Why Do University Students From Australia, New Zealand, and Argentina Play Drinking Games? A Mixed-Method Cross-Country Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Qualitative work suggests that young people’s motives for playing drinking games (DGs) extend beyond those assessed in the Motives for Playing Drinking Games (MPDG) measure. Using a mixed-methods approach, we tested whether the 7-factor model of the MPDG would emerge among university students from Australia, New Zealand, and Argentina, and whether their open-ended responses regarding their reasons for playing would map onto the MPDG subscales. Students ( N = 895; ages = 18–30 yrs) completed the MPDG-33 measure and an open-ended-question regarding their reasons for playing DGs. We found support for the 7-factor model of the MPDG among students across sites. Open-ended responses revealed that students were motivated to play for a variety of reasons, some of which overlapped with the MPDG subscales while others did not. We present a conceptual model that considers motives specific to alcohol consumption in the context of a DG and reasons/possible motives for playing a DG given its specific features.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it