Our Mission

The MGGG Redistricting Lab is a research group at Tisch College of Tufts University that grew out of an informal research collective called the Metric Geometry and Gerrymandering Group. The Lab is led by PI Moon Duchin. Our staff has expertise and interests spanning mathematics (geometry, topology, discrete math, dynamics), algorithms, software development, geography, STS, and policy. We research data science interventions for civil rights.

Our goals are these:

• to pursue cutting-edge research in the basic science and practically relevant applications of geometry, topology, and computing to the redistricting problem;
• to build open-source tools and resources that create public access and analytical power for better understanding districts and their consequences;
• to partner with civil rights organizations to reexamine and strengthen the quantitative toolkit for protecting voting rights;
• to offer formal and informal expert consulting to stakeholders on all sides.

Highlights

• Jobs at MGGG

  MGGG

  10 November 2021

  Come join our team! We’re hiring a new Software Developer to rewrite our Districtr web app. Letters of interest are being accepted by email to jobs@mggg.org.

  Read more about the position here.

• 

  Participatory Mapping & Communities of Interest

  MGGG

  01 November 2021

  In 2021, an unprecedented number of states, counties, cities, and other local jurisdictions are considering Communities of Interest, or “COIs,” in the redistricting process. The precise legal definition of a COI varies across the country when it is spelled out at all. Broadly speaking, COIs are geographical areas defined by a residential group with significant shared interests that are relevant to policy and representation. These interests can be cultural, economic, or environmental; they can concern employment or public services or infrastructure—basically, relevant interests include anything that causes neighborhoods or regions to need a shared voice in government. Prioritizing COIs is generally considered to be an essential ingredient of fair redistricting but, in practice, it is prohibitively difficult to do well without local community knowledge.

  This year, MGGG worked to make COI collection easier and more usable than it has been in past redistricting cycles, using our public mapping software called Districtr. This lets us collect spatialized testimony from the public, combining narrative descriptions with the ability to paint community areas using the same kinds of mapping software that will ultimately be used to draw the lines. The team has organized and hosted weekly student-led train-the-trainer sessions throughout 2021 to offer background, tips, and hands-on help with COI mapping.

• 

  Ranked Choice Voting and Minority Representation

  MGGG

  07 October 2021

  In a new preprint, we outline and demonstrate a data-driven methodology that voting rights advocates can use to understand likely impacts of ranked choice voting for securing minority representation in local government. We incorporate both election data and demographics, with variable assumptions on candidate availability and voter turnout. The core of our analysis uses four models of voter ranking behavior that take racial polarization into account; to assess districts, we use random district-generation algorithms developed at the Lab. We focus on the case of STV or “single transferable vote,” where multiple officials are elected from a single district, because this is known to promote proportionality.

The MGGG Redistricting Lab is a nonpartisan research organization. MGGG has major support from the Jonathan M. Tisch College of Civic Life at Tufts University and the Amar G. Bose Research Grant Program at MIT and an active partnership with the Lawyers' Committee for Civil Rights Under Law.