Bibliographic record
Abstract
Robert O. Pihla* & Rachel Suttonaa Department of Psychology, McGill University, Montreal, Québec, Canada* Correspondence: Robert O. Pihl, Department of Psychology, McGill University, Montreal, Québec, CanadaIntoxicated aggression is both a dangerous and a costly problem for society, with alcohol being involved in over 50% of violent crimes, and the cost of alcohol-consumption-related crime being estimated at $205 billion in the United States alone. First, the authors reviewed the substantial evidence for the connection between alcohol consumption and aggression, and then they examined the risk factors for this problem. These included societal/cultural factors, such as availability and alcohol expectancies, and individual factors, such as demographic characteristics, personality, comorbid disorders, individual differences in response to alcohol, and cognitive functioning. Finally, interventions were suggested focusing on policy, alcohol sellers, treatments for alcohol abuse and dependency, anger management, pharmacology, and low executive functioning. Further efforts are still needed to target interventions to specific risk factors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".