IN 1812 the Boston Gazette first used the term gerrymander in response to a set of voting districts devised by Massachusetts Gov. Elbridge Gerry. The Herald suggested that one of the districts looked like a salamander, and so created the (admittedly awkward) portmanteau for the map, calling it the “Gerry-mander.”

Today, gerrymandering has roughly the same meaning as when it was coined: manipulating voting districts to gain an advantage for a party or other group. While most don’t know much about the process of drawing districts, one thing is clear: people hate gerrymandering. A 2019 poll shows that 63 percent of Americans have a negative impression of gerrymandering, while a measly 5 percent view it favorably.

Gerrymandering is as harmful as it is unpopular. We run two projects that provide tools to help people, courts, and legislators understand how and why that is so. The Algorithm-Assisted Redistricting Methodology (ALARM) Project and the Election Law Clinic are housed in Harvard University’s Institute for Quantitative Social Science and Harvard Law School, respectively.

The Election Law Clinic partners with PlanScore to offer visualizations of the partisan biases of redistricting plans. The site includes data from 1972 to 2022 for every state, and allows users to easily see the partisan skews of congressional, state house, and state senate plans.

Take the Massachusetts congressional districts, for example. You might think there’s some advantage for Democrats when the congressional delegation is consistently made up of nine Democrats and zero Republicans. And you’d be right. The efficiency gap (a widely accepted measure of partisan advantage) for the plan was 17 percent in Democrats’ favor in 2022. That means that Democratic voters were disproportionately able to convert their votes into seats, compared to Republican voters. That figure, 17 percent, is also just shy of the biggest pro-Democratic tilt of the last 50 years.

But is the plan really unfair to Republican voters? Or is this degree of bias the natural consequence of the rules and the residential patterns of Democrats and Republicans in Massachusetts? That’s where ALARM comes in. The site relies on a method developed by one of us (Professor Imai) to randomly create thousands of congressional district plans for every state with more than one district. For Massachusetts, ALARM finds that no matter how you draw the lines, the state’s political geography means that you almost always end up with eight or nine Democratic districts.

We can repeat this exercise with Florida (or any other state). According to PlanScore, Florida’s enacted plan exhibited a 5 percent efficiency gap in favor of Republicans in 2022—corresponding to Republicans winning 20 of the state’s 28 congressional districts. Okay, though, is this just a consequence of Democrats clustering in cities and Republicans spreading out across suburban and rural areas (as per the Big Sort)? No. ALARM data shows that when you randomly generate thousands of congressional district plans for Florida, exactly zero of them include 20 Republican districts. The average simulated plan has just 16 Republican districts, four fewer seats than expected under the enacted plan.

Critically, this information isn’t just useful for political junkies. It’s also invaluable for litigants bringing, and courts assessing, partisan gerrymandering claims. PlanScore was originally built using the data from two federal lawsuits seeking to overturn the Wisconsin Assembly and North Carolina Congressional plans as unconstitutionally biased. Although both suits succeeded at trial, the Supreme Court ultimately declared, in 2019, that the doors of federal courts are closed to these claims.

Thankfully, the fight against gerrymandering continues in the states—and benefits from the work of PlanScore and ALARM. PlanScore’s scoring tool has been used to score over 389,000 plans in the 2020 redistricting cycle. The resulting evaluations of maps have been cited by experts, discussed by courts, introduced to redistricting commissions, and covered by journalists. These assessments have shown when proposed plans are highly skewed and should be vigorously opposed. They’ve also revealed when maps are fair and should be commended.

Likewise, one of us (Professor Imai) has used the methodology underlying ALARM as an expert in several cases, including one being argued in the Supreme Court this week. In that case, the technique supports the conclusion that South Carolina’s First Congressional District was racially gerrymandered. That district has an artificially smaller Black population than almost all randomly generated districts in the Charleston area. Outside the litigation context, activists in Ohio relied on the ALARM findings to write a constitutional amendment to end partisan gerrymandering. Signature gathering is now underway and that proposal is likely to be on the ballot in 2024.

This is, we hope, just the beginning. The Election Law Clinic recently teamed up with Ph.D. candidate and ALARM team member Christopher T. Kenny to create RPV Near Me, a tool that provides estimates of racially polarized voting for every county in America. With the Supreme Court having upheld the Voting Rights Act’s protections for communities of color in its Allen v. Milligan decision this summer, RPV Near Me will help countless activists and lawyers to recognize vote dilution, advocate for change, and, if necessary, sue governments to win meaningful representation for people of color in institutions from school boards to Congress.

Though we share just one application of data visualization here—identifying and ridding the country of unfair voting systems—the lesson of our work is a general one. Researchers and experts have done a phenomenal job making big data available to the world, and now it’s time for them to help us visualize what it all means.

Kosuke Imai is professor in the Department of Government and the Department of Statistics at Harvard University. He is also an affiliate of the Institute for Quantitative Social Science and a co-creator of the ALARM Project. Ruth Greenwood is visiting assistant clinical professor and director of the Election Law Clinic at Harvard Law School. She is also a co-creator of PlanScore and RPVNearMe.