The spread of substance use and delinquency between adolescent twins.
Bibliographic record
Abstract
This investigation examines the spread of problem behaviors (substance use and delinquency) between twin siblings. A sample of 628 twins (151 male twin pairs and 163 female twin pairs) drawn from the Quebec Newborn Twin Study completed inventories describing delinquency and substance use at ages 13, 14, and 15. A 3-wave longitudinal actor-partner interdependence model (APIM) identified avenues whereby problem behaviors spread from one twin to another. Problems did not spread directly between twins across domains. Instead, 2 indirect pathways were identified: (a) Problems first spread interindividually (between twins) within a behavioral domain, then spread intraindividually (within twins) across behavioral domains (e.g., Twin A delinquency → Twin B delinquency → Twin B substance use); and (b) problems first spread intraindividually (within twins) across behavioral domains, then spread interindividually (between twins) within a behavioral domain (e.g., Twin A delinquency → Twin A substance use → Twin B substance use). Controls for genetic effects, gene-environment correlations, friend substance use and delinquency, and parenting behaviors increase confidence in the conclusion that twin siblings uniquely contribute to the spread of problem behaviors during adolescence. Twin sibling influence is a risk factor for illicit substance use, both because substance use by one twin predicts substance use by the other twin, but also because delinquency in one twin predicts delinquency in the other twin, which then gives rise to greater substance use. (PsycINFO Database Record
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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 | 0.010 |
| 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".