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Record W4402609073 · doi:10.1017/jmo.2024.20

Applying a person-oriented approach to workplace aggression: Implications for employee emotional well-being

2024· article· en· W4402609073 on OpenAlex
Hamsa Gururaj, Aaron C. H. Schat

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 Management & Organization · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsMcMaster UniversityBishop's University
Fundersnot available
KeywordsAggressionPsychologySocial psychologyEmotional laborApplied psychology

Abstract

fetched live from OpenAlex

Abstract Using a person-oriented approach with a broad sample of 200 employees across several sectors, we identified four victim subgroups sharing similar configurations of frequency and severity of aggression: high–high (high levels of frequency and severity; 15%), moderate–moderate (moderate levels of frequency and severity; 15%), high–low (high frequency but low severity; 26.5%), and low–low (lowest levels of frequency and severity; 43%). Further, we examined the relationship between victim groups, social demographics, and victim disposition. The results showed that women, young, and lower-tenured employees are at risk of belonging to the high–high victim group. In addition, employees with high negative affect and psychopathy traits are at risk of belonging to the high–high victim group. Drawing upon learned helplessness theory, we examined whether victim groups differed concerning internalizing problems. Results suggest that high–high group victims experienced the highest anxiety, loss of confidence, and social dysfunction, whereas low–low group members experienced the lowest levels.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.019
GPT teacher head0.294
Teacher spread0.275 · 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