No abstract

No abstract

No abstract

nities for people of color (Richeson 2015). More recent examples inlcude opposing police brutality and supporting the Black Lives Matter movement (Arora, Stout, and Kretschmer 2020). As Jennifer Richeson (2015) succinctly puts it, "it is when groups come together that real change becomes possible."Although a significant number of studies have considered the prospects for coalition building between African Americans and Latinos (Jones-Correa 2011; Kaufman 2003; Mc-Unpacking Identity: Opportunities and Constraints for Cross-Racial Collaboration m a neesh a ror a, sa r a sa dh Wa ni, a nd sono sh a hWe argue that two factors are important for cross-racial coalition building: policy convergence in key issue arenas and perceived interest alignment with other racial groups. Drawing on the 2016 National Asian American Survey, we examine two of the most salient issues Asian Americans consistently rate as among the most important: immigration and economic policy. Using principal component analysis, we plot mean scores by group to analyze national-origin clustering along these two dimensions. Next, we analyze national-origin differences in perceived interest alignment with Blacks and Latinos. Combining these two factors, we identify clusters of groups that have a strong potential for cross-racial coalition building and that face greater constraints. In sum, we propose a theoretical framework for understanding cross-racial coalition building that includes disaggregating Asian Americans by national origin, and then identify which national-origin groups have the greater opportunity to form such coalitions.

The adoption of the top two primary system in California is resulting in a rising number of general elections in which candidates from the same party compete. Incidentally, California is also home to a large and diverse Latino community. When party identification is no longer a reliable cue, do Latino voters turn to the race or ethnicity of a candidate in selecting whom to support? We examine co-partisan Republican general elections in California's state assembly from 2012-2016. Using surname-matched precinct-level voter data, we conduct ecological inference analysis to estimate support for candidates based on the ethnicity of voters. Taking the case of Latino voters, we find a strong level of support for Latino Republican candidates, suggesting that a candidate's ethnicity may inform voters' strategic decision making in partisan elections.

No abstract

No abstract

Do undocumented immigrants matter as constituents for state legislators? In this study we examine legislator responsiveness to differing ethnicities and immigration statuses of immigrant constituents through a field experiment conducted in 2014 in 44 U.S. state legislatures. We advance a theory of citizen advantage, that citizens and particularly white citizens will reap greater representation from legislators, but that even undocumented immigrants can constitute a meaningful subconstituency that receives some, albeit less, responsiveness from legislators. Each legislator received a constituent request that was identical in content and varied the constituent’s race/ethnic identity by using a first name and surname cue (Latinx or Eastern European) and immigration status (undocumented/citizen/control). We found that legislators respond less to undocumented constituents regardless of their ethnicity and are more responsive to both the Latinx and Eastern European-origin citizen treatments, with Republicans being more biased in their responsiveness to undocumented residents. Nuances within the data reveal that despite limited electoral incentive, some legislators are responsive to undocumented immigrants regardless of race or ethnicity; however, when immigration status is not cued, white residents receive greater responsiveness than Latinx.