Consumption plans for the rest of the night among Australian nightlife patrons
Bibliographic record
Abstract
Curtis, A., Coomber, K., Droste, N., Hyder, S., Mayshak, R., Lam, T., Gilmore, W., Chikritzhs, T., & Miller, P. (2017). Consumption plans for the rest of the night among Australian nightlife patrons. The International Journal Of Alcohol And Drug Research, 6(1), 19-25. doi:http://dx.doi.org/10.7895/ijadr.v6i1.243Aims: This study investigates associations between blood alcohol content (BAC), gender, location, time of night, and intention to consume more alcohol, energy drinks, and illicit drugs following a street intercept interview.Design: Interviews were conducted from December 2011 to July 2012.Setting: Interviews were conducted in nightlife areas of Sydney, Melbourne, Perth, Wollongong, and Geelong, between 8 p.m. to 5 a.m.Participants: Data from 4,203 participants are utilized in the current paper.Measures: Participants were asked demographic questions, as well as questions about their intentions for the rest of the night (further alcohol, drug, and energy drink use), and completed a breathalyzer test.Findings: Over 70% of the nightlife patrons intended to consume more alcohol, and this was more likely for males, regional patrons, and those with a BAC of over 0.08 g/100 ml. Overall, intention to use drugs was consistent across BAC, location, and time of night, though males were significantly more likely than females to intend to consume drugs.Conclusions: Given the risky behaviors of the most intoxicated group out drinking late at night, interventions that target latenight drinking, high levels of intoxication, and high-risk drinkers are indicated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".