Replication Data for: Signaling Race, Ethnicity, and Gender with Names: Challenges and Recommendations

A growing body of research uses names to cue experimental subjects about race, ethnicity, and gender. However, researchers have not explored the myriad of characteristics that might be signaled by these names. In this paper, we introduce a large, publicly available database of the attributes associated with common American first and last names. For 1,000 first names and 21 last names, we provide ratings of perceived race; for 336 first names, we provide ratings on 26 social and personal characteristics. We show that the traits associated with first names vary widely, even among names associated with the same race and gender. Researchers using names to signal group memberships are thus likely cuing a number of other attributes as well. We demonstrate the importance of name selection by replicating DeSante (2013). We conclude by outlining two approaches researchers can use to choose names that successfully cue race (and gender) while minimizing potential confounds.

日益增多的研究以姓名为线索，向实验被试传递种族、族群与性别相关信息。然而，现有研究尚未探究这类姓名可能传递的多元特征。本研究构建了一个大规模公开可用的数据库，收录与美国常见姓名相关的各类属性特征。针对1000个名字（first name）和21个姓氏（last name），我们提供了其感知种族的评分；针对336个名字，则提供了26项社会与个人特征的评分。研究表明，即便同属某一种族与性别的姓名，其所关联的特质也存在显著差异。因此，借助姓名标识群体归属的研究者，实际上也可能同时传递了诸多其他属性特征。我们通过复刻DeSante（2013）的研究，论证了姓名选择的重要性。最后，我们提出了两种可供研究者选用的姓名选择方法，既能有效传递种族（与性别）线索，又能尽可能降低潜在混淆变量的影响。