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Saturday, June 10 • 10:20am - 10:40am
Wikipedia’s Race and Ethnicity Gap and the Unverifiability of Whiteness

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Although Wikipedia has a widely studied gender gap, almost no research has attempted to discover if it has a comparable race and ethnicity gap among its editors or its articles. In this paper I articulate the reasons for this quantitative aporia: No such comprehensive analysis of Wikipedia’s editors exists because legal, cultural, and social structures complicate surveying them about race and ethnicity. Nor is it possible to precisely measure how many of Wikipedia’s biographies are about people from indigenous and nondominant ethnic groups, because most articles lack ethnicity information. (I use the provisional term "indigenous and nondominant ethnic groups" to describe the related phenomena of race, ethnicity, caste and nationality on a global scale.) While it seems that many of these uncategorized biographies are about white people, these biographies are not categorized by ethnicity because Wikipedia policies require citations to reliable sources to verify such categorization; this verification process is central to Wikipedia's epistemology. These sources do not exist for white people because whiteness is a social construct that has historically been treated as a transparent default. Thus, these biographies cannot be categorized as white because whiteness is unverifiable in Wikipedia’s white epistemology. In the absence of a precise analysis of the gaps in its editors or its articles, I present a quantitative and qualitative analysis of these structures that prevent such an analysis. I examine policy discussions about categorization by race and ethnicity, which demonstrate persistent anti-Black racism. Turning to Wikidata, I reveal how the ontology of whiteness shifts as it enters the database, functioning differently than existing theories of whiteness account for. Existing theories describe a transparency function, where where whiteness is the normalized default, and goes without mentioning. Thus in legal or semiotic contexts, people are white as long as they are not described as nonwhite. In the database, in contrast, because data requires affirmative assignment—a database cannot assign a value of a double negative—the transparency function behaves differently. While the data does point toward a significant race and ethnicity gap, the data cannot definitively reveal meaning beyond its inability to reveal quantitative meaning. Yet the unverifiability of whiteness is itself an undeniable verification of Wikipedia’s whiteness.


Michael Mandiberg

Professor, CUNY Graduate Center and College of Staten Island

Saturday June 10, 2023 10:20am - 10:40am EDT
PS 401 (Design Center)