Western Australian students’ alcohol consumption and expenditure intentions for Schoolies
Bibliographic record
Abstract
In Australia, the immediate post-school period (known as 'Schoolies') is associated with heavy drinking and high levels of alcohol-related harm. This study investigated students' intended alcohol consumption during Schoolies to inform interventions to reduce alcohol-related harm among this group. An online survey was administered to students in their senior year of schooling. Included items related to intended daily alcohol consumption during Schoolies, amount of money intended to be spent on alcohol over the Schoolies period, and past drinking behaviour. On average, participants (n=187) anticipated that they would consume eight standard drinks per day, which is substantially higher than the recommended maximum of no more than four drinks on a single occasion. Participants intended to spend an average of A$131 on alcohol over the Schoolies period. Although higher than national guidelines, intended alcohol consumption was considerably lower than has been previously documented during Schoolies events. The substantial amounts of money expected to be spent during Schoolies suggest this group has adequate spending power to constitute an attractive target market for those offering alternative activities that are associated with lower levels of alcohol-related harm.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".