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Record W2271831877 · doi:10.1080/00223891.2015.1044093

The Brief Aggression Questionnaire: Structure, Validity, Reliability, and Generalizability

2015· article· en· W2271831877 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Personality Assessment · 2015
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyHostilityAggressionAngerGeneralizability theoryConvergent validityReliability (semiconductor)Test validityPoison controlClinical psychologyIncremental validityPsychometricsSocial psychologyDevelopmental psychologyInternal consistency

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.370
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it