Although scholars agree that traditional forms of discrimination have generally been supplanted by subtler interpersonal manifestations of discrimination, it is yet unknown whether targets of these behaviors or the American judicial branch recognize such negative behaviors as violations of extant law. Extending research and theory, we propose that denigrating messages toward women and ethnic minorities (i.e., microaggressions) emerge in workplace interactions and are sometimes interpreted as discrimination. Specifically, this research explores the presence, severity, and frequency of microaggressions that appear in a random sample of race and gender discrimination cases in federal court dockets since the year 2000. The results suggest that microinsults, microinvalidations, and microassaults are reported in a variety of discrimination claims. However, only overt and intentional forms of microaggressions (microassaults) increased the likelihood that decisions favored plaintiffs. Thus, there may be a disconnect between forms of discrimination perceived by claimants and how those forms are evaluated by the legal system that protects victims of discrimination. This potential misalignment of science and practice is discussed, as are directions for future research.
Electronic ré sumé s, online applications, and automated personnel systems have reduced the effort required for a candidate to apply for employment opportunities like selection and promotion. The nature of these systems may affect analyses of adverse impact. For example, candidates that can easily apply to many positions multiple times could strongly influence analyses of adverse impact under particular circumstances. This study demonstrates some potential consequences of including frequent applicants in adverse impact analyses. Using workforce simulation methodology, we illustrate some conditions where a lesser qualified frequent applicant substantially influences the statistical significance of adverse impact detection. In some cases, the adverse impact against a subgroup may be accounted for by a single frequent applicant; in other cases, statistically significant adverse impact may be disguised by a single frequent applicant. We also consider methods for identifying frequent applicants and present options for handling these cases in analyses.
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