This research applies a scientific framework to examine the effects of actions that male workers direct toward female coworkers on judgments of harassment, emotional reactions, and work performance for people who experience the action (e.g., potential complainants). In addition, it tests differences between those who experience the alleged harassment, those who observe the alleged harassment (e.g., co-workers and witnesses), and those who predict the potential impact of the action from indirect evidence of it (e.g., judges and juries). Preliminary work by the PIs has shown that predictors expect those who experience the action to report more harassment, more negative emotions, and more performance decrements than experiencers of actions actually report. The research relies on a model of legal decision-making to better understand the influence of interpersonal interaction, affective forecasting, and the roles of pervasiveness and severity of the misconduct. Specifically, the research addresses: 1) How severe or pervasive must misconduct be to trigger reactions among complainants, witnesses, and judges and juries to satisfy the legal requirements of hostile work environment harassment? 2) Do different levels of experienced and anticipated emotion explain these reactions? And, 3) what are the differences in reactions between potential complainants, witnesses, and juries/judges? To examine these questions, the PIs will conduct a coordinated set of 3 experimental studies in which student and community participants experience, observe, and predict the impact of actions, which vary in severity and pervasiveness, to test the effects on harassment judgments, emotions, and work performance.

This work has the potential to generate new knowledge with theoretical and practical significance. The findings will explain how certain forms of interpersonal interaction affect harassment perceptions, emotions, and work performance from the perspectives of complainants, potential witness, and judges, jurors, and mediators. It also provides a model and potential intervention to explain and reduce the differences between these entities.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Marjorie Zatz
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University of Nebraska-Lincoln
United States
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