Medical cannabis identity and public health paternalism
Bibliographic record
Abstract
Objectives: State-dependent and variable lists of medical conditions granting access to medical cannabis in the United States may be an example of public health paternalism. While purporting to ensure that medical use is clearly defined, the variability of approved conditions has created an atmosphere of ambiguity and medical precarity. The purpose of this study is to examine the relationship between "state" and "self" medical cannabis user identities and the ways non-medical users understand their cannabis consumption. Study design: This is a mixed methods study consisting of semi-structured interviews and survey data. Methods: In Phase 1, we examined the relationship between self and state-sanctioned cannabis identity, drawing on the 2022 New Frontier Data Consumer Survey of current cannabis consumers (N = 4682). In Phase 2, we conducted eight semi-structured interviews with a separate sample of adults who use cannabis regularly but do not consider themselves "medical consumers". Results: Self-reported cannabis identity was significantly related to the adoption of a cannabis consumer identity. Those who self-identified as solely medical or recreational consumers were more likely to reject the identity of "cannabis consumer" than those who identified as both. Self-medical identity was overshadowed by use for "wellness" among interviewees. Most interviewees, despite not identifying as medical users, report therapeutic benefit. Their identity as a cannabis consumer, is tied to the definition of "medical cannabis patient" where they live as well as the fluctuating role of cannabis related to their well-being across their lifespan. Conclusions: The designation of medical vs. nonmedical use of cannabis varies from state to state, which is not the case for other medicine. This highly variable designation may be paternalistic in nature as governments attempt to differentiate between "legitimate" and "illegitimate" use in the context of federal cannabis prohibition. As a result, lines between medical use and wellness are blurred, which impacts consumer self-identity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".