The Impact of Community Violence and an Organization's Procedural Justice Climate on Workplace Aggression
Bibliographic record
Abstract
This study contrasts community violence and an organization's procedural justice climate (or lack thereof) as explanations for employee-instigated workplace aggression in the geographically dispersed plants of a nationwide organization. The findings showed that violent crime rates in the community where a plant resided predicted workplace aggression in that plant, whereas the plant's procedural justice climate did not. Workplace aggression, or behavior committed by employees with the intention of harming those with whom they work or have worked (e.g., Neuman & Baron, 1998), continues to be a significant and prevalent organizational problem. Its effects include lowered productivity, increased employee stress and absenteeism (Braverman, 1993), lawsuits, increased insurance premiums, tarnished reputations (e.g., Atkinson, 2000), reduced customer satisfaction (Walkup, 1999), and costly property damage. Because of workplace aggression, organizations have to bear considerable costs; these were estimated to be $4.2 billion in 1992 (Bensimon, 1994) and to have risen in subsequent years (Laabs, 1999). Not surprisingly, workplace aggression has garnered significant attention in both the popular me-We would like to express our gratitude to Maureen Ambrose and three anonymous reviewers for their insightful comments. We also would like to thank Judi McLean Parks for her comments on earlier versions, and Maura A. Dietz and Nicole N. Nolan for their help in the data collection. The Social Sciences and Humanities Research Council of Canada supported this research with a grant (#410-2002-0637) to the first two authors. A version of this article was published in the 1998 Academy of
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".