There Goes the Neighborhood - Map Predicts How Neighborhoods Racial Makeup Will Change
Author: University of Cincinnati
Published: 2022/07/14 - Updated: 2023/01/04
Peer Reviewed Publication: Yes
Topic: Offbeat News - Publications List
Page Content: Synopsis - Introduction - Main
Synopsis: Machine-learning models for spatially-explicit forecasting of future racial segregation in American cities. The predictive maps could help schools or governments plan for more services such as Spanish-speaking classrooms or interpreters. It also could help sociologists understand the driving forces behind the changing demographics of neighborhoods.
Introduction
A map created by researchers at the University of Cincinnati can predict how the racial makeup of neighborhoods will change with surprising accuracy.
Main Item
UC College of Arts and Sciences geography professor Tomasz Stepinski created a machine-learning algorithm to predict how neighborhoods will become more or less segregated in the next ten years.
Stepinski, who works in UC's Space Research Institute for Discovery and Exploration, analyzed data collected by the U.S. Census Bureau every decade. They mapped the data by racial composition in the high resolution of 300-meter squares called cells.
The algorithm had to be "trained" to interpret the data from two census years spaced ten years apart. The algorithm also examined individual cells about those around them.
"The name 'machine learning' suggests something magical about it, but it's just more powerful statistics," Stepinski said.
Stepinski validated his algorithm by comparing its predictions to actual data from the 2010 and 2020 censuses and found it was up to 86% accurate.
"Our hypothesis that you can predict the class of a cell in 10 years based on the previous two classes and surrounding classes was correct," he said. "It's not perfect, but you can see it's pretty good."
Stepinski and co-author Anna Dmowska, an assistant professor in the Department of Geoinformation at Adam Mickiewicz University in Poland, applied their algorithm to Chicago's Cook County, Illinois, at one time considered one of the most racially segregated places in America.
UC's map showed that many neighborhoods dominated by white and Black populations will become less segregated by 2030, with less noticeable changes in neighborhoods dominated by Hispanic and Asian American populations.
Stepinski said researchers in Chicago had conducted pioneering sociological research on race, ethnicity, and gentrification using Cook County as their model. The sprawling, heavily populated county also provides a good model to study the algorithm because it still has many segregated neighborhoods despite trending toward greater racial and ethnic diversity over the last 50 years, he said.
Stepinski also applied the algorithm to Houston, Texas, Los Angeles, and San Francisco in California with similar success.
"The ability to predict demographic changes is essential from a scientific point of view and for policymakers, city development, etc.," co-author Dmowska said.
"As shown in the paper, the predictive maps are pretty accurate and show how the area might look in the next ten years," she said.
Stepinski said the predictive maps could help schools or governments plan for more services such as Spanish-speaking classrooms or interpreters. It also could help sociologists understand the driving forces behind the changing demographics of neighborhoods.
"My interest is not sociological. My specialty is computation," Stepinski said. "I leave the why to someone else. But I can imagine what's happening."
Stepinski said younger generations are often likely to remain in nearby neighborhoods if they remain in an area at all. And if one particular racial population declines in an area, others typically fill the void.
"It's diffusion," Stepinski said. "So in Cook County, a Hispanic population grows faster than the white population. They're going to move close by. They're not going to move far from home."
Michael Chavarria, executive director of the nonprofit HOPE Fair Housing Center in Illinois, said he was surprised by the map's predictive accuracy.
"One compelling thing it does is affirm the narrative that people don't have as much control over where they live as decision-makers think they do," he said.
"People think segregation is the result of individual choices. And some people might choose to live in places where everyone looks like them," Chavarria said. "But the idea that an algorithm can predict where people live shows that other factors control these decisions. That tells me that the choice about where we live isn't rooted in the full agency."
In Cook County's case, Chavarria said the predictive map's snapshot view might suggest that some neighborhoods in Cook County are becoming less segregated. But it might also merely capture the transition from one type of segregated neighborhood to another just as segregated.
"Seeing these neighborhoods change could just be a precursor to more segregation," Chavarria said.
Olivia Cobbins, an investigator with the Cook County Human Rights Commission, said it's important to examine racial segregation in the context of issues such as housing discrimination or public services.
"Chicago has a history of racial discrimination, redlining, and inequalities towards African Americans," she said.
Cobbins said policies and laws must keep up with changing demographics to ensure equal opportunities for everyone.
"Public officials and society have a moral responsibility and obligation to provide justice, equality, and equity and to ensure public assistance and decent, affordable housing is available to those in need."
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Attribution/Source(s): This peer reviewed publication was selected for publishing by the editors of Disabled World (DW) due to its relevance to the disability community. Originally authored by University of Cincinnati and published on 2022/07/14, this content may have been edited for style, clarity, or brevity. For further details or clarifications, University of Cincinnati can be contacted at uc.edu NOTE: Disabled World does not provide any warranties or endorsements related to this article.