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Record W2012474084 · doi:10.1037/1099-9809.14.3.266

Adolescent alcohol use in context: The role of parents and peers among African American and European American youth.

2008· article· en· W2012474084 on OpenAlexfundno aff
Deborah J. Jones, Andrea M. Hussong, J. Sloan Manning, Emma Sterrett

Bibliographic record

VenueCultural Diversity & Ethnic Minority Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersNational Institute on Drug AbuseUniversity of British ColumbiaUniversity of North Carolina at Chapel HillNational Institutes of HealthUniversity of Victoria
KeywordsAfrican americanModerationPsychologyContext (archaeology)Intervention (counseling)Developmental psychologyAdolescent developmentClinical psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

African American youth are less likely to use alcohol than their European American counterparts; however, the greater consequences of use for African American youth highlight the need for greater research attention to this group. Two social contexts that have been linked with adolescent alcohol use are parents and peers, yet these studies have rarely included African American youth or failed to examine potential racial differences. This study examined the main and interactive effects of parents and peers, as well as the moderating role of race on alcohol use, in African American and European American rural adolescents (n=71) identified as at high-risk for alcohol use. Contrary to study hypotheses, however, parents were not a more robust moderator for African American than European American youth. Clinical implications for prevention and intervention programming for both African American and European American youth are discussed.

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)0.002
metaresearch head score (Gemma)0.005
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
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.079
GPT teacher head0.304
Teacher spread0.224 · 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

Citations31
Published2008
Admission routes1
Has abstractyes

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