How Black Are Lakisha and Jamal? Racial Perceptions from Names Used in Correspondence Audit Studies

By S. Michael Gaddis. 2017

294 citations recorded by the source corpus.

Online correspondence audit studies have emerged as the primary method to examine racial discrimination. Although audits use distinctive names to signal race, few studies scientifically examine data regarding the perception of race from names. Different names treated as black or white may be perceived in heterogeneous ways. I conduct a survey experiment that asks respondents to identify the race they associate with a series of names. I alter the first names given to each respondent and inclusion of last names. Names more commonly given by highly educated black mothers (e.g., Jalen and Nia) are less likely to be perceived as black than names given by less educated black mothers (e.g., DaShawn and Tanisha). The results suggest that a large body of social science evidence on racial discrimination operates under a misguided assumption that all black names are alike, and the findings from correspondence audits are likely sensitive to name selection.

Subfields: Artificial Intelligence, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/b6904215e4933476222491402f3d7e5230a2adb0

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In Artificial Intelligence

In Sociology and Political Science

Citations in the corpus

The Role of Protected Class Word Lists in Bias Identification of Contextualized Word Representations (2019, methodology): “In fact, for racial names Gaddis (2017)’s method (using linear regression) can be used to both ﬁlter and pair names.”