lasting and unintended consequences of decades of drug prohibition and criminalization.As a response to the promise that legalization would bring with it racial justice, this research centres the experiences of racialized people, bringing into focus forms of inequality, prejudice and discrimination that remain intact despite changes to drug policy.To complement numerous quantitative studies on the lasting impacts of cannabis criminalization, this qualitative research explores the nuances of individual experiences of legalization among cannabis users.This research draws on broader theoretical perspectives surrounding settler colonialism, intersectionality, and race to situate both the historical and contemporary effects of cannabis prohibition.This research situates the interview findings within a critical race and cumulative disadvantage framework, using racial habitus as a conceptual tool for understanding the differences in experience across racial categories.By conducting open-focused interviews with Black, Indigenous, and white individuals who use either the new legal means of obtaining cannabis or illegal methods of acquiring it, this thesis reveals the extent to which notions of race become entrenched in the commonly held perceptions of cannabis use and users and in turn, how these notions impact the experiences and decision-making of racialized cannabis users in the post-legalization landscape.From the findings, racial differences are seen in feelings of awareness to differing reactions to cannabis, in perceptions of safety, and in levels mistrust, which in turn establish and enhance barriers to participation in the new legal scheme.In particular, Black and Indigenous interviewees altered their behaviours surrounding their cannabis use while in certain settings based on how they believed they may be perceived.Most notably, Black participants had a general mistrust surrounding the new legal system that influenced all Black participants in this study to refrain from obtaining cannabis through the new legal means.This thesis concludes that race is particularly important when it comes to understanding the impacts of legalization, as it alters the way in which individuals come to be perceived, how they experience phenomena, and how they react to situations.My findings reinforce the need for alternatives outside of drug policy reform in order to address long-standing biases and inequalities related to drugs and the criminal justice system that continue to impact Black and Indigenous communities across Canada.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.046 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".