Drugs and Aggression Readily Mix; So What Now?
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
Intoxicated 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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it