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What Is Extreme Gerrymandering?

Understanding how extreme partisan gerrymandering works.

Figure 1:  Tisdale, Elka­nah. “The Gerry-Mander,” Boston Gazette, March 26, 1812.

What is extreme gerry­man­der­ing?

Gerry­man­der­ing describes the inten­tional manip­u­la­tion of district bound­ar­ies to discrim­in­ate against a group of voters on the basis of their polit­ical views or race.

The term dates to 1812 when Massachu­setts Governor Elbridge Gerry signed into law a redis­trict­ing plan that included a district many thought looked like a sala­man­der, lead­ing oppon­ents to nick­name the district after him. 

But while the term has become a synonym for redis­trict­ing abuses, it actu­ally covers a wide vari­ety of sins, not all of which are related.

For example, one form of gerry­man­der­ing involves draw­ing districts in order to protect incum­bents. Like­wise, some­times districts are drawn to ensure a favored candid­ate can success­fully run for office. These types of gerry­manders – which often occur through bipar­tisan collu­sion between polit­ical parties – can be harm­ful to demo­cracy by pre-determ­in­ing outcomes and depriving voters of a mean­ing­ful choice at the polls.

But the partisan gerry­man­der­ing cases currently in front of the Supreme Court – Rucho v. Common Cause, Rucho v. League of Women Voters of North Caro­lina, and Lamone v. Benisek involve another vari­ant of polit­ical gerry­man­der­ing that is even more perni­cious.

In the type of extreme partisan gerry­man­der­ing being chal­lenged in North Caro­lina and Mary­land, a polit­ical party uses its control of the process to artfully craft maps that lock in an outsized share of seats for an entire decade. The last­ing and harm­ful effects of extreme partisan gerry­man­der­ing are espe­cially appar­ent in tradi­tion­ally purple states, like North Caro­lina. At a statewide level, North Caro­lina is a robust demo­cracy with highly contested elec­tions for everything from pres­id­ent to state auditor. But over the last decade, Repub­lic­ans secured super­ma­jor­it­ies in the state legis­lature, as well as a safe, durable 10–3 advant­age in the congres­sional deleg­a­tion.

Extreme partisan gerry­manders not only bake in results, but also result in maps that are deeply unrep­res­ent­at­ive. John Adams famously wrote in 1788 that the House of Repres­ent­at­ives – and by exten­sion state legis­latures – should be a “exact portrait” and “mini­ature” of the people as a whole. That does­n’t happen when district bound­ar­ies are manip­u­lated in this way.

How does extreme gerry­man­der­ing work? 

People often asso­ci­ate gerry­man­der­ing with the creation of super-safe districts that a party wins by over­whelm­ingly large margins. But, in fact, making districts too safe makes it hard to do an extreme gerry­mander. Rather, the goal of a party seek­ing to use an extreme gerry­mander to grab a dispro­por­tion­ate share of seats is to spread its support­ers out among districts, letting it win a larger number of seats.

To illus­trate how this works, consider a simpli­fied hypo­thet­ical state with four districts and slightly more Demo­crats than Repub­lic­ans. You could draw the districts in such a way that the parties split the seats

But, altern­at­ively, you also could draw the districts in a way that Demo­crats end up with all four seats – essen­tially trad­ing super-safe districts for more seats.

Of course, there is a danger for gerry­man­der­ers. The trick is not to spread your voters out so much that districts become vulner­able to flip­ping to the other party in the normal give and take of elect­oral polit­ics.

Fortu­nately for gerry­man­der­ers – and unfor­tu­nately for the rest of us – this is becom­ing easier to do with “Big Data” and advance­ments in tech­no­logy. And when gerry­man­der­ers succeed, they create the worst of all worlds – a map that both is uncom­pet­it­ive and skewed in favor of one party.

How can you tell when a map is an extreme gerry­mander?

Although people often focus on indi­vidual districts when they talk about partisan gerry­man­der­ing, the extreme gerry­man­der­ing being chal­lenged in North Caro­lina and Mary­land also involves look­ing at the map as a whole to gauge whether a map results in an unfair alloc­a­tion of seats between parties.

Math­em­at­ical and stat­ist­ical meas­ures can be power­ful diagnostic tools that can help courts identify when a partic­u­lar distri­bu­tion of seats is stat­ist­ic­ally unlikely to be random – or at least when a map needs to be looked at more closely. Computer simu­la­tions that create hundreds and even thou­sands of random maps also can help point to situ­ations where some­thing is likely amiss.

But stat­ist­ical bias is not the end of the inquiry.

Courts can also look to other types of evid­ence – includ­ing legis­lat­ive mater­i­als, floor state­ments by lawmakers, and emails – to help determ­ine whether or not maps have been drawn in a way that can’t be explained by neut­ral consid­er­a­tions.

Like­wise, a state whose map is being chal­lenged can present evid­ence to show that the bias in a map was due to things other than the intent to maxim­ize partisan advant­age.

Does­n’t the fact that Demo­crats are concen­trated in cities explain why Repub­lic­ans get more seats?

No. It’s true that big cities like New York and Los Angeles are heav­ily Demo­cratic. And it’s true that resid­en­tial patterns – or so-called clus­ter­ing – may have some impact on the number of seats each party has. But there still are plenty of oppor­tun­it­ies to gerry­mander in areas outside big cities. In fact, Prin­ceton professor Sam Wang shows how easily this is possible when there are signi­fic­ant pock­ets of both parties outside the big cities if there is a relat­ively even spread of partis­ans in those areas:

Fixed dots

Figure 2: Sam Wang (@Sam­Wang­PhD). 2017. “This popu­la­tion can give a 5–1 split…or 4–2 the oppos­ite way…all w/nice bound­ar­ies. Need more than maps to solve.” Twit­ter, August 25, 2017, 1:53pm.https://twit­­PhD/status/901155535541723137.

In fact, it’s notable that extreme gerry­manders occur not in deeply red or deeply blue states but in battle­ground states like Wiscon­sin, Michigan, North Caro­lina, and Pennsylvania, that aren’t starkly clustered but that just happened to be controlled by a single party at the time of redis­trict­ing. To be sure, the cities in those states are fairly to heav­ily Demo­cratic, but, as a precinct level map will show, these battle­ground states also have a lot of Demo­crats in suburbs, college towns, and rural areas. Given this compar­at­ively even spread of Repub­lic­ans and Demo­crats, it abso­lutely matters how you draw districts. Draw a district head­ing one direc­tion, you end up with a Demo­cratic or at least a compet­it­ive district. Draw it in the other direc­tion, and you have two safe R seats. 

A great real-world example is in Cumber­land County, North Caro­lina, where the city of Fayetteville currently is split between two congres­sional districts.

Figure 3: Supple­mental Declar­a­tion of Jowei Chen, 3, League of Women Voters of North Caro­lina v. Rucho, No. 16-cv-01164 (M.D.N.C. July 11, 2018). 

If Fayetteville had not been split in this way, it may have been possible to have a compet­it­ive district for Demo­crats in the area, in part, due to a nearby cluster of Demo­cratic voters in Hoke and Robe­son Counties.



Figure 4: Supple­mental Declar­a­tion of Jowei Chen, 2, League of Women Voters of North Caro­lina v. Ruch, No.16-cv-01164 (M.D.N.C. July 11, 2018). 

And in the Midwest­ern battle­ground states, like Wiscon­sin and Michigan, the geography is even more favor­able for creat­ing Demo­cratic, or at least highly compet­it­ive, districts. (It would be differ­ent if every census block outside of the big cities were uniformly, say, 56% / 44% Repub­lican over Demo­crat, but that isn’t the case.)

One final point: It’s telling that the prob­lem of high partisan bias is closely correl­ated with single-party control of the redis­trict­ing process. Contrast that with states that where commis­sions, split control legis­latures, and courts draw maps, which have much lower – and much less durable – levels of bias. Cali­for­nia had high levels of bias in the 1990s when Demo­crats controlled draw­ing of the maps. It has negli­gible levels today.