Which Congressional Districts are Over and Under Populated
The foundation of the U.S. democratic system is based on fair representation of its residents. The story of representation is complicated, hard-fought, and still evolving. Currently, representation through the 435 Congressional districts is decided in elections every two years but districts are redrawn every ten years after the decennial Census is conducted. Districts are drawn by states to have an exactly equal, or as close as possible, number of people within the boundaries of each. That population is determined from dividing the state’s population by the number of districts, producing a number sometimes called the target or ideal population.
But population constantly shifts and changes in between when districts are redrawn, causing some districts to be what we’ll call “over” or “under” populated. Overpopulated districts have grown faster than the state as a whole and have more people than ideal. Underpopulated districts have grown slower than the state, or even declined in population, and thus have fewer people than the ideal population for fair representation.
Over and underpopulated
Using the latest U.S. Census Bureau estimates, we mapped the over-and-under population of Congressional representation across the country. For each state, we calculated the target population (state’s population divided by the number of districts). We styled the districts by the percentage over or underpopulated. Click on a district for more information about it in relation to each district in its state.
What it tells us about representation
How equal are Congressional districts supposed to be? Exactly equal, if possible, with only as much as one person deviation among districts, ever since Vieth v Jubelirer in 2004. This is, of course, an unmaintainable standard in between decades, as the population has changed even before the districts go into effect. Even when districts are redrawn mid-decade, such as recently in North Carolina, they are instructed to use the 2010 population data.
Nevertheless, it can be an interesting exercise to look at representation of the most over and underpopulated districts.
Most overpopulated districts
As it turns out, the 10 most over and underpopulated districts are represented evenly by Republicans and Democrats.
The 22nd Congressional District in Texas, the most overpopulated, is a rapidly diversifying area sprawling south of Houston. Donald Trump won this district by eight points in 2016, down from Mitt Romney’s substantially larger 25 point win in 2012. The district is represented by Republican Pete Olson, who announced last year that he is retiring at the end of his term.
Most underpopulated districts
The 10 most underpopulated districts are also represented evenly by Democrats and Republicans.
The most underpopulated district is the sprawling 13th district covering much of northern Texas. Because of rapid population growth elsewhere in the state, this district is underpopulated by over 8%. The district is currently represented by Republican Mac Thornberry.
What this map doesn’t show
Congressional representation is reapportioned every ten years. We wrote about this last year. Some states, like Texas, are expected to gain Congressional representation and therefore districts after reapportionment. Unlike states that will have the same number of districts before and after, redistricting may not necessarily shrink those overpopulated districts. That’s because the state’s target population for districts will be adjusted to take into account a greater number of districts. There, you will see additional districts added — likely in high population growth areas.
Find the right Congressional district
On the Cicero team, we are constantly tracking updates and changes to the electoral map. When new districts are drawn, we update our database to ensure that every client has access to the most up-to-date data on election districts. Check out our data here or contact our team for more information.
Originally published at https://www.azavea.com on July 29, 2020.
