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Submerged for Some? Government Visibility, Race, and American Political Trust

Published online by Cambridge University Press:  14 July 2020

Abstract

Scholarship concerning American government visibility has focused on the state’s growing submergence, yet these accounts contrast with racial and ethnic politics research focusing on the American state’s conspicuousness in the lives of people of color. Attending to this disconnect, I ask how government visibility varies across racial groups. Combining interviews and quantitative analysis within a policy feedback framework, I argue that five public policy trends have created a racial split in the American state’s visibility. For whites, submerged state policies have grown alongside the rising visibility of racialized poverty policies and taxation. As a result, whites are less aware of how government benefits them and more aware of how government uses tax dollars to fund programs perceived as solely benefitting racial others. For people of color, the decline of civil rights legislation has contrasted with criminal legal policies that have made the criminal legal system a uniquely visible manifestation of government in their lives. To demonstrate the political importance of this racial divide, I uncover a racial heterogeneity in people’s political trust attachments, wherein white trust is connected to welfare attitudes, while trust among people of color is associated with feelings about the police.

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© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association

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Footnotes

A list of permanent links to Supplemental Materials provided by the authors precedes the References section.

*

Data replication sets are available in Harvard Dataverse at: https://doi.org/10.7910/DVN/FXEJW

He thanks the audience, fellow panelists, and discussant at the 2019 Annual Meeting of the American Political Science Association for their insightful comments on earlier versions of this paper. He is also grateful for Michael Bernhard’s editorial guidance, as well as the four anonymous reviewers who significantly improved this article. Finally, thanks to Florencia Montal, Joe Soss, Andrew Karch, and Sarah Bruch for their help in developing this paper.

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