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Record W2149622114 · doi:10.1002/ab.20193

Role of motivation to respond to provocation, the social environment, and trait aggression in alcohol‐related aggression

2007· article· en· W2149622114 on OpenAlexafffundabout
Paul F. Tremblay, Ljiljana Mihić, Kathryn Graham, Jennifer Jelley

Bibliographic record

VenueAggressive Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsCentre for Addiction and Mental HealthWestern University
FundersCanadian Institutes of Health Research
KeywordsAggressionPsychologyProvocation testAngerTraitAssertivenessPoison controlSocial psychologyDevelopmental psychologyHuman factors and ergonomicsInjury preventionConformityClinical psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

Little attention has been paid to the motivation to respond to provocation and to the interaction between this motivation, alcohol, the drinking environment, and individual characteristics. Undergraduates at six Canadian universities (N = 1,232) read three vignettes describing conflict situations with social environmental manipulations while imagining themselves as either sober or intoxicated. Self-ratings assessed likelihood of assertive and aggressive responses and motivational indices of anger, offensiveness of the instigator's actions, and importance to respond to the provocation. Respondents also completed a measure of trait aggression. Multi-group structural equation models supported the hypothesis that perceived likelihood of reactive aggression is influenced by perceived alcohol intoxication, gender, trait aggression, social environmental factors, and motivation to respond to the provocation. In addition, a number of interactions were found among the predictors. These results provide insight into the types of factors that may influence aggression in drinking situations.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2007
Admission routes3
Has abstractyes

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