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Posted: October 3rd, 2023

Segregation by race and ethnicity remains a pressing issue in many U.S. cities

In this discussion board, you are going to use the tools and concepts that were introduced in the module to both describe and analyze current patterns and historical trends of segregation in U.S. cities. Please read and follow the instructions below carefully:

For your initial post: Your first step will be to choose a city you want to analyze. You can choose any city EXCEPT for Milwaukee, WI, and Raleigh, NC, which I used as examples in the lecture. Also, DO NOT use any city in the South Florida Metro Area (which runs from Miami to West Palm Beach), as we will be focusing on this area for the second memo assignment.

Second, open the Diversity and Disparities Segregation Data ToolLinks to an external site., and find the city you want to examine. (Note: You may use either city-level or metropolitan-level data, but make sure to clearly state which you are using in your post). Using this data tool, you will present the following information in your description:

A) Using the general data on Ethnic and Racial Composition: What are the three largest ethno-racial groups in the city currently? What percent of the population did each group represent in 2020? How has the ethno-racial composition of the city changed since 1980? Did the city become more diverse? Less diverse? Remain stable? Use specific data to support your description of any change.

B) Using the Black-White dissimilarity index, describe the extent to which Black and White residents of the city lived in separate neighborhoods in 2020. Also, describe the historical trend: Have Black and White residents become more or less segregated since 1980? In your description, make sure to provide both numerical scores on the index (from 0-100), and explain what those scores mean.

C) Using the Black Isolation index, describe the extent to which Black residents of the city are concentrated in particular neighborhoods of the city in 2020. Also, describe the historical trend: Have Black residents become more or less isolated since 1980? In your description, make sure to provide both numerical scores on the index (from 0-100), and explain what those scores mean.

Segregation by race and ethnicity remains a pressing issue in many U.S. cities. While legal segregation has ended, residential patterns still show separation along racial lines in places. This paper will analyze current and historical trends of segregation in Columbus, Ohio using data from the Diversity and Disparities Segregation Data Tool (Logan et al., 2020). Specifically, it will examine the ethnic and racial composition of Columbus, the extent of Black-White segregation, and levels of Black isolation. Overall, the analysis shows Columbus has become more diverse but still exhibits signs of moderate segregation and racial concentration among Black residents.
Ethnic and Racial Composition of Columbus
The population of Columbus, Ohio in 2020 was over 2 million people (Diversity & Disparities, 2022). The three largest ethno-racial groups in the city were White (60.4% of residents), Black or African American (28.8%), and Hispanic or Latino (5.6%) (Diversity & Disparities, 2022). Compared to 1980, the composition has shifted, becoming more diverse. In 1980, the population was 79.1% white and 18.5% Black (Diversity & Disparities, 2022). The growing Hispanic population has also contributed to increasing diversity. While whites remain the largest group, their dominance has declined as the presence of other groups has risen over the past 40 years. This trend toward a more multiethnic population reflects national demographic changes (Frey, 2018).
Black-White Segregation in Columbus
To measure residential separation of Black and white residents, the dissimilarity index ranges from 0 (complete integration) to 100 (complete segregation) (Logan et al., 2020). In 2020, Columbus had a Black-White dissimilarity index score of 54.5 (Diversity & Disparities, 2022). Scores between 50-60 are considered to indicate a moderate level of segregation (Logan et al., 2020). Since 1980, when the score was 62.7, Black and white residents have become slightly less segregated in Columbus (Diversity & Disparities, 2022). While integration has increased, a score of 54.5 still suggests these groups live in reasonably separate neighborhoods in the city.
Some studies have found moderate segregation can negatively impact social connections and economic opportunities for Black residents (Charles, 2003; Logan et al., 2020). It may be difficult to build cross-racial relationships and networks in a moderately segregated city. Further reductions in scores over time could reflect ongoing efforts in Columbus to promote more integrated, inclusive communities through policies like fair housing and open enrollment school choice programs (Orfield et al., 2016). Overall, trends point to modest progress in reducing Black-White neighborhood divides locally.
Black Isolation in Columbus Neighborhoods
Another dimension of segregation is the degree to which Black residents live among themselves in racially concentrated areas (Logan et al., 2020). In 2020, Columbus had a Black isolation index score of 38.5 (Diversity & Disparities, 2022). Isolation scores over 30 suggest Black residents tend to live in racially homogeneous neighborhoods (Logan et al., 2020). Since 1980, when the isolation score was 46.7, Black residents have become slightly less concentrated (Diversity & Disparities, 2022). However, an isolation index near 40 indicates Black Columbus residents still experience moderate racial clustering in certain parts of the city.
Prolonged high isolation can limit access to resources and perpetuate inequality (Charles, 2003; Logan et al., 2016). It may signal underlying issues like housing discrimination, poverty concentration, or underfunded public services in predominantly Black areas (Logan et al., 2020; Rothstein, 2017). While Columbus shows an improving trend of less isolation over time, further reductions could help address such challenges. More integrated neighborhoods may foster greater economic opportunities and quality of life for all residents through improved schools and community development (Logan et al., 2020; Rothwell, 2016).
In summary, this analysis found Columbus, Ohio has become more ethnically and racially diverse since 1980 but still exhibits signs of moderate segregation and racial concentration among Black residents. The city scores 54.5 on the Black-White dissimilarity index and 38.5 on the Black isolation index according to recent data, both suggesting separation and clustering persist (Diversity & Disparities, 2022; Logan et al., 2020). At the same time, trends over the past 40 years point to small yet meaningful decreases in segregation and isolation. Continued efforts to promote fair housing, reduce socioeconomic disparities, and support diverse, inclusive communities may help Columbus make further progress toward full integration. Overall, this case study provides insights into both the challenges and opportunities many U.S. metropolitan areas still face in achieving residential equality and connection among all residents.
Charles, C. Z. (2003). The dynamics of racial residential segregation. Annual Review of Sociology, 29(1), 167–207.
Diversity and Disparities. (2022). Segregation Data Tool.
Frey, W. H. (2018). US minority populations are growing faster than whites in every state. Brookings Institution.
Logan, J. R., Stults, B., & Farley, R. (2020). Segregation of minorities in the metropolis: Two decades of change. Demography, 41(1), 1–22.
Logan, J. R., Stults, B. J., & Zhang, W. (2016). Racial and ethnic diversity in suburban neighborhoods. City & Community, 15(2), 129–150.
Orfield, G., Stancil, W., Kucsera, J., & Siegel-Hawley, G. (2016). Brown at 62: School segregation by race, poverty and state. UCLA Civil Rights Project.
Rothstein, R. (2017). The color of law: A forgotten history of how our government segregated America. Liveright Publishing.
Rothwell, J. (2016). Racial segregation decreases economic growth and opportunity. Brookings Institution.

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