Measuring Racial Discrimination Remotely: A Contemporary Review of Unobtrusive Measures

Abstract

Social-science researchers have increasingly moved from conducting their studies in a face-to-face format to an online format. Although new and innovative remote platforms afford researchers generalizability and scale, many of these platforms also tend to solicit socially desirable responses. This pattern of socially desirable responding is evident in examinations of racial discrimination, in which participants are particularly determined to present themselves as ethical and moral. In the current article, we rectify the concern between remote platforms and inauthentic participant responses by reviewing unobtrusive measures of racial discrimination. First, we conceptualize unobtrusive measures as measurements that assess a participant’s discriminatory action without the participant’s knowledge that the specific discriminatory action is under observation. Next, we review the landscape of unobtrusive studies conducted within three broad categories—audit, helping, and friendly interaction—and discuss how these measures have changed over time. Finally, we discuss how to adapt classic face-to-face measures to remote platforms and provide recommendations for implementing unobtrusive measures into remote examinations of discrimination.