Associations Between Marijuana Use Trajectories and Educational and Occupational Success in Young Adulthood
Bibliographic record
Abstract
Adolescence and young adulthood is a critical stage when the economic foundations for life-long health are established. To date, there is little consensus as to whether marijuana use is associated with poor educational and occupational success in adulthood. We investigated associations between trajectories of marijuana use from ages 15 to 28 and multiple indicators of economic well-being in young adulthood including achievement levels (i.e., educational attainment and occupational prestige), work characteristics (i.e., full vs part-time employment, hours worked, annual income), financial strain (i.e., debt, trouble paying for necessities, delaying medical attention), and perceived workplace stress. Data were from the Victoria Healthy Youth Survey, a 10-year prospective study of a randomly recruited community sample of 662 youth (48% male; M age = 15.5), followed biennially for six assessments. Models adjusted for baseline age, sex, SES, high school grades, heavy drinking, smoking, and internalizing and oppositional defiant disorder symptoms. Chronic users (our highest risk class) reported lower levels of educational attainment, lower occupational prestige, lower income, greater debt, and more difficulty paying for medical necessities in young adulthood compared to abstainers. Similarly, increasers also reported lower educational attainment, occupational prestige, and income. Decreasers, who had high early use but quit over time, showed resilience in economic well-being, performing similar to abstainers. Groups did not differ on employment status or perceived workplace stress. The findings indicate that early onset and persistent high or increasingly frequent use of marijuana in the transition from adolescent to young adulthood is associated with risks for achieving educational and occupational success, and subsequently health, in young adulthood.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".