Authors: Tye Rush, Samuel Hall, Matthew Barreto

How are non-citizens counted and accounted for in representation? Section 2 of the Fourteenth Amendment requires that all whole persons residing in a state are to be counted for apportionment and districting. Courts have interpreted Section 2’s requirement to include women (before the Nineteenth Amendment), non-citizens, and people under 18 years old. Yet today, some states are attempting to exclude non-citizens from apportionment and representation by using a citizen population calculus. This stands in contrast to more than 225 years of practice and to nearly all modern legal interpretations of representation. In landmark 1960s cases such as Wesberry v. Sanders and Reynolds v. Sims, the Supreme Court clarified the ideals of equal representation, writing that every district should have the same total population following the decennial apportionment, so that each of the 435 U.S. House districts had almost the exact same total population. As the nation’s immigrant population has increased in the last sixty years, some have argued that only eligible voters should be counted for apportionment, to the exclusion of non-citizens and even children. In 2016, the Supreme Court addressed this question in Evenwel v. Abbott, in which Evenwel challenged Texas’ use of total population and argued instead for the exclusion of non-citizens. The Court upheld Texas’ use of total population. However, it did not go so far as to say that total population is the only population that can be used, thus leaving the door open for states to potentially choose whether to count every individual residing within their borders or to count exclusively adult citizens.

This Essay examines the potential impact of excluding non-citizens in the redistricting process on the composition of districts. We show that, in moving from total population to citizen population, states with large immigrant populations, such as California, Texas, Florida, and New York, would lose Congressional seats. Further, the communities within these states that have a higher concentration of immigrants, many of which are in Los Angeles, San Jose, Houston, Miami, and New York City, would stand to lose seats in their respective state legislatures. It goes without saying that immigrants contribute greatly to their communities, pay taxes, own homes, and have U.S.-born citizen children in school systems, regardless of their own citizenship statuses. As such, immigrants are entitled to political representation as defined in Section 2 of the Fourteenth Amendment, which directs the counting of all whole persons in states. We conclude that using citizen population instead of total population in redistricting and apportionment is inconsistent with U.S. jurisprudence and would result in immigrant communities losing their constitutionally guaranteed representation. We believe the law requires counting the total population and focusing on communities of interest (COI), including immigrant communities, to allow all residents of the United States to be incorporated into the redistricting and line-drawing process to ensure fair representation.

In Thornburg v. Gingles, the Supreme Court provided the elemental test for vote dilution claims under § 2 of the Voting Rights Act. In part, § 2 requires Plaintiffs to prove that voting patterns within the challenged jurisdiction are polarized by race. Because most states do not track the race of voters, social scientists developed statistical methods to make the evidentiary showing required in Gingles. These methods are decades old and are often the subject of intense scrutiny in vote dilution trials. In some cases, the size of the jurisdiction and the quality of the voter file and voting records prevent plaintiffs from meeting their burden of proof. Analyzing the presence of racially polarized voting will be one of the most important issues during and after the 2021−22 redistricting round. Within the last year, an innovative method adapted from other fields of study has been applied to the racially polarized voting analysis in vote dilution cases and has been approved by a federal district court and the Second Circuit: Bayesian Improved Surname Geocoding (BISG). BISG has received little scholarly attention in legal scholarship addressing voting rights yet promises to be the most critical advancement in detecting vote dilution in decades. This Article seeks to showcase this method, equipping voting rights advocates and governments alike in their effort to secure equal voting rights nationwide. This Article argues that BISG should be used by voting rights advocates as an additional method to bolster racially polarized voting analysis conclusions when the necessary data is available and of sufficient quality. Further, BISG should be utilized by governments in jurisdictions with limited access to American Community Survey or decennial census block data to redistrict in compliance with § 2.

Contributors: Matthew Barreto, Michael Cohen, Loren Collingwood, Chad Dunn & Sonni Waknin