MétaCan
Menu
← Back to cohort
Record W7133073834

School and parental correlates of adolescent substance use

2007· dissertation· W7133073834 on OpenAlexaboutno aff
Jonah Santa-Barbara

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisSubstance useAddictionSubstance abuseIllicit drugLogistic regression
DOInot available

Abstract

fetched live from OpenAlex

This quantitative study assessed the association of various school factors with adolescent substance use, and whether the quality of the adolescent---parental relationship moderated this association. Using the Center for Addiction and Mental Health's (CAMH) 2003 Ontario School Drug Use Survey, data was analyzed from 3,152 adolescent students between the ages of 12 and 20. Logistic regression analysis showed that a number of academic factors are positively (school safety, school belonging) and negatively (academic orientation, views on classes and teachers) associated with adolescents' use of alcohol, cannabis, hard drugs, and a cannabis use problem indicator. Further, the perceived quality of the adolescent/parental relationship appears to moderate the association between certain school factors and cannabis use, hard drug use, and problem level cannabis use. Results are discussed in terms of their integration with existing substance use literature, their implications for adolescent development and substance use prevention programs.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.033
GPT teacher head0.348
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueTSpace→Same topicSubstance Abuse Treatment and Outcomes→French-language works237,207→