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Record W2088193340 · doi:10.3200/jach.56.3.285-292

Drinking Patterns, Problems, and Motivations Among Collegiate Bisexual Women

2007· article· en· W2088193340 on OpenAlexaff
Wendy Bostwick, Sean Esteban McCabe, Stacey S. Horn, Tonda L. Hughes, Timothy P. Johnson, Jesús Ramírez-Valles

Bibliographic record

VenueJournal of American College Health · 2007
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsInstitute of Gender and Health
FundersNational Institute on Drug AbuseNational Institutes of HealthNational Institute for Health and Care ResearchUniversity of Michigan
KeywordsPsychologyMinority stressPopulationSuicide preventionCoping (psychology)HeterosexualityHomosexualityClinical psychologyInjury preventionPoison controlSexual orientationMedicineSexual minoritySocial psychologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE AND PARTICIPANTS: The authors compared the drinking behaviors, motivations, and problems of collegiate bisexual women with those of heterosexual women (N = 2,788; n = 86 bisexual women). METHODS: Data came from the 2003 Student Life Survey, a random population-based survey at a large midwestern university. The authors explored the hypothesis that bisexual women would be more likely than heterosexual women to report drinking motivations related to stress and coping as a result of sexual identity stigma. RESULTS: They found that bisexual women drank significantly less than did heterosexual women. There were few differences between the 2 groups in drinking motivations and problems. Bisexual women reported a comparable number of problems related to their drinking but were significantly more likely to report contemplating suicide after drinking than were heterosexual women. CONCLUSIONS: More research is needed to understand the finding that despite lower levels of alcohol consumption, bisexual women reported a comparable number of drinking problems. College health educators and health care providers need to be aware of findings related to heightened suicidal risk among bisexual women.

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)0.002
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 score0.010
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.363
Teacher spread0.328 · 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

Citations28
Published2007
Admission routes1
Has abstractyes

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