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Record W7073651681

Gender specific trends in alcohol use: cross-cultural comparisons from 1998 to 2006 in 24 countries and regions

2009· article· en· W7073651681 on OpenAlexaboutno aff

Bibliographic record

VenueLenus, The Irish Health Repository (Dr Steevens Hospital Library) · 2009
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsnot available
Fundersnot available
KeywordsDeveloped countryTest (biology)Injury preventionSuicide preventionDeveloping countryPoison controlOccupational safety and health
DOInot available

Abstract

fetched live from OpenAlex

Objective: To examine trends in the prevalence of monthly alcohol
\nuse and lifetime drunkenness among 15 year olds in 20 European countries, the Russian Federation, Israel, the United States of America, and Canada.
\nMethods: Alcohol use prevalence and drunkenness were assessed
\nin the Health Behavior in School-aged Children Survey
\nconducted in each country in 1998, 2002, and 2006. Trends were
\ndetermined using the Cochran-Mantel-Haenszel test for trends.
\nResults: Average monthly alcohol use across all countries declined
\nfrom 45.3 % to 43.6 % and drunkenness declined from
\n37.2 % to 34.8. There was substantial variability across countries,
\nwith decreases in some countries and increases or no
\nchange in use or drunkenness in others. The overall decline
\nwas greater among boys, from 41.2 % to 36.7 % than among
\ngirls, 33.3 % to 31.9 %. In most of the countries where drinking
\nor drunkenness increased, it was due mainly to increases
\namong girls.
\nConclusions: Trends in alcohol use and drunkenness varied by
\ncountry. Drinking and drunkenness remained higher among
\nboys than girls, but the gap between boys and girls declined and
\ngirls appear to be catching up with boys in some countries.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.275
Teacher spread0.242 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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