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Predicting Workplace Aggression and Violence

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Other designConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.966
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.042
GPT teacher head0.439
Teacher spread
0.397 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

Consistent with the relative recency of research on workplace aggression and the considerable media attention given to high-profile incidents, numerous myths about the nature of workplace aggression have emerged. In this review, we examine these myths from an evidence-based perspective, bringing greater clarity to our understanding of the predictors of workplace aggression. We conclude by pointing to the need for more research focusing on construct validity and prevention issues as well as for methodologies that minimize the likelihood of mono-method bias and that strengthen the ability to make causal inferences.

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.

The record

Venue
Annual Review of Psychology
Topic
Workplace Violence and Bullying
Field
Social Sciences
Canadian institutions
Saint Mary's UniversityMemorial University of NewfoundlandQueen's University
Funders
not available
Keywords
AggressionPsychologyCLARITYPerspective (graphical)Construct (python library)Social psychologyPoison controlHuman factors and ergonomicsMythologyApplied psychologyMedical emergency
Has abstract in OpenAlex
yes