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Record W2063034591 · doi:10.5539/gjhs.v4n1p57

Alcoholic Beverages Drinking among Female Students in a Tourist Province, Thailand

2011· article· en· W2063034591 on OpenAlexvenueno aff
Wirin Kittipichai, Hatairat Sataporn, Nithat Sirichotiratana, Phitaya Charupoonphol

Bibliographic record

VenueGlobal Journal of Health Science · 2011
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersFaculty of Public Health, Mahidol UniversityMahidol UniversityChina Medical Board
KeywordsTourismEnvironmental healthMedicinePsychologyGeographyDemographySociology

Abstract

fetched live from OpenAlex

This study aimed to investigate alcoholic beverages drinking and predictive factors among female students. The participants were 377 subjects from 3 high schools in a tourist province, of Thailand. Data collection was done through self-administered questionnaire. Scales of the questionnaire had reliability coefficients ranging from 0.84 - 0.88. The data were analyzed by using descriptive and inferential statistics. The findings revealed as follows. About half (51%) of them have ever drunk and 10.5% of drinkers have drunk once a week. In addition, 15.6% of drinkers began their first drink when they were under 10 years old. Risk factors for alcohol consumption of female student were age, GPA, drinker in family, peer pressure, advertisement and accessibility to alcoholic beverages while protective factors were perception of drinking impacts on family and moral values. Students who have a drinking family member were 4.6 times more likely to drink than those who do not have.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.354
Teacher spread0.309 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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