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Overbuilding is all the more of a drag in places like Cleveland or Detroit or Buffalo or Toledo where there is still ample and relatively inexpensive green space to expand into on the outskirts, because every new project saddles the region not only with excess housing and retail capacity but also with the long-term burden of sustaining exponentially more infrastructure. In geographically constrained places, people end up redeveloping underused spaces within the city because there is less blank space outside it to sprawl into.1
PERSISTENT SEGREGATION
When these mobility patterns are layered on top of a legacy of discrimination, we get typical Rust Belt racial and economic segregation. Recently a couple of items have made the rounds of the internet showing the geographic distribution of people by race and income in the U.S. By some of these measures, Cleveland is the most segregated city in the country.2 Notably, a number of the other most segregated cities on that list have similar histories of regional population stagnation or shrinkage since the late 1960s.
Beginning in the 1930s or earlier in Cleveland and many other cities, properties were designated as the lowest investment quality, based, presumably, on age and location. This designation seems to have established a decades-long trajectory. A 2014 Belt feature showed that much of East Cleveland was designated as the lowest, “grade D” property many decades before the notorious years of white flight3 in the 1960s. Those old redlines set in motion a sequence of events that helped define the current segregation of Cleveland: in part because investment in upkeep was discouraged by the low rating, many grade D properties steadily lost value leading up to the 1960s. Wealthier residents moved out and were replaced by people of lesser means. Many of the new residents were renters because banks would not issue mortgages due to the low investment grade. Discriminatory renting, lending, and selling practices prevented black families from moving into any places except for these lowest-grade neighborhoods, which meant that even if a family managed to buy a home, often the property did not increase in value, so little if any wealth was accumulated, resulting in some geographic areas that were disproportionately populated by people with low wealth and dark skin.
By the time black families were able to move relatively freely after the civil rights advances of the 1960s, the region had already entered its post-industrial population decline, which meant there was very little demand pressure for anyone of any race to move into the older, deteriorated neighborhoods. So most of the acres of land that were segregated and low-income fifty years ago have remained segregated and low-income. Meanwhile, the number of people living in those neighborhoods has declined precipitously. The Cleveland neighborhood of Hough claimed 72,000 people and was predominantly black in 1960; by the year 2000 it was still predominantly black but had less than 20,000 residents. (Granted, there is some upbeat news in that downward trend: many of the African Americans who moved out are now a generation or two into a more prosperous life in racially integrated places.)
A fascinating visual data project by the Cooper Center plots the residence location of every single person in the United States, broken down in broad categories by race, and it shows this phenomenon dramatically. Looking at the entire United States, it’s clear that the relatively few people who live in vast, sparsely populated rural areas are overwhelmingly white (with the exception of some rural areas of the Southeast that have more black residents), while all other races are concentrated in urban areas. If you were to draw borders around those large areas where the very few humans are white, and then filled each entire area with a solid color indicating the predominant skin color of the residents, it would appear that the United States is 90 percent white. Many of the geographic segregation maps are drawn this way—this area is white, this area is Asian, this area is black, this area is Hispanic—but it doesn’t show if there are fifty people per acre or one person per square mile. Acres aren’t people. The dot map shows that some areas of greater Cleveland (especially the inner suburbs on both sides of town) are pretty well mixed in race and income, but the amount of land occupied by those places is modest compared to the amount of land occupied by population-depleted inner-city areas and especially the sparsely populated, mostly white outer suburbs and countryside. Because the actual number of people is so few, any influx of diverse population into these geographic areas would quickly change the picture of segregation—however, there has been no influx of anyone into those inner-city neighborhoods for a good sixty years.
SCHOOL RATINGS AS REAL ESTATE MARKETING TOOLS
Another realm in which the dynamics of mobility operate is in our schools and the tools we use to rate them. In Ohio, the primary effect of the state’s student-testing regime has not been to improve educational outcomes, but to encourage migration within regions. The test methodology is designed so that the reports don’t show which districts are making the most difference but rather which ones start off with the highest-achieving students.
The design of a research instrument usually says a lot about the motivations of its designers, and it would appear from this example that the primary purpose of the state report cards is to spur economic development in some places at the expense of other places. Why else would you take the valuable precise individual student test data you have about how James is doing in reading and Jasmine is doing in math and then throw away the value by unscientifically lumping scores together to make contests between communities, unless the primary goal is to get people to desire one community over another? If your motivation were really to help those individual students, you’d use the individual test data to identify which students need what help,
