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Record W2058482823 · doi:10.2190/de.42.1.e

Starting to Drink: The Experiences of Australian Lower Secondary Students with Alcohol

2012· article· en· W2058482823 on OpenAlexaff
Gillian Davenport, Richard Midford, Robyn Ramsden, Helen Cahill, Lynne Venning, Leanne Lester, Bernadette Murphy, Michelle Pose

Bibliographic record

VenueJournal of Drug Education · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsContext (archaeology)Psychological interventionRural areaHarmSuicide preventionEnvironmental healthPoison controlGovernment (linguistics)Injury preventionMedicinePsychologyGeographySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study describes Australian year eight students' (13-14 years old) experiences with alcohol in terms of communication with parents, initiation into drinking, patterns of consumption, context of use, and harms experienced. The sample comprised 521 year eight students from four state government secondary schools in the state of Victoria. Three of the schools are in Melbourne, the capital of Victoria; the fourth is in a rural center. Female and rural students were more likely to talk to parents about alcohol, but this was not associated with safer drinking. Initiation into drinking was higher among rural students. Rural students also drank more, were more likely to drink without adult supervision, to drink to get drunk, and drink more than planned. Student drinkers experienced just over four alcohol-related harms on average in 12 months, with some indication of greater harm among rural students. Higher levels of drinking by rural students, accompanied by more risky patterns of consumption and the possibility of greater harm, supports prioritizing interventions in rural schools.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.048
GPT teacher head0.460
Teacher spread0.412 · 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 designQualitative
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

Citations3
Published2012
Admission routes1
Has abstractyes

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