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Record W2047415208 · doi:10.1080/1067828x.2013.786921

Association of Educational Attainment and Adolescent Substance Use Disorder in a Clinical Sample

2014· article· en· W2047415208 on OpenAlexaff
Tunde Apantaku-Olajide, Philip James, Bobby P. Smyth

Bibliographic record

VenueJournal of Child & Adolescent Substance Abuse · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsSaint John Regional HospitalDalhousie University
Fundersnot available
KeywordsSubstance abusePsychosocialPsychologySubstance useDropout (neural networks)Intervention (counseling)Clinical psychologyMainstreamOddsPsychiatryDemographicsEducational attainmentMedicineLogistic regressionDemography

Abstract

fetched live from OpenAlex

This study explores substance use, psychosocial problems, and the relationships to educational status in 193 adolescents (school dropouts, 63; alternative education, 46; mainstream students, 84) who attended a substance abuse treatment facility in Dublin, Ireland, within a 42-month period. For each adolescent, data on demographics, family background, substance use, psychiatric history, and offending behaviors were collected. The study found that the 3 groups exhibited statistically significant differences in their substance use problems, with the school dropouts displaying significantly more problems. The need for early detection and intervention of at-risk students, and collaborative interagency work aimed at addressing substance use, cannot be overemphasized as strategies to ultimately prevent school dropout.

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)0.003
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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