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Record W4366525808 · doi:10.1080/14659891.2023.2202735

How do mandated college student drinkers characterize binge drinking?

2023· article· en· W4366525808 on OpenAlexaboutno aff
Benjamin N. Montemayor, Adam E. Barry

Bibliographic record

VenueJournal of Substance Use · 2023
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsBinge drinkingPsychologyAlcoholAlcohol consumptionQuarter (Canadian coin)Environmental healthClinical psychologyMedicineInjury preventionPoison control

Abstract

fetched live from OpenAlex

Background Within the past 30 days, a quarter of U.S. college students reported binge drinking (i.e., consuming ≥ five drinks (male) or ≥ four drinks (female), in about 2 hours). While scholars have refined binge drinking parameters/definitions over time, determining college students’ personal characterization of binge drinking is important as misperceptions can directly impact students’ alcohol use and associated consequences.Objective This study explored differences in college students’ characterization of binge drinking and the effect of overestimating standardized parameters.Methodology This study was conducted at a large public university in the Southeast U.S. among college students who violated campus alcohol-use policies (n = 816). Respondents anonymously completed measures of alcohol frequency and quantity, and binge drinking characterization. Analyses explored the relationship between binge drinking parameters and personal alcohol use.Results Statistically significant differences existed for alcohol consumption between students who underestimated/accurately characterized binge drinking parameters and those who overestimated. Moreover, students who overestimated participated in binge drinking more frequently (p < .001) and were nearly 3.5 times more likely to binge drink than their counterparts.Conclusions Correcting misperceptions, establishing clear and accurate understandings, and eliminating ambiguity associated with alcohol behaviors and norms should be a priority for college health practitioners and administrators.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.290
Teacher spread0.243 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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