Current Projects
Our Model: the Vote Maximizer
Vote Maximizer is an app for democracy preservation that brings attention to critical races nationwide. Using rigorous mathematical analysis, this project is designed to maximize a single person’s political leverage. Check out the full project:
What else are we doing?
With the recent Moore v. Harper ruling, the U.S. Supreme Court has secured a state’s ability to limit partisan manipulation of congressional maps. This defense of democracy encourages ongoing reform efforts at the state level. We are seeing this play out throughout the nation; and in fact, EIL released a report to guide efforts underway in Ohio to form an independent, citizen-led, nonpartisan redistricting commission: A Citizen’s Guide to Redistricting in Ohio.
With the continued failure to pass a federal voting rights bill, the battle for democracy is in the states. We can help them.
Yet, fair representation is not just about maps - if we do the work, we can provide more analytical data to answer questions about whether alternative voting methods help realize goals towards fair and meaningful representation. In cities, counties, and states, advocates are looking for ways to encourage more eligible candidates to run for office and diversify the pool of candidates. EIL can explore voter-centric methods to promote increased engagement by voters seeking to cast ballots for a wider slate of candidates more reflective of their communities.
One of EIL’s priority projects is an analysis of past ranked-choice elections which will inform the generation of a model to calculate the outcomes of various voting rules (first-past-the-post, ranked-choice, Top Four, approval) in future elections. We will focus on state-specific optimization of voting reform by exploring these questions:
● Which reforms make sense in different states?
● How do local factors shape dynamics and incentives?
● Which reforms are attainable and help communities achieve improved representation?
● How do different reforms synergize with or cancel one another?
We are preparing for opportunities for democracy reform with the release of 2030 census data.
The U.S. Census Bureau provides the 50 states, the District of Columbia, and Puerto Rico with population counts to use in their redrawing of congressional and state legislative district boundaries—along with tens of thousands of other jurisdictions—a process known as “redistricting".
The first marquee project of EIL, the Princeton Gerrymandering Project (PGP), became a key resource for advocacy groups, nonprofit organizations, legislative commissions, judicial representatives, journalists, and the public. PGP data and analytics helped inform advocacy strategies to achieve fair representation through nonpartisan redistricting efforts in multiple states. The number of gerrymandered Congressional and legislative districts dropped sharply during the current decade compared with 2012, thanks to independent commissions (Michigan, Colorado), court cases (Pennsylvania, New York, Connecticut, Maryland), and public input (New York, Virginia).
With the 2020 redistricting cycle complete, PGP generated data, work products, and scoring of redistricting plans is being updated and will remain as a public resource at gerrymander.princeton.edu/. A new website allowing for more functionality is being planned in time for the 2030 census cycle and district map drafting.
One of EIL's 2023 projects is a multistate review of redistricting commissions. We will review the outcome of the last decade’s reforms in Virginia, Colorado, Ohio, Michigan, and other states, all of which implemented slightly different reforms.
We will expand on this work by integrating our findings with a given state's constitution, laws, and political environment, so we can help identify parameters for attainable reform. We will analyze the likely outcomes of hypothetical reforms, including demonstration maps, keeping the following factors in mind:
● mechanisms must be crafted to promote effective models of nonpartisan commissions, clear fairness standards, and means of resolving disputes;
● concerns from specific interest groups must be addressed; and
● advocates must trust and learn to use data and analytics to further their goals.