Applying a person-oriented approach to workplace aggression: Implications for employee emotional well-being
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".