Adolescent Drug Use in Connecticut Private High Schools: Zero Tolerance, Contextual Peer Influence, and Deterrence Effectiveness
Bibliographic record
Abstract
After the 1994 Gun-Free School Act, schools expanded the use of zero-tolerance policies with all Connecticut private high schools implementing punitive drug and alcohol policies. Based on the criminological theory of deterrence, zero-tolerance policies deliver severe and certain punishments designed to deter rational actors from engaging in problem behaviors. Existing research suggests that adolescents perceive rewards more strongly around peers and lack impulse control, raising the possibility that peer pressure may override rational deterrence in an adolescents’ decision-making process. An “immune group” of adolescents predisposed to ignore punitive deterrents may play a sizable role in inducing peer drug use. If peer influence supersedes deterrence in a significant number of cases, adolescents who are affected both by deterrents and peer pressure may be at a higher risk of following the example of the “immune group.” This study raises the question of whether Connecticut private high school students’ drug use is correlated with perceptions of punishment mandated by school policy and contextual peer influences. A questionnaire that measured students’ drug use on a scale of 1 to 4, perceived severity and likelihood of punishment from 0 to 10, and interaction with drug using peers from 0 to 10, was completed by 50 respondents. The study found no correlations between student drug use and perception of punishment likelihood and severity but found contextual peer influences to be positively associated with expected student drug use in the future. While the results of this study are limited to Connecticut private high school students, the observed tendency in students to disregard risks and pursue peer-involved drug use may be generalized in adolescents. Even in places where school discipline is not a wide issue, the impact of contextual factors like peer influence must be reconceptualized in thinking about school drug policies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".