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Record W2140556697 · doi:10.1037/1089-2699.11.1.31

Group alcohol climate, alcohol consumption, and student performance.

2007· article· en· W2140556697 on OpenAlexfundno aff
Jennifer Carson, Julian Barling, Nick Turner

Bibliographic record

VenueGroup Dynamics Theory Research and Practice · 2007
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAlcoholAlcohol consumptionPsychologyMultilevel modelConsumption (sociology)Social psychologyEnvironmental healthMedicineSociologyMathematicsChemistry

Abstract

fetched live from OpenAlex

This study explored the relationship between group norms for drinking and two indicators of student performance. Based on data from 96 undergraduate students (mean age 22 years) living in 21 student houses, the multilevel hypotheses that (a) house alcohol climate is associated with student alcohol consumption, (b) student alcohol consumption is associated with student withdrawal behavior (i.e., absence from class), and (c) that student alcohol consumption mediates the link between house alcohol climate and student withdrawal behavior are supported. No link between student alcohol consumption and student academic performance (i.e., average grades) was found. Similarly, there was no empirical support for the hypothesis that house cohesion would moderate the relationship between house alcohol climate and student alcohol consumption. Implications for future research 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)0.012
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.429
Teacher spread0.340 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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