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.

社会科学研究人员越来越多地从面对面的形式转向在线形式的研究。尽管新的和创新的远程平台为研究人员提供了普遍性和规模，但其中许多平台也倾向于征求社会期望的响应。这种社会合意的回应模式在种族歧视的考试中很明显，在这些考试中，参与者特别决心将自己呈现为道德和道德的。在当前的文章中，我们通过审查种族歧视的不引人注目的措施来纠正远程平台和不真实的参与者反应之间的担忧。第一的，我们将不显眼的措施概念化为在参与者不知道具体歧视行为正在观察中的情况下评估参与者的歧视行为的度量。接下来，我们回顾了在审计、帮助和友好互动三大类别中进行的不引人注目的研究，并讨论了这些措施如何随着时间的推移而发生变化。最后，我们讨论了如何将经典的面对面措施应用于远程平台，并为在远程歧视检查中实施不显眼的措施提供建议。