Changes in Quantity Measures of Various Forms of Cannabis Consumption among Emerging Adults in Canada in Relation to Policy and Public Health Developments
Bibliographic record
Abstract
Limited research examines changes in quantities of various forms of smoked/vaped cannabis among regular consumers, including emerging adults (EAs; 18 to 29) in Canada. This information is particularly relevant in the current context of emerging cannabis behaviors among EAs related to political amendments (legalization of cannabis), vaping-related lung illnesses (EVALI), and unprecedented pandemics (COVID-19). This study investigated the impact of legalizing recreational cannabis use in Canada, the EVALI epidemic, and the COVID-19 pandemic on the quantity of smoked/vaped forms of cannabis in relation to gender differences. EAs retrospectively self-reported the quantity of herb, hash, concentrates, joint size, and the number of joints and vaping cartridges in relation to three consecutive developments: pre-legalization, post-legalization; pre-EVALI, post-EVALI, pre-COVID-19, and during COVID-19. The quantity of herb use significantly increased among heavy users, and vaping quantity significantly increased among light users. Overall, an increasing incremental trend was observed in the average quantity of cannabis forms used over time. Males consumed higher quantities of all cannabis forms than females. More males than females reported using concentrates (p < 0.05). These findings reveal unique aspects of the amount of various cannabis forms smoked/vaped in relation to gender and provides preliminary evidence of cannabis consumption behaviors in relation to changing social and cultural contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".