The Brief Aggression Questionnaire: Structure, Validity, Reliability, and Generalizability
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
In contexts that increasingly demand brief self-report measures (e.g., experience sampling, longitudinal and field studies), researchers seek succinct surveys that maintain reliability and validity. One such measure is the 12-item Brief Aggression Questionnaire (BAQ; Webster et al., 2014), which uses 4 3-item subscales: Physical Aggression, Verbal Aggression, Anger, and Hostility. Although prior work suggests the BAQ's scores are reliable and valid, we addressed some lingering concerns. Across 3 studies (N = 1,279), we found that the BAQ had a 4-factor structure, possessed long-term test-retest reliability across 12 weeks, predicted differences in behavioral aggression over time in a laboratory experiment, generalized to a diverse nonstudent sample, and showed convergent validity with a displaced aggression measure. In addition, the BAQ's 3-item Anger subscale showed convergent validity with a trait anger measure. We discuss the BAQ's potential reliability, validity, limitations, and uses as an efficient measure of aggressive traits.
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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 | 0.004 | 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 | 0.000 | 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