The Company They Keep: Drinking Group Attitudes and Male Bar Aggression
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to assess (a) similarities in self-reported bar-aggression-related attitudes and behaviors among members of young male groups recruited on their way to bars and (b) group-level variables associated with individual members' self-reported likelihood of perpetrating physical bar aggression in the past year, controlling for individual attitudes. METHOD: Young, male, natural drinking groups recruited on their way to a bar district Thursday, Friday, and Saturday nights (n = 167, 53 groups) completed an online survey that measured whether they had perpetrated physical aggression at a bar in the past year and constructs associated with bar aggression, including attitudes toward male bar aggression and frequency of heavy episodic drinking in the past year. RESULTS: Intraclass correlations and chi-square tests demonstrated significant within-group similarity on bar-aggression-related attitudes and behaviors (ps < .01). Hierarchical linear modeling revealed that group attitudes toward bar aggression were significantly associated with individuals' likelihood of perpetrating physical bar aggression, controlling for individual attitudes (p < .01); however, the link between group heavy episodic drinking and self-reported bar aggression was nonsignificant in the full model. CONCLUSIONS: This study suggests that the most important group influence on young men's bar aggression is the attitudes of other group members. These attitudes were associated with group members' likelihood of engaging in bar aggression over and above individuals' own attitudes. A better understanding of how group attitudes and behavior affect the behavior of individual group members is needed to inform aggression-prevention programming.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".