Employment and Training Institute .

Research Update

Racial Integration in Urban America: A Block Level Analysis of African American and White Housing Patterns


by Lois M. Quinn and John Pawasarat, Employment and Training Institute, University of Wisconsin-Milwaukee, December 2002, revised January 2003.
[Report is also available in PDF format]

Rankings - whether of cities, states, universities, or high school students -- are very popular with the media and the public. These rankings often purport to measure highly complex conditions based on a single statistic and sometimes can be very damaging for the entities ranked. A recent report on Exposing Urban Legends: The Real Purchasing Power of Central City Neighborhoods, conducted by the University of Wisconsin-Milwaukee Employment and Training Institute for The Brookings Institution, examined the damage that marketing firms do to cities by ranking neighborhoods based on average household income from richest to poorest and then using racial and other stereotypes that steer retail businesses away from central city neighborhoods. This study examines the basis for the segregation index, which has been used historically to compare urban areas, in order to determine why Milwaukee was ranked as the 3rd most segregated metro area in the U.S. and to assess the strengths and limitations of the formula used to calculate the rankings.

Findings

An alternative definition of black-white integration is presented in this paper, not as a competitive model for ranking cities and metro areas, but to expose the biases and limitations of the segregation indexes. It represents a radical departure from the white domination approach to desegregation that was introduced in the 1950s and that has persisted in the segregation index rankings. Unlike the historic segregation index, the integration measure reflects a democratic perspective that both majority white and majority black neighborhoods may be considered integrated, that is, if an 80 percent white and 20 percent black population is acceptable for a residential block, then an 80 percent black and 20 percent white population should be acceptable as well. Using this new definition of black-white integration, this study analyzed the racial compositon of 8.2 million blocks in the U.S. We find that:

Conclusion

This block level analysis raises serious questions about the white-black dissimilarity segregation index historically used to rank metropolitan areas and its assumptions about the lack of integration occurring in many cities with large African American populations. No single statistic or set of statistics can capture the complex population mix and levels of integration and segregation in urban America, and current segregation rankings of cities and metropolitan areas - while popular in the media - appear to offer little insight into the configuration of neighborhoods in cities with large African American populations. Given housing preferences and electoral successes of African Americans in majority black neighborhoods and cities, emphasis on even dispersal of African Americans throughout each metropolitan area can hardly be considered a national goal with broad-based consensus. Further, in-migration of Latino and Asian populations has brought increasing diversity to urban neighborhoods. In this context, integration may appropriately be defined as successful mixing of diverse populations, rather than the continued dominance of neighborhoods by an urban white majority.

Much of the United States remains racially segregated, with almost a third of the African American population living on blocks that are more than 90 percent black and over half of the white population living on blocks that are more than 90 percent white. The data for Milwaukee and other metro areas clearly suggest the need for remedial efforts to combat racial discrimination and racial steering in housing; to support affirmative housing opportunities, particularly for low and moderate income African American families interested in moving into suburban areas; and to provide public and private support for integrated and diversified neighborhoods.

The implicit goal of the segregation index, that is, integrating urban America by diluting the population of black residents in individual neighborhoods, is one, however, which requires serious reexamination. This preliminary development of an alternative measure of integration - which views black and white populations as equal partners in the integrating process - is a first step toward articulating goals that may assist cities in identifying the strengths and weaknesses of their population mixes. Public policy makers are encouraged to use block level 2000 Census data to develop other tests of racial integration and to develop new measures of diversity in order to identify and address the racial challenges of the 2000s.

I. Methodology

One of the most repeated claims and damaging urban legends is that Milwaukee is the second or third most segregated city in the country. This study examines the basis for the historic statistical tool used to define "segregation" in Milwaukee and compares the national "segregation" rankings to actual counts of residents living on racially integrated blocks in each city and metropolitan area in the United States. The research identifies serious problems with the traditional segregation and "hyper-segregation" indexes and challenges statistical approaches that consider modestly integrated neighborhoods as "too black" while ranking cities with very low African American populations as "least segregated." The historic context for the segregation index is also explored, given the concern of many academic researchers in the 1960s and 1970s with neighborhood "tipping points" and racial biases of white homeowners.

In the 2000 Census, respondents were asked to check up to fifteen racial categories that each household member considered himself/herself to be, including: white; black, African American, or Negro; American Indian or Alaska Native; any of eleven groups of Asian and Pacific Islander; or "some other race." Additionally, respondents were asked whether they were Spanish/Hispanic/Latino.

While a growing number of sociologists are pouring over the 2000 census data analyzing the complex overlay of racial identity in 21st century urban America, the researchers calculating segregation indexes for the Lewis Mumford Center for Comparative Urban and Regional Research at the State University of New York at Albany and the U.S. Census Bureau used definitions that are reminiscent of the 19th century "one drop rule." Whites are defined, not as any one who told the U.S. Census they were white, but only those persons who told the census they were white and white only. Persons who reported that they were white and Native American, Asian, black or other race are considered of another race. The census bureau report states, "The reference group -- non-Hispanic Whites -- is always defined as those who report being White along, and who are not of Hispanic origin."(4) By contrast, "blacks" are persons with any part black (except, as noted, Hispanics): persons who are white and black, white and black and Native American, Asian and black, etc., that is, any mixture that includes black. Because these definitions are those used for the segregation index rankings, and for that reason alone, these racially biased definitions are also used in this analysis.

For our integration research measure the racial composition of all 8.2 million blocks in the United States was examined for the 2000 U.S. Census. Population data files were examined for individual blocks, block groups, census tracts, cities, and metropolitan areas. Blocks, rather than census tracts, were chosen as the unit of analysis since they are more sensitive to whether interaction is occurring between races. To the extent that residential closeness signals racial interaction, the block suggests a better measure than block groups or census tracts.(5) In a number of cases, the census tract (a much larger geographic unit, typically containing 2,500 to 8,000 residents) may include sizeable mixtures of black and white populations even though most blocks in the tract are not racially mixed. Blocks are considered "black-white integrated" if at least a fifth (20 percent) of their population is black and at least a fifth is white. The historic segregation index appears to have a built-in bias suggesting that integration (or non-segregation) is defined by what the majority will tolerate. Its goal of "evenness" of the white majority and black minority reflects this perspective. The integration measure used here (at least 20 percent black and at least 20 percent white on a residential block) describes a more democratic ideal that suggests that each racial group finds the other group acceptable as neighbors.

In order to eliminate blocks that appear integrated due to the presence of institutionalized populations, all U.S. blocks were identified with institutionalized residents (i.e., prison inmates; patients in nursing homes, mental hospitals or wards, hospitals or wards for chronically ill patients, and hospices).(6) Blocks where over a third of the residents are institutionalized are excluded from the count of residentially integrated populations. The percentages of city (or metropolitan) residents living on black-white integrated blocks are calculated by dividing the total population living on black-white integrated blocks by the total city (or metropolitan) population minus the excluded population living in blocks with one-third or more institutionalized persons. The findings for these analyses are then compared to the rankings historically used by academics to compare segregation in urban areas.

II. History of the Segregation Index

Much of the research work on residential segregation developed out of the University of Chicago and focused on racial changes in Chicago neighborhoods. In 1955 Otis Dudley Duncan and Beverly Duncan of the University of Chicago published an analysis of segregation indexes in the American Sociological Review, identifying strengths of various conceptual models.(7) The historic dissimilarity segregation index most commonly used today to rank metropolitan areas and cities as to their degree of segregation was popularized by Karl and Alma Taeuber of the University of Wisconsin, who prepared historic segregation rankings for U.S. cities and discussed the discriminatory practices contributing to segregation of Midwestern cities in their book Negroes in Cities, published in 1965. Segregation was defined as the lack of "even" distribution of the black population. Taeuber and Taeuber explained, "Our segregation index is an index of dissimilarity, and its underlying rationale as a measure of residential segregation is simple: Suppose that whether a person was Negro or white made no difference in his choice of residence, and that his race was not related to any other factors affecting residential location (for instance, income level). Then no neighborhood would be all-Negro or all-white, but rather each race would be represented in each neighborhood in approximately the same proportion as in the city as a whole."(8)

In the 1960s the dissimilarity index addressed two major concerns of academic researchers. First, settlement patterns of African Americans to urban areas, particularly in Chicago and other industrial cities of the Midwest, were shaped not only by the time periods in which African Americans arrived in the northern cities, but also by public and private discriminatory actions. White real estate agents, homeowners and landlords often discriminated against African Americans seeking access to housing as they migrated to the North. The federal government itself redlined in the granting of home mortgages under the Federal Housing Administration and Veterans Administration, enforced racially restrictive covenants placed on deeds in new subdivisions, funded racially segregated housing projects, and supported "urban renewal" projects that displaced low-income residents. Many municipalities prohibited public housing for returning World War II veterans and lower-income families to prevent non-white families from entering their communities. Others enacted restrictive zoning laws that limited new construction housing options for low and moderate-income families.(9) When the federal Fair Housing Act was finally passed in 1968, researchers saw the dissimilarity segregation index as a tool to measure progress toward open housing.

Much of the concern about neighborhoods in racial transition centered on the observed unwillingness of urban white residents to remain in or move into racially mixed neighborhoods. Researchers spoke of a theoretical "tipping point," which Taeuber and Taeuber described as "the percentage Negro in an area which 'exceeds the limits of the neighborhood's tolerance for inter-racial living.'"(10) (In this quotation, the term "neighborhood's tolerance" actually refers to the white residents' tolerance.(11) Along with measuring movement of African Americans into previously all-white neighborhoods, in large part the dissimilarity segregation index addressed the concerns of a white population (and mainly white academic researchers) with "tipping," by identifying the lowest possible black neighborhood population that could be achieved if blacks were spread evenly throughout the city or the entire metro area.(12) The Taeubers explained the approach: "The value of the index may be interpreted as showing the minimum percentage of non-whites who would have to change the block on which they live in order to produce an unsegregated distribution - one in which the percentage of non-whites living on each block is the same throughout the city (0 on the index). For instance, if some governing council had the power and the inclination to redistribute the population of Birmingham so as to obtain an unsegregated distribution of white and non-white residences, they would have to move 92.8 per cent of the non-whites from blocks now containing an above-average proportion of non-whites to blocks now disproportionately occupied by whites."(13) Taeuber and Taeuber calculated segregation indexes based on block data as well as on census tract data.

The segregation index has been used to rank cities and metropolitan areas regardless of their population size or the size of the black population. Rather than recognizing a range of population mixes as integrated (or non-segregated), the index seeks an even distribution of the black population in the metro area as the ideal condition. The index number itself represents the percentage of black residents who would have to move out of their present census tracts and into "whiter" tracts so that all census tracts would have an identical percentage mix of white and black populations.(14) While purporting to be race-neutral, the index has historically been used to measure progress toward the dispersal of blacks into geographic units where they would remain in the minority. (15) In Negroes in Cities, Taeuber and Taeuber reported receiving correspondence from Otis Dudley Duncan suggesting that "a more effective redistribution of the population to achieve desegregation could be made by having white and non-white households exchange residences."(16) This simple adjustment of the segregation index formula to expect that both black and white residents could be expected to move to achieve the index goal of even white-black populations in each census tract -- which was not pursued -- would create a dramatically different ranking of the metro areas on the segregation index. (In 2000, the rankings for 47 of the 100 largest metro areas would shift by 20 or more places if white residents were also expected to move for racial "evenness." Milwaukee's ranking would improve by 19 places.)(17)

When most U.S. cities were majority white, the index was typically applied to measure "evenness" of the black population within city boundaries. Once suburbanization of white residents expanded urban centers and some major cities became majority black, scholars and open housing advocates began using the index primarily for metropolitan statistical areas, as defined by the federal Office of Management and Budget. (18) Even though emphasis on dispersal of their population throughout the metropolitan area was increasingly challenged as a primary housing goal after African Americans gained political power in major U.S. cities and electoral districts, the dissimilarity segregation index continued to be used by academics as the primary measure of black-white racial trends. A number of other segregation indexes have been introduced, but none reached the popularity of the dissimilarity segregation index. It was easy to calculate, especially with the availability of computers; produced an impressively precise number; and typically generated newspaper headlines, at least for the cities ranked as most segregated.

When the dissimilarity segregation index is applied to the Milwaukee metropolitan area in 2000, its score is 82.16%, based on the "ideal" of moving 197,890 blacks of the total 240,859 African American population out of their "too black" census tracts and into the remaining "whiter" tracts. When the dissimilarity index is applied to the Hispanic population as a Latino-white index, it expects 59.5 percent of the Latino population, or 56,200 residents to move from "too Latino" neighborhoods.

Other Segregation Indexes

In the late 1980s, Douglas Massey and Nancy Denton brought renewed publicity to the segregation index by coining the term "hypersegregation," which they used to describe many metropolitan areas with the largest black populations. (19) In addition to the historic segregation index, Massey and Denton used an "isolation index" to calculate the average percentage of other blacks living in census tracts with blacks. Massey and Denton rank the percentages on a scale from 0 to 100 percent.(20) For example, in 1990 the "isolation index" ratings in Anaheim, California, and the Salt Lake City-Ogden, Utah metro areas were each 0.4 percent, indicating that on average blacks lived in census tracts that had only a 0.4 percent black population. Massey and Denton considered these the best rankings among major metropolitan areas. (21) Metro areas where blacks typically live with more than 60 percent other blacks are considered candidates for the Massey-Denton "hypersegregation" category. Under this approach, blacks are considered "isolated" when they live with a substantial majority of other blacks. They are not considered "isolated" when they live in nearly all-white census tracts.

A third measure ("absolute centralization") used by Massey and Denton reflects a racial dispersal goal that the black population should be distributed in equal distances from the central business district to the borders of the metro area, regardless of where the housing stock or populations are located in the region. (In the case of Milwaukee, this means that the black population should be spread equally from the heart of downtown to the Sheboygan, Fond du Lac, Dodge, Jefferson, Walworth, and Racine county lines.) Massey and Denton have chosen to rank metro areas where the black population is located closer to the center of the city as most "segregated" and the metro areas where the black population has more settlements in the suburban, exurban, and rural portions of the metro area as least "segregated."

None of the indexes used by Massey and Denton actually calculate the percentage of blacks living in all-black neighborhoods or the percentage of whites living in all-white neighborhoods. (22) Yet, in spite of the limitations of their methodology, in 2001 Massey went so far as to describe the metro areas they had labeled as "hypersegregated," including Milwaukee, as follows: "Blacks in these areas live within large, contiguous settlements of densely inhabited neighborhoods packed tightly around the urban core. Inhabitants typically would be unlikely to come into contact with non-Blacks in the neighborhood where they live. If they were to travel to an adjacent neighborhood, they would still be unlikely to see a White face. If they went to the next neighborhood beyond that, no Whites would be there either. People growing up in such an environment would have little direct experience with the culture, norms, and behaviors of the rest of American society, and have few social contacts with members of other racial groups." (23)

The graph below shows the actual distribution of the black population in the Milwaukee metropolitan area by residential block. Black residents live in a variety of settings -- from predominantly white neighborhoods, to majority white integrated neighborhoods, to majority black integrated neighborhoods, to predominantly black neighorhoods. In all, 5 percent of the black population (13,156 blacks) live on blocks that are 100 percent black and 33 percent live on blocks that are 90-99 percent black, while 62 percent live in largely mixed race situations. The Massey description of absolute lack of contact with non-black populations is not actually tested by his indexes and does not hold for the black population in metro Milwaukee.

Graph 1.

Distribution of black population by percent black in the
census tract for the Milwaukee metropolitan area: less than 10 percent black (9%), 10-19 percent
black (3%), 20-29 percent black (3%), 30-39 percent black (2%), 40-49 percent black (8%), 50-
59 percent black (10%), 60-69 percent black (10%), 70-79 percent black (11%), 80-89 percent
black (14%), 90-98 percent black (30%)

A new report by the U.S. Census Bureau staff uses a similar approach to rank large metro areas on their level of residential segregation (with separate rankings for African Americans; Hispanics; American Indians and Alaska Natives; and Asians, Native Hawaiians, and other Pacific Islanders).(24) Five values are measured by the Census Bureau indexes:

Like the Massey-Denton approach, the Census Bureau rankings have combined the anti-minority biases of the dissimilarity and isolation indexes with anti-urban indexes valuing population redistribution onto farmland and "urban sprawl" areas surrounding the central cities. The Census Bureau's "delta index" expects the black population to be evenly distributed on the land mass of each metropolitan area, regardless of land type (residential, commercial, industrial, rural) and location of existing housing. (25) For the Milwaukee metro area, this means that the black population should be limited to 165 black residents per square mile throughout the four-county region. According to the Census Bureau, 89 percent of the black population would need to move into less populated tracts to achieve the Census Bureau's new desegregation goal of equal number of blacks per square mile -- giving Milwaukee the worst "segregation" ranking in this category. Under this standard, the City of Milwaukee would be limited to 15,920 black residents (and the total City population would be limited to 99,231 residents). All the rest of the city residents would be expected to relocate onto less populated census tracts, including the many acres of farmland in Ozaukee, Washington, and Waukesha counties. (When applied to the metro Milwaukee Latino population, the Census Bureau goal would limit the Hispanic population to 58 Hispanics per square mile. The Census Bureau redistribution goal for Asians in metro Milwaukee would be 22 Asians per square mile.)

Like Denton and Massey, the Census Bureau uses the "absolute centralization index," expecting the black population to be scattered equal distance away from the population center of the metro area, ignoring the location of existing housing or any advantages of residing in city areas with existing infrastructure, mass transit, and urban amenities. Finally, reflecting the perspective that segregation is a minority problem, and not a majority problem, the Census Bureau report eliminates from its rankings of "most segregated" communities those metro areas with over one million population but with less than 20,000 blacks. (26)

The recent releases of segreation indexes based on 2000 census data demonstrate many of the limitations of continuing to use this statistical approach as the primary tool for gauging segregation in urban America. Proponents of the segregation indexes often avoid discussions of the perplexing configuration of metropolitan areas ranked as "least segregated" by omitting them from their ranking lists. For example, the Mumford Center publishes dissimilarity indexes for metropolitan areas on its website and seeks out press coverage on its rankings of cities. (27) The center reported the black-white segregation index for white it called the "top 50 metro areas," after excluding 80 metro areas with the largest total populations but with fewer African Americans. Similarly, the Hispanic-white segregation index rankings are reported only for the 50 metropolitan areas with the most Hispanic residents. If the 50 largest metro areas were used, the "least segregated" metro , areas for Hispanics and whites would be St. Louis, Pittsburgh, and Cincinnati -- all areas with less than 2 percent Latino populations. (28) The Mumford Center ranks all 331 metro areas on its black-white indexes and then provides a small note indicating that its methodology may not be valid for 226 of the areas. (29)

The perspective that "segregation" occurs when neighborhoods have "too high" a concentration of black residents and not when neighborhoods have "too high" a concentration of white residents also permeates the Mumford Center reports. In one report, the Mumford Center staff stated, for example, "Black-white segregation remains very high except in the metropolitan areas with the smallest black populations."(30)

Under this segregation index, the City of Milwaukee is reported to have a higher level of segregation (74.6 on the black- white segregation index scale) than the "suburban areas" of Milwaukee, Ozaukee, Washington and Waukesha counties. The suburbs have a 46.4 rating, described by the Mumford Center as only "a moderate level of segregation." Actually, in the so-called "moderately segregated" suburban/exurban areas, blacks make up only 1.5 percent of the population and less than 1 percent of the population lives on black-white integrated blocks.(31)

By ignoring racial integration occurring in the large urban centers and focusing on dispersal of small African American populations in suburban and exurban areas of metropolitan counties, press coverage of the historic segregation index rankings reinforces the latest anti-urban legend that the nation's predominantly white suburbs and cities with very small black populations are the most successful models for black-white integration growth in the 1990s. A recent study on black-white segregation used the index to conclude that, "The decline in segregation comes about primarily from the integration of formerly entirely white census tracts."(32) Areas that are nearly all non-black are considered "least segregated" when their small black populations are dispersed. Meanwhile, the racial integration occurring in the major cities of the Midwest is ignored - with much of it considered "segregation" under the old indexes.

III. Black-White Integration in the 50 Largest U.S. Cities

The segregation index is typically applied to metropolitan areas, yet media and public discussions regarding the rankings usually focus on the central city as the entity analyzed. Accordingly, it may be instructive to review the racial composition of blocks in the 50 largest cities, where much of focus of the index rankings has centered. For this analysis all blocks in the 50 largest U.S. cities were examined to identify black-white integrated blocks where black and white residents each comprised at least 20 percent of the block population.


Table 1

Ranking Black-White Integration in the 50 Largest U.S. Cities
% of Residents
Living on
Black-White City
Integrated Population Total
CITY Blocks Rank % Black Rank Population Rank
Virginia Beach, VA 41.1% 1 19.5% 26 425,257 38
Charlotte, NC 31.9% 2 33.0% 13 540,828 26
Nashville-Davidson, TN 29.4% 3 27.3% 16 545,524 25
Jacksonville, FL 28.7% 4 29.3% 15 735,617 14
St. Louis, MO 27.2% 5 51.8% 7 348,189 49
Memphis, TN 26.6% 6 61.6% 4 650,100 18
Columbus, OH 25.1% 7 25.8% 19 711,470 15
Indianapolis, IN 24.4% 8 26.1% 17 781,870 12
Minneapolis, MN 23.3% 9 20.0% 25 382,618 45
Milwaukee, WI 21.7% 10 38.0% 10 596,974 19
Kansas City, MO 21.2% 11 32.0% 14 441,545 36
Baltimore, MD 19.8% 12 64.8% 3 651,154 17
Oakland, CA 19.5% 13 36.7% 12 399,484 41
New Orleans, LA 18.5% 14 67.3% 2 484,674 31
Sacramento, CA 18.5% 15 16.4% 27 407,018 40
Fort Worth, TX 17.3% 16 20.5% 24 534,694 27
Oklahoma City, OK 16.2% 17 16.1% 29 506,132 29
Cleveland, OH 15.9% 18 51.4% 8 478,403 33
Philadelphia, PA 14.1% 19 43.4% 9 1,517,550 5
Tulsa, OK 13.4% 20 16.3% 28 393,049 43
Omaha, NE 13.2% 21 14.0% 31 390,007 44
Boston, MA 12.6% 22 25.7% 20 589,141 20
Washington, DC 11.0% 23 60.5% 6 572,059 21
Detroit, MI 10.8% 24 82.3% 1 951,270 10
Portland, OR 10.4% 25 7.6% 41 529,121 28
Dallas, TX 10.4% 26 26.1% 18 1,188,580 8
Wichita, KS 10.2% 27 12.1% 32 344,284 50
Seattle, WA 10.1% 28 9.6% 37 563,374 23
Colorado Springs, CO 9.9% 29 7.3% 42 360,890 48
Atlanta, GA 8.8% 30 61.6% 5 416,474 39
Long Beach, CA 8.4% 31 15.4% 30 461,522 34
Denver, CO 7.2% 32 11.6% 33 554,636 24
Las Vegas, NV 7.1% 33 10.8% 35 478,434 32
Houston, TX 6.7% 34 25.4% 22 1,953,631 4
Austin, TX 6.4% 35 10.2% 36 656,562 16
Chicago, IL 5.7% 36 36.9% 11 2,896,016 3
San Diego, CA 4.8% 37 8.5% 39 1,223,400 7
New York, NY 4.1% 38 25.6% 21 8,008,278 1
San Francisco, CA 3.7% 39 8.2% 40 776,733 13
Fresno, CA 3.2% 40 8.6% 38 427,652 37
San Antonio, NM 3.2% 41 6.9% 43 1,144,646 9
Honolulu, HI 2.0% 42 2.2% 50 371,657 46
El Paso, TX 1.8% 43 3.0% 48 563,662 22
Miami, FL 1.5% 44 21.3% 23 362,470 47
Los Angeles, CA 1.4% 45 11.4% 34 3,694,820 2
Phoenix, AZ 1.3% 46 5.3% 44 1,321,045 6
Tucson, AZ 0.9% 47 4.6% 45 486,699 30
San Jose, CA 0.4% 48 3.8% 46 894,943 11
Mesa, AZ 0.4% 49 2.8% 49 396,375 42
Albuquerque, NM 0.3% 50 3.2% 47 448,607 35
50 LARGEST U.S. CITIES 9.4% 24.8% 44,559,138


IV. Black-White Integrated Blocks in the 100 Largest Metropolitan Areas

Since the 1990s most academics have used the segregation index to compare metropolitan areas, relying on the definition of metropolitan areas from the Office of Management and Budget. The OMB defines metro areas to include cities with a population of at least 50,000 (or an urbanized area with at least 100,000 people) along with the county in which the city is located and adjacent counties considered to have a "metropolitan character" based on commuting patterns, population density, and economic and social interrelationships. In New England, metropolitan areas are composed of cities and towns rather than whole counties and the urbanized population must total at least 75,000.

The metropolitan areas were used as the unit of analysis to compare the segregation index rankings to the percentages of residents living on black-white integrated blocks for the 100 largest metropolitan areas. Ranking comparisons are limited, however, by differences among metro areas throughout the U.S.

The percentage comparisons of black-white integration in metro areas showed different results from the percentages observed in the largest cities.

Table 2 below compares the rankings on the black-white integration measure with the rankings on the historic segregation index. Many of the metropolitan areas with low percentages of residents living on black-white integrated blocks are ranked "high" on the segregation index. Likewise, many metro areas, particularly in the Midwest, with relatively higher percentages of residents living on black-white integrated blocks are ranked as highly segregated on the old index system.


Table 2
Comparison of Black-White "Segregation Index" Rankings to Percentage of Metro Population Living on Black-White Integrated Blocks
% of
Population
Black-White Black Living on
Segregation Population Black-White
Dissimilarity Old in Metro Integrated
100 Largest Metropolitan Areas, 2000 Census Index Rank Area Rank Blocks Rank
Albuquerque, NM MSA 31.81 1 2.6% 95 0.3% 95
Honolulu, HI MSA 35.83 2 3.1% 91 2.9% 86
El Paso, TX MSA 36.45 3 3.0% 94 2.5% 88
Orange County, CA PMSA 36.80 4 1.8% 97 0.1% 97
Salt Lake City--Ogden, UT MSA 36.91 5 1.3% 99 0.1% 98
Tucson, AZ MSA 38.82 6 3.3% 89 0.6% 94
San Jose, CA PMSA 40.51 7 3.1% 92 0.3% 96
Las Vegas, NV--AZ MSA 43.32 8 8.5% 59 5.7% 66
Phoenix--Mesa, AZ MSA 43.72 9 3.9% 88 1.0% 93
Ventura, CA PMSA 45.52 10 2.1% 96 0.1% 99
Tacoma, WA PMSA 45.95 11 8.2% 64 13.7% 23
Raleigh--Durham--Chapel Hill, NC MSA 46.17 12 23.0% 15 23.1% 6
Norfolk--Virginia Beach--Newport News, VA--NC MSA 46.20 13 31.5% 5 38.6% 1
Riverside--San Bernardino, CA PMSA 46.28 14 8.1% 66 6.3% 62
Greenville--Spartanburg--Anderson, SC MSA 46.44 15 17.7% 29 17.8% 17
Charleston--North Charleston, SC MSA 47.42 16 31.1% 6 32.2% 3
Portland--Vancouver, OR--WA PMSA 48.07 17 3.2% 90 3.0% 85
McAllen--Edinburg--Mission, TX MSA 49.47 18 0.4% 100 0.0% 100
Seattle--Bellevue--Everett, WA PMSA 49.62 19 5.2% 86 4.1% 77
San Antonio, TX MSA 50.40 20 6.7% 75 4.4% 74
Vallejo--Fairfield--Napa, CA PMSA 50.90 21 12.5% 46 15.6% 21
Middlesex--Somerset--Hunterdon, NJ PMSA 51.97 22 8.0% 68 7.2% 56
Columbia, SC MSA 52.15 23 32.3% 3 33.5% 2
Austin--San Marcos, TX MSA 52.28 24 8.1% 65 5.4% 68
Bakersfield, CA MSA 52.28 25 6.1% 78 3.1% 84
Allentown--Bethlehem--Easton, PA MSA 53.27 26 3.1% 93 2.8% 87
Wilmington--Newark, DE--MD PMSA 53.55 27 18.2% 28 20.3% 9
Jacksonville, FL MSA 53.94 28 21.9% 18 20.9% 8
San Diego, CA MSA 54.15 29 6.2% 77 3.2% 83
Fresno, CA MSA 54.30 30 5.3% 85 1.7% 91
Oklahoma City, OK MSA 54.45 31 11.2% 50 11.2% 31
Stockton--Lodi, CA MSA 54.45 32 7.0% 72 3.4% 81
Charlotte--Gastonia--Rock Hill, NC--SC MSA 55.16 33 20.7% 20 21.5% 7
Scranton--Wilkes-Barre--Hazleton, PA MSA 55.60 34 1.6% 98 1.1% 92
Sacramento, CA PMSA 55.97 35 8.4% 62 8.4% 46
Richmond--Petersburg, VA MSA 57.04 36 30.5% 7 26.4% 4
Orlando, FL MSA 57.04 37 14.1% 39 10.1% 38
Nashville, TN MSA 57.05 38 15.9% 32 17.0% 19
Minneapolis--St. Paul, MN--WI MSA 57.83 39 6.1% 80 6.2% 64
Knoxville, TN MSA 58.05 40 6.1% 81 5.0% 72
Wichita, KS MSA 58.21 41 8.4% 61 6.8% 61
Tulsa, OK MSA 58.52 42 9.4% 56 7.6% 49
Providence--Fall River--Warwick, RI--MA MSA 58.69 43 4.3% 87 3.5% 80
Greensboro--Winston-Salem--High Point, NC MSA 59.01 44 20.4% 22 18.9% 13
Dallas, TX PMSA 59.36 45 15.3% 33 10.5% 37
Fort Worth--Arlington, TX PMSA 60.33 46 11.4% 49 11.8% 27
San Francisco, CA PMSA 60.87 47 5.7% 84 1.9% 90
Albany--Schenectady--Troy, NY MSA 60.91 48 6.4% 76 7.4% 54
Little Rock--North Little Rock, AR MSA 61.27 49 22.2% 17 20.2% 10
Denver, CO PMSA 61.76 50 5.9% 83 5.1% 71
Fort Lauderdale, FL PMSA 62.25 51 21.5% 19 16.2% 20
Oakland, CA PMSA 62.81 52 13.4% 40 8.7% 45
Columbus, OH MSA 63.10 53 14.2% 38 13.6% 25
Washington, DC--MD--VA--WV PMSA 63.12 54 26.7% 12 20.2% 11
Ann Arbor, MI PMSA 63.24 55 7.9% 69 10.7% 35
Monmouth--Ocean, NJ PMSA 63.35 56 5.9% 82 5.4% 69
Mobile, AL MSA 63.73 57 27.5% 11 17.7% 18
Springfield, MA MSA 64.13 58 6.8% 74 6.0% 65
Tampa--St. Petersburg--Clearwater, FL MSA 64.47 59 10.4% 53 7.8% 47
Louisville, KY--IN MSA 64.49 60 14.3% 37 11.3% 29
Omaha, NE--IA MSA 64.69 61 8.8% 57 7.8% 48
Hartford, CT MSA 65.05 62 9.7% 55 7.0% 58
Atlanta, GA MSA 65.61 63 29.2% 9 18.4% 14
Boston, MA--NH PMSA 65.68 64 7.3% 71 4.4% 75
Jersey City, NJ PMSA 65.69 65 12.8% 45 3.8% 79
Akron, OH PMSA 65.85 66 11.5% 48 10.8% 34
Rochester, NY MSA 66.32 67 10.6% 52 9.1% 42
West Palm Beach--Boca Raton, FL MSA 66.68 68 14.5% 35 9.7% 40
Baton Rouge, LA MSA 66.93 69 32.1% 4 17.9% 16
Sarasota--Bradenton, FL MSA 67.15 70 6.1% 79 4.3% 76
Grand Rapids--Muskegon--Holland, MI MSA 67.18 71 7.7% 70 6.9% 59
Pittsburgh, PA MSA 67.27 72 8.5% 60 7.6% 50
Houston, TX PMSA 67.49 73 17.6% 30 7.6% 51
Los Angeles--Long Beach, CA PMSA 67.55 74 10.0% 54 2.5% 89
Baltimore, MD PMSA 67.93 75 27.9% 10 19.0% 12
Memphis, TN--AR--MS MSA 68.72 76 43.6% 1 23.5% 5
New Haven--Meriden, CT PMSA 68.97 77 13.4% 42 11.4% 28
Toledo, OH MSA 69.10 78 13.3% 43 11.3% 30
Kansas City, MO--KS MSA 69.12 79 13.2% 44 10.1% 39
New Orleans, LA MSA 69.25 80 37.7% 2 18.3% 15
Syracuse, NY MSA 69.26 81 7.0% 73 6.9% 60
Dayton--Springfield, OH MSA 70.16 82 14.8% 34 9.4% 41
Harrisburg--Lebanon--Carlisle, PA MSA 70.62 83 8.2% 63 7.5% 52
Indianapolis, IN MSA 70.66 84 14.4% 36 13.7% 24
Philadelphia, PA--NJ PMSA 72.33 85 20.4% 21 11.1% 32
Youngstown--Warren, OH MSA 72.85 86 10.6% 51 8.8% 44
Birmingham, AL MSA 72.92 87 30.2% 8 14.8% 22
Bergen--Passaic, NJ PMSA 73.24 88 8.1% 67 3.4% 82
Miami, FL PMSA 73.57 89 19.9% 23 3.9% 78
St. Louis, MO--IL MSA 74.35 90 18.7% 27 13.2% 26
Nassau--Suffolk, NY PMSA 74.38 91 8.7% 58 5.3% 70
Cincinnati, OH--KY--IN PMSA 74.84 92 13.4% 41 10.9% 33
Buffalo--Niagara Falls, NY MSA 76.74 93 12.0% 47 7.3% 55
Cleveland--Lorain--Elyria, OH PMSA 77.32 94 18.9% 26 10.6% 36
Newark, NJ PMSA 80.42 95 22.5% 16 7.5% 53
Chicago, IL PMSA 80.85 96 19.0% 25 6.3% 63
New York, NY PMSA 81.82 97 23.8% 13 4.7% 73
Milwaukee--Waukesha, WI PMSA 82.16 98 16.0% 31 9.1% 43
Gary, IN PMSA 84.14 99 19.8% 24 5.7% 67
Detroit, MI PMSA 84.72 100 23.4% 14 7.1% 57


V. Distribution of the Black and White Populations in the 100 Largest Metropolitan Areas

No single statistic or set of statistics can capture the complex population mix and levels of integration and segregation in urban America, and communities are encouraged to use block level census data to understand the mixes of their neighborhoods. Current rankings of cities and metropolitan areas appear to offer little insight into the configuration of neighborhoods in cities with large African American populations. In addition to defining and identifying integrated blocks, it is critical to locate areas where less racial mixing is taking place.

Table 3 below shows the breakdown of the black population by those living on black-white integrated blocks as well as those living on blocks that are predominantly black (here defined as more than 80 percent black). Additionally, percentages are shown of the black population living on blocks where blacks make up less than 20 percent of the population and whites comprise over 50 percent of the total population. A remaining "other mixture" category shows the population on blocks where blacks typically reside with Latino or Asian populations as well as whites.

Similarly, Table 4 below shows the breakdown of the white population by those living on black-white integrated blocks as well as those living on blocks that are predominantly white (here defined as more than 80 percent white), majority black and less than a fifth white, and the remaining blocks with other mixtures.

The tables showing percentages of black and white residents living together help demonstrate the limitations of a two-race analysis. In many metro areas, Latino and Asian populations make up a sizeable proportion of the total population and individuals may identify themselves as members of more than one racial/ethnic group. The smaller the total black population or larger the "other mixture" populations, the fewer residents who will likely live on predominantly black blocks.


Table 3
Racial Composition of Blocks Occupied by Black Residents
% of Black Population Living on Blocks That Are:
Black >=20% Black+ <20% Black+ Other
Metropolitan Area Population >=20% White >50% White >80% Black Mixture
MIDWEST
Akron, OH PMSA 80,180 38.7% 21.7% 36.1% 3.5%
Ann Arbor, MI PMSA 45,704 51.7% 31.6% 13.5% 3.3%
Chicago, IL PMSA 1,575,173 12.6% 7.0% 68.5% 11.9%
Cincinnati, OH--KY--IN PMSA 220,034 37.1% 14.2% 46.6% 2.1%
Cleveland--Lorain--Elyria, OH PMSA 425,722 24.0% 10.4% 62.3% 3.3%
Columbus, OH MSA 218,565 40.3% 21.5% 31.5% 6.6%
Dayton--Springfield, OH MSA 141,038 30.0% 18.5% 48.8% 2.8%
Detroit, MI PMSA 1,037,674 14.1% 6.6% 75.2% 4.1%
Gary, IN PMSA 125,093 12.2% 5.2% 68.3% 14.3%
Grand Rapids--Muskegon--Holland, MI MSA 84,193 36.0% 26.3% 23.2% 14.5%
Indianapolis, IN MSA 230,843 39.5% 13.5% 39.3% 7.7%
Kansas City, MO--KS MSA 235,277 31.4% 18.3% 43.7% 6.5%
Milwaukee--Waukesha, WI PMSA 240,859 27.0% 7.7% 52.3% 13.0%
Minneapolis--St. Paul, MN--WI MSA 180,006 37.1% 37.2% 4.1% 21.7%
Omaha, NE--IA MSA 63,134 38.7% 26.4% 24.8% 10.1%
St. Louis, MO--IL MSA 486,602 31.5% 10.6% 55.2% 2.7%
Toledo, OH MSA 82,304 36.0% 17.5% 40.2% 6.3%
Wichita, KS MSA 45,776 27.6% 32.4% 30.1% 9.9%
Youngstown--Warren, OH MSA 63,221 39.6% 17.6% 33.5% 9.3%
NORTHEAST
Albany--Schenectady--Troy, NY MSA 56,092 43.9% 35.1% 10.2% 10.8%
Allentown--Bethlehem--Easton, PA MSA 19,526 26.9% 52.3% 0.8% 20.1%
Bergen--Passaic, NJ PMSA 110,763 13.4% 16.3% 19.0% 51.3%
Boston, MA--NH PMSA 247,684 20.2% 27.9% 21.2% 30.7%
Buffalo--Niagara Falls, NY MSA 140,496 25.9% 15.3% 50.8% 8.0%
Harrisburg--Lebanon--Carlisle, PA MSA 51,579 37.1% 21.4% 20.7% 20.9%
Hartford, CT MSA 114,378 25.6% 26.2% 22.1% 26.1%
Jersey City, NJ PMSA 77,941 8.7% 5.9% 36.8% 48.6%
Middlesex--Somerset--Hunterdon, NJ PMSA 93,639 28.5% 30.2% 4.2% 37.1%
Monmouth--Ocean, NJ PMSA 66,698 31.9% 30.0% 17.6% 20.5%
Nassau--Suffolk, NY PMSA 238,293 21.8% 16.0% 21.9% 40.2%
New Haven--Meriden, CT PMSA 72,419 31.8% 17.0% 22.8% 28.4%
New York, NY PMSA 2,217,680 7.3% 4.6% 40.3% 47.9%
Newark, NJ PMSA 457,825 12.8% 6.4% 58.2% 22.6%
Philadelphia, PA--NJ PMSA 1,040,144 22.0% 11.7% 53.3% 13.1%
Pittsburgh, PA MSA 200,229 37.0% 22.5% 38.5% 2.0%
Providence--Fall River--Warwick, RI--MA MSA 51,012 23.9% 40.4% 0.5% 35.2%
Rochester, NY MSA 116,235 34.0% 23.6% 19.5% 22.9%
Scranton--Wilkes-Barre--Hazleton, PA MSA 9,817 26.5% 70.4% 0.5% 2.7%
Springfield, MA MSA 40,349 28.6% 26.9% 6.5% 38.0%
Syracuse, NY MSA 50,995 38.7% 27.5% 20.2% 13.7%
SOUTH
Atlanta, GA MSA 1,202,260 25.8% 10.9% 53.0% 10.3%
Austin--San Marcos, TX MSA 101,518 20.1% 28.8% 4.9% 46.2%
Baltimore, MD PMSA 712,002 28.1% 10.5% 57.1% 4.3%
Baton Rouge, LA MSA 193,449 26.3% 7.4% 63.2% 3.1%
Birmingham, AL MSA 278,254 23.1% 6.1% 68.3% 2.4%
Charleston--North Charleston, SC MSA 170,564 44.0% 11.3% 41.7% 3.0%
Charlotte--Gastonia--Rock Hill, NC--SC MSA 310,821 39.4% 14.1% 34.9% 11.6%
Columbia, SC MSA 173,380 45.5% 7.6% 43.0% 3.9%
Dallas, TX PMSA 537,789 24.8% 17.2% 28.6% 29.4%
El Paso, TX MSA 20,085 23.6% 4.6% 0.1% 71.7%
Fort Lauderdale, FL PMSA 349,610 26.8% 14.1% 39.7% 19.4%
Fort Worth--Arlington, TX PMSA 194,002 34.0% 22.7% 19.1% 24.2%
Greensboro--Winston-Salem--High Point, NC MSA 255,112 36.7% 14.2% 38.0% 11.0%
Greenville--Spartanburg--Anderson, SC MSA 170,249 41.0% 18.0% 37.6% 3.5%
Houston, TX PMSA 734,732 14.0% 10.2% 32.1% 43.7%
Jacksonville, FL MSA 241,161 38.0% 17.1% 41.5% 3.4%
Knoxville, TN MSA 41,582 32.7% 36.3% 29.4% 1.5%
Little Rock--North Little Rock, AR MSA 129,554 39.8% 12.4% 41.8% 5.9%
Louisville, KY--IN MSA 147,162 30.2% 19.9% 47.0% 2.9%
McAllen--Edinburg--Mission, TX MSA 2,085 1.2% 4.1% 0.5% 94.2%
Memphis, TN--AR--MS MSA 494,641 26.1% 5.2% 64.1% 4.6%
Miami, FL PMSA 448,173 7.0% 1.7% 49.3% 42.0%
Mobile, AL MSA 148,754 26.9% 8.4% 62.4% 2.2%
Nashville, TN MSA 196,127 38.1% 20.9% 37.8% 3.3%
New Orleans, LA MSA 503,720 21.9% 5.4% 66.0% 6.6%
Norfolk--Virginia Beach--Newport News, VA--NC MSA 493,863 47.7% 10.3% 37.3% 4.7%
Oklahoma City, OK MSA 121,420 36.1% 27.5% 27.5% 8.9%
Orlando, FL MSA 232,243 27.6% 21.1% 28.9% 22.4%
Raleigh--Durham--Chapel Hill, NC MSA 273,724 38.7% 17.1% 30.8% 13.5%
Richmond--Petersburg, VA MSA 303,953 37.3% 11.2% 45.8% 5.7%
San Antonio, TX MSA 106,747 19.0% 19.4% 4.3% 57.3%
Sarasota--Bradenton, FL MSA 36,186 25.2% 24.4% 30.2% 20.1%
Tampa--St. Petersburg--Clearwater, FL MSA 248,058 29.2% 23.0% 32.5% 15.3%
Tulsa, OK MSA 75,471 28.0% 28.7% 36.0% 7.4%
Washington, DC--MD--VA--WV PMSA 1,312,419 28.2% 12.3% 43.3% 16.3%
West Palm Beach--Boca Raton, FL MSA 163,774 24.1% 16.8% 42.1% 17.0%
Wilmington--Newark, DE--MD PMSA 106,463 41.9% 18.8% 28.0% 11.3%
WEST
Albuquerque, NM MSA 18,544 3.4% 42.6% 0.2% 53.8%
Bakersfield, CA MSA 40,606 16.0% 29.3% 1.2% 53.5%
Denver, CO PMSA 124,352 28.1% 34.8% 5.0% 32.0%
Fresno, CA MSA 48,597 9.2% 18.5% 2.7% 69.6%
Honolulu, HI MSA 27,134 23.4% 22.0% 0.0% 54.6%
Las Vegas, NV--AZ MSA 133,244 19.0% 43.9% 7.7% 29.3%
Los Angeles--Long Beach, CA PMSA 950,765 7.8% 8.8% 13.7% 69.7%
Oakland, CA PMSA 319,836 21.7% 12.1% 9.1% 57.1%
Orange County, CA PMSA 51,080 1.4% 44.7% 0.0% 53.9%
Phoenix--Mesa, AZ MSA 127,227 6.8% 49.6% 1.4% 42.2%
Portland--Vancouver, OR--WA PMSA 61,373 34.8% 54.7% 1.7% 8.8%
Riverside--San Bernardino, CA PMSA 263,591 22.1% 21.3% 0.7% 55.9%
Sacramento, CA PMSA 136,246 28.8% 30.9% 0.4% 39.9%
Salt Lake City--Ogden, UT MSA 17,717 2.5% 78.8% 0.2% 18.4%
San Diego, CA MSA 174,418 13.9% 30.6% 0.7% 54.8%
San Francisco, CA PMSA 99,199 10.2% 20.9% 5.4% 63.5%
San Jose, CA PMSA 51,590 2.7% 26.8% 0.1% 70.5%
Seattle--Bellevue--Everett, WA PMSA 124,410 25.6% 52.6% 0.5% 21.3%
Stockton--Lodi, CA MSA 39,684 13.5% 21.8% 0.2% 64.6%
Tacoma, WA PMSA 57,374 47.2% 45.0% 0.2% 7.6%
Tucson, AZ MSA 27,876 4.6% 60.4% 0.2% 34.7%
Vallejo--Fairfield--Napa, CA PMSA 64,897 36.5% 22.6% 2.7% 38.2%
Ventura, CA PMSA 16,055 1.4% 49.8% 0.1% 48.7%


Table 4

Racial Composition of Blocks Occupied by White Residents
% of White Population Living on Blocks That Are:
White >=20% White+ <20% White+ Other
Metropolitan Area Population >=20% Black >50% Black >80% White Mixture
MIDWEST
Akron, OH PMSA 593,445 6.8% 0.4% 89.3% 3.5%
Ann Arbor, MI PMSA 484,391 6.8% 0.1% 79.4% 13.8%
Chicago, IL PMSA 4,798,533 4.8% 0.7% 64.2% 30.3%
Cincinnati, OH--KY--IN PMSA 1,375,267 6.6% 0.5% 90.0% 2.9%
Cleveland--Lorain--Elyria, OH PMSA 1,697,660 6.8% 0.6% 85.6% 7.0%
Columbus, OH MSA 1,238,296 8.7% 0.6% 82.1% 8.6%
Dayton--Springfield, OH MSA 776,050 5.8% 0.6% 87.8% 5.9%
Detroit, MI PMSA 3,096,900 4.5% 1.1% 85.0% 9.4%
Gary, IN PMSA 428,791 3.6% 0.9% 81.0% 14.5%
Grand Rapids--Muskegon--Holland, MI MSA 903,766 4.1% 0.2% 84.0% 11.7%
Indianapolis, IN MSA 1,299,311 8.6% 0.6% 85.6% 5.2%
Kansas City, MO--KS MSA 1,391,492 6.3% 0.4% 83.3% 10.0%
Milwaukee--Waukesha, WI PMSA 1,116,150 5.3% 0.8% 85.2% 8.7%
Minneapolis--St. Paul, MN--WI MSA 2,514,494 3.3% 0.2% 85.9% 10.6%
Omaha, NE--IA MSA 593,902 4.5% 0.3% 83.2% 12.0%
St. Louis, MO--IL MSA 2,014,776 8.6% 0.7% 86.1% 4.6%
Toledo, OH MSA 495,070 6.8% 0.6% 83.6% 9.0%
Wichita, KS MSA 430,553 4.4% 0.2% 75.2% 20.2%
Youngstown--Warren, OH MSA 513,967 5.0% 0.5% 91.9% 2.6%
NORTHEAST
Albany--Schenectady--Troy, NY MSA 771,049 4.2% 0.2% 89.2% 6.4%
Allentown--Bethlehem--Easton, PA MSA 552,429 1.7% 0.0% 87.0% 11.3%
Bergen--Passaic, NJ PMSA 890,640 2.1% 0.3% 60.7% 36.9%
Boston, MA--NH PMSA 2,726,018 2.4% 0.2% 80.5% 16.9%
Buffalo--Niagara Falls, NY MSA 965,233 4.1% 0.5% 90.2% 5.2%
Harrisburg--Lebanon--Carlisle, PA MSA 544,078 4.4% 0.4% 89.6% 5.6%
Hartford, CT MSA 915,287 4.0% 0.2% 82.0% 13.8%
Jersey City, NJ PMSA 215,216 3.5% 0.7% 18.5% 77.3%
Middlesex--Somerset--Hunterdon, NJ PMSA 797,594 4.5% 0.1% 61.2% 34.2%
Monmouth--Ocean, NJ PMSA 955,076 3.0% 0.2% 86.1% 10.7%
Nassau--Suffolk, NY PMSA 2,105,352 2.8% 0.4% 80.0% 16.8%
New Haven--Meriden, CT PMSA 395,573 6.8% 0.6% 77.3% 15.3%
New York, NY PMSA 3,684,669 4.4% 1.7% 48.4% 45.5%
Newark, NJ PMSA 1,196,664 5.3% 1.2% 70.0% 23.5%
Philadelphia, PA--NJ PMSA 3,583,090 7.4% 0.7% 80.8% 11.1%
Pittsburgh, PA MSA 2,100,501 4.8% 0.2% 92.5% 2.5%
Providence--Fall River--Warwick, RI--MA MSA 990,722 1.9% 0.0% 86.7% 11.5%
Rochester, NY MSA 902,811 5.1% 0.5% 87.4% 7.1%
Scranton--Wilkes-Barre--Hazleton, PA MSA 600,830 0.7% 0.0% 97.6% 1.7%
Springfield, MA MSA 459,511 3.4% 0.2% 81.4% 15.0%
Syracuse, NY MSA 644,035 3.9% 0.3% 91.1% 4.7%
SOUTH
Atlanta, GA MSA 2,460,740 14.1% 1.6% 66.8% 17.5%
Austin--San Marcos, TX MSA 758,302 3.3% 0.1% 46.6% 50.0%
Baltimore, MD PMSA 1,692,851 14.4% 1.3% 73.8% 10.5%
Baton Rouge, LA MSA 385,099 13.5% 1.5% 78.3% 6.7%
Birmingham, AL MSA 611,574 10.9% 1.4% 83.1% 4.6%
Charleston--North Charleston, SC MSA 351,434 26.0% 1.4% 61.1% 11.5%
Charlotte--Gastonia--Rock Hill, NC--SC MSA 1,067,594 15.7% 0.7% 74.0% 9.6%
Columbia, SC MSA 337,574 26.4% 1.3% 65.9% 6.4%
Dallas, TX PMSA 1,979,218 7.8% 0.6% 50.3% 41.3%
El Paso, TX MSA 115,535 6.2% 0.0% 1.7% 92.1%
Fort Lauderdale, FL PMSA 941,674 11.1% 1.3% 43.5% 44.1%
Fort Worth--Arlington, TX PMSA 1,116,886 7.9% 0.4% 59.5% 32.2%
Greensboro--Winston-Salem--High Point, NC MSA 905,018 13.1% 0.8% 77.4% 8.7%
Greenville--Spartanburg--Anderson, SC MSA 747,540 12.3% 0.6% 80.2% 6.9%
Houston, TX PMSA 1,923,990 6.1% 1.0% 45.3% 47.6%
Jacksonville, FL MSA 775,279 14.7% 0.6% 66.8% 17.9%
Knoxville, TN MSA 623,048 3.2% 0.1% 93.5% 3.2%
Little Rock--North Little Rock, AR MSA 429,131 14.0% 1.1% 78.0% 6.9%
Louisville, KY--IN MSA 840,677 7.6% 0.4% 86.9% 5.1%
McAllen--Edinburg--Mission, TX MSA 59,423 0.0% 0.0% 21.8% 78.2%
Memphis, TN--AR--MS MSA 588,808 20.8% 2.7% 69.2% 7.3%
Miami, FL PMSA 465,772 6.0% 3.3% 6.4% 84.3%
Mobile, AL MSA 370,631 13.7% 1.0% 80.0% 5.3%
Nashville, TN MSA 960,118 11.8% 0.5% 79.5% 8.2%
New Orleans, LA MSA 731,514 15.1% 2.3% 68.4% 14.2%
Norfolk--Virginia Beach--Newport News, VA--NC MSA 959,404 32.4% 1.3% 52.1% 14.2%
Oklahoma City, OK MSA 789,780 7.5% 0.3% 62.3% 29.9%
Orlando, FL MSA 1,070,460 6.4% 0.5% 53.0% 40.1%
Raleigh--Durham--Chapel Hill, NC MSA 793,714 17.7% 0.9% 63.1% 18.3%
Richmond--Petersburg, VA MSA 637,800 20.6% 1.5% 68.7% 9.2%
San Antonio, TX MSA 627,176 4.0% 0.2% 23.4% 72.4%
Sarasota--Bradenton, FL MSA 505,267 2.2% 0.2% 90.4% 7.2%
Tampa--St. Petersburg--Clearwater, FL MSA 1,821,955 4.5% 0.4% 73.6% 21.6%
Tulsa, OK MSA 593,498 4.7% 0.3% 61.0% 34.0%
Washington, DC--MD--VA--WV PMSA 2,762,241 16.2% 1.5% 48.6% 33.7%
West Palm Beach--Boca Raton, FL MSA 798,484 6.1% 0.5% 69.4% 24.0%
Wilmington--Newark, DE--MD PMSA 433,306 14.4% 0.6% 74.2% 10.9%
WEST
Albuquerque, NM MSA 340,286 0.3% 0.0% 19.6% 80.1%
Bakersfield, CA MSA 327,190 2.5% 0.0% 39.6% 57.9%
Denver, CO PMSA 1,484,343 3.2% 0.2% 61.9% 34.7%
Fresno, CA MSA 374,913 1.3% 0.0% 25.6% 73.1%
Honolulu, HI MSA 175,633 6.9% 0.0% 1.4% 91.7%
Las Vegas, NV--AZ MSA 986,463 3.8% 0.1% 38.3% 57.8%
Los Angeles--Long Beach, CA PMSA 2,959,614 2.8% 0.4% 23.7% 73.1%
Oakland, CA PMSA 1,140,504 6.4% 0.8% 27.7% 65.1%
Orange County, CA PMSA 1,458,978 0.1% 0.0% 33.3% 66.6%
Phoenix--Mesa, AZ MSA 2,140,171 0.6% 0.0% 57.7% 41.7%
Portland--Vancouver, OR--WA PMSA 1,564,685 1.7% 0.0% 74.2% 24.1%
Riverside--San Bernardino, CA PMSA 1,541,053 4.5% 0.1% 25.8% 69.6%
Sacramento, CA PMSA 1,046,616 4.8% 0.1% 50.6% 44.5%
Salt Lake City--Ogden, UT MSA 1,104,467 0.1% 0.0% 77.0% 22.9%
San Diego, CA MSA 1,548,833 2.1% 0.1% 40.2% 57.6%
San Francisco, CA PMSA 885,518 1.5% 0.1% 36.9% 61.5%
San Jose, CA PMSA 744,282 0.3% 0.0% 19.1% 80.6%
Seattle--Bellevue--Everett, WA PMSA 1,841,254 2.3% 0.1% 62.8% 34.8%
Stockton--Lodi, CA MSA 267,002 2.3% 0.0% 22.2% 75.5%
Tacoma, WA PMSA 532,934 8.8% 0.0% 63.0% 28.2%
Tucson, AZ MSA 518,720 0.5% 0.0% 44.7% 54.9%
Vallejo--Fairfield--Napa, CA PMSA 280,214 10.2% 0.3% 28.9% 60.6%
Ventura, CA PMSA 427,449 0.1% 0.0% 45.0% 54.9%


Maps 1 and 2 below show the location of integrated, predominantly black, and predominantly white blocks in the Milwaukee metropolitan area. Integrated blocks have at least a 20 percent black and a 20 percent white population. Predominantly black blocks show a population that is more than 80 percent black; predominantly white blocks show a population that is more than 80 percent white. Blocks are left blank that have no residents (i.e., industrial land, parks, cemeteries, schools) or where the institutionalized population makes up more than a third of the total population.


Map of
Integrated, Predominantly Black, and Predominantly White Blocks in the Milwaukee
Metropolitan Area

Map 1. Map of Integrated, Predominantly Black, and Predominantly White Blocks in the 4-County Milwaukee Area


Map of Integrated,
Predominantly Black, and Predominantly White Blocks in the Milwaukee Metropolitan
Area

Map 2. Detailed Map of Integrated, Predominantly Black, and Predominantly White Blocks in the Milwaukee Metro Area


VI. Density Maps of Integrated, Predominantly Black, and Predominantly White Block Groups

Maps were prepared for the 100 largest metro areas in the U.S. to aid public policy makers in identifying integrated neighborhoods. The analysis of integrated and predominantly one-race neighborhoods was conducted at the block level. For mapping purposes, block groups were used to help show the location of integrated and predominantly one-race areas. Three sets of population density maps were prepared for each of the 100 largest metropolitan areas:

The maps show the concentration of population based on density per square mile. As a result, urban neighborhoods with higher concentrations of residents (integrated, predominantly black, or predominantly white) are highest, or tallest, in the 3-D maps presented, while sparsely populated areas appear flat. Block groups are excluded where the institutionalized population makes up more than a third of the total population or where the block group population totals less than 50 people. Some metropolitan areas have residents living on black-white integrated blocks but have no block groups meeting the black-white integration criteria. Likewise, some metro areas, particularly those with large Latino and Asian populations, may have individual blocks with predominantly black (or predominantly white) populations but no block groups where the population is predominantly black (predominantly white).

Density maps for the Milwaukee metropolitan area are shown below. Maps for other metropolitan areas are available at Density Maps of the African American and White Populations in the 100 Largest Metro Areas.


Map of
Milwaukee Area Block Groups That Are Integrated

Map 3. Integrated Neighborhoods in the Milwaukee Metropolitan Area


Map of
Milwaukee Area Block Groups That Are Over 80 Percent Black

Map 4. Predominantly Black Neighborhoods in the Milwaukee Metropolitan Area


Map of
Milwaukee Area Block Groups That Are Over 80 Percent White

Map 5. Predominantly White Neighborhoods in the Milwaukee Metropolitan Area


Endnotes

1. Under the segregation index, the racial "ideal" in 329 of the 331 metropolitan areas in the U.S. would result in blacks being in the minority in every census tract. Only in Albany, Georgia (population 120,822) and Pine Bluff, Arkansas (population 84,278), where the metro population is majority black, does the index allow a goal of majority black tracts.

2. In the Milwaukee metro area the population includes 1,116,150 residents (74.4 percent) identified as white only and non-Hispanic, 240,859 residents (16.5 percent) identified as in whole or any part black, 94,511 residents (6.3 percent) identified as Hispanic regardless of other racial choices, and the remaining 49,221 residents reporting their racial/ethnic identity as Native American, Asian or other race (but not Hispanic and not part black). The segregation index formula uses the black population percentage of the combined black and white population total for the metro area in determining the "ideal" racial mix in each tract. In the Salt Lake City-Ogden metro area the population is 82.8 percent white, 1.3 percent black, and 15.9 percent other.

3. The equally absurd converse - that 917,029 whites out of the total 1,169,641 white population in the four-county area (or 82.16%), would abandon their "too white" census tracts and move into the remaining tracts - never appears to be discussed as a policy option. See, for example, the discussion by Taeuber and Taeuber on moving 92.8 percent of the black population of the City of Birmingham. Karl E. Taeuber and Alma F. Taeuber, Negroes in Cities: Residential Segregation and Neighborhood Change (Chicago: Aldine Publishing Company, 1965), 30.

4. John Iceland, Daniel H. Weinberg, and Erika Steinmetz, U.S. Census Bureau Series CENSR-3, Racial and Ethnic Segregation in the United States: 1980-2000 (Washington, D.C.: U.S. Government Printing Office, August 2002), 117.

5. In cities census blocks usually correspond to individual city blocks bounded by streets, but in rural areas "blocks" may include several square miles and have boundaries that are not streets.

6. Institutionalized populations are included among the black populations "expected to move" in the calculations for the segregation index.

7. Otis Dudley Duncan and Beverly Duncan, "A Methodological Analysis of Segregation Indexes," American Sociological Review 20 (April 1955): 210-217.

8. Taeuber and Taeuber, 29. The dissimilarity index formula is D=
formula for calculating the dissimilarity index
where bi is the black population in census tract i, B is the total black population in the metropolitan area, wiis the white population in census tract i, and W is the total white population in the metropolitan area.

9. For discussions of racial practices in Milwaukee, see Ruth Zubrensky, "A Report on Past Discrimination Against African-Americans in Milwaukee, 1835-1999" (July 1999); Joe William Trotter, Jr., Black Milwaukee: The Making of an Industrial Proletariat, 1915-45 (Urbana: University of Illinois Press, 1985); Lois M. Quinn, Michael G. Barndt, and Diane S. Pollard, "Relationships Between School Desegregation and Government Housing Programs: A Milwaukee Case Study," report prepared for the National Institute of Education (Milwaukee: Metropolitan Integration Research Center, 1980).

10. Taeuber and Taeuber, quoting from Morton Grodzins, The Metropolitan Area as a Racial Problem (Pittsburgh: University of Pittsburgh Press, 1958), 100.

11. In his 1971 study on The Black Ghetto, Harold Rose of the University of Wisconsin-Milwaukee observed that the terminology used by scholars to describe racial changes in neighborhoods, while derived from descriptions of plant ecology, "has come to represent the white residents' perception of events in the struggle for residential space, and in all likelihood the white writer's perception as well." Harold M. Rose, "The Development of an Urban Subsystem: The Case of the Negro Ghetto," Annals of the Association of American Geographers (March 1970), 4, cited in Harold M. Rose, The Black Ghetto: A Spatial Behavioral Perspective (New York: McGraw-Hill Book Company, 1971), 8.

12. A more recent use of "tipping point" and "dispersal" policies can be seen in the Gautreaux public housing relocation program, an experiment finding housing for African American families in 115 suburbs around Chicago. According to Northwestern University sociologist James Rosenbaum, the program did not place families in communities considered to be "too near a 'tipping point' (a level of black population above which white residents might feel threatened and flee)." James E. Rosenbaum, "Changing the Geography of Opportunity by Expanding Residential Choice: Less from the Gautreaux Program," Housing Policy Debate 6 (1995): 257.

13. Taeuber and Taeuber, 30.

14. For example, if the black population in a metro area makes up 10 percent of the combined black and white populations, the goal of the segregation index would be to have each census tract with a 90 percent white and 10 percent black population out of the combined black-white total. Under the one-way movement approach, if a census tract has 1,000 black residents and 18 white residents, all but 2 of the black residents would be expected to move out of the tract so that the tract could be 90 percent white. If a census tract has no whites, all blacks are expected to move out to achieve the black-white "evenness" goal for the metro area.

15. Surveys of housing preferences of metro Detroit area residents by University of Michigan researchers in 1976 and 1992 found that a majority of African American respondents preferred racially mixed neighborhoods with at least fifty percent or more black populations. There was some increase in tolerance for mixed neighborhoods by white respondents from 1976 to 1992. Still, in 1992 while 70 percent of white respondents indicated they would feel comfortable with a racial mix equal to the Detroit metro average (20 percent black), 73 percent reported that they would not be willing to move onto a block that was just over 50 percent black. Reynolds Farley, Sheldon Danziger, and Harry J. Holtzer, Detroit Divided (New York: Russell Sage Foundation, 2000), 188-216.

16. Duncan's formula for calculating the percentage of the total population required to move under this approach was not used by the authors or discussed further in the text. Taeuber and Taeuber, 30.

17. Under the Duncan approach, the formula used is 2 times the percentage black of the metro area's combined black and white populations (p) times the percentage white of the metro area's combined black and white population (q=1- p) times the dissimilarity index (D), or 2pqD.

18. For a study using the historical segregation index to rank cities based on 2000 census data, see William H. Frey and Dowell Myers, "Working Paper: Neighborhood Segregation in Single-Race and Multirace America: A Census 2000 Study of Cities and Metropolitan Areas" (Fannie Mae Foundation, 2002).

19. Douglas S. Massey and Nancy A. Denton, "The Dimensions of Residential Segregation," Social Forces 67: 281-315.

20. Douglas S. Massey and Nancy A. Denton, American Apartheid: Segregation and the Making of the Underclass (Cambridge, Mass.: Harvard University Press, 1993); Douglas S. Massey and Nancy A. Denton, "Hypersegregation in U.S. Metropolitan Areas: Black and Hispanic Segregation Along Five Dimensions," Demography 26 (August 1989), 374.

21. Nancy A. Denton, "Are African Americans Still Hypersegregated?" pp. 80-81 in Robert D. Bullard, J. Eugene Grigsby, and Charles Lee (eds.), Residential Apartheid: The American Legacy (Los Angeles: CAAS Publications, 1994).

22. The last two measures compare the density of census tracts with black population to the density of blocks with white populations and test whether blacker census tracts are located closer together than whiter census tracts.

23. Douglas S. Massey, "Residential Segregation and Neighborhood Conditions in U.S. Metropolitan Areas," in Neil J. Smelser, William Julius Wilson, and Faith Mitchell (eds.), America Become: Racial Trends and Their Consequences (Washington, D.C.: National Academy Press, National Research Council Commission on Behavioral and Social Sciences and Education, 2001), 410.

24. Iceland et al, Racial and Ethnic Segregation in the United States.

25. The delta index formula is
formula for calculating the delta index
where bi is the black population in census tract i, B is the total black population in the metropolitan area, aiis the land area of census tract i, and A is the total land area in the census tracts of the metropolitan area. Ibid., 122-123.

26. The Census Bureau ranked large metro areas on their segregation of African Americans in the year 2000 only if their total population was at least one million in 1980 and had at least 20,000 blacks (or blacks comprised 3 percent or more of the population) in 1980.

27. The dissimilarity segregation indexes in this report are from the Lewis Mumford Center for Comparative Urban and Regional Research website at mumford1.dyndns.org/cen2000/data.html. The center maintains a website listing its national newspaper coverage at mumford1.dyndns.org/cen2000/news.html.

28. See John Logan et al, "Ethnic Diversity Grows, Neighborhood Integration Lags Behind," (Albany: University of New York, Lewis Mumford Center, April 2001). Online at mumford1.dyndns.org/cen2000/WholePop/WPreport/page1.html.

29. The Mumford Center states that its ranking results "should be interpreted with caution" when the population of blacks or Hispanics is under 50,000 (a condition affecting 226 of its 331 metro area rankings for blacks and 245 of its 331 metro area rankings for Hispanics). According to the Mumford Center, the formulae work for the Asian population unless it is under 20,000, although the mathematical basis for this difference in the formulae's utility is not explained. The Asian-white rankings would be questionable for 260 metro areas under the Mumford Center's "20,000 minimum rule." If a "50,000 minimum rule" were applied, 293 of the 331 Asian-white rankings posted on the Mumford Center website would be questionable. "Metropolitan Area Rankings: Population of All Ages," Mumford Center web page at mumford1.dyndns.org/cen2000/WholePop/WPsort.html, accessed August 8, 2002.

30. "Ethnic Diversity Grows," p.4.

31. When the dissimilarity segregation index is used to rank the four counties in the Milwaukee area on their black-white segregation, Milwaukee County is ranked the "most segregated" with an index of 77.3. The three suburban counties show what is considered only "modest segregation." Ozaukee County has a segregation index of 36.5; Washington County has an index of 35.0; and Waukesha County has an index of 33.0. The City of Waukesha is combined with the City of Milwaukee as the "central cities area" of the Milwaukee MSA in the Mumford calculations. In Waukesha blacks comprise 1 percent of the total population; in the City of Milwaukee, blacks comprise 38 percent of the population.

32. Edward L. Glaeser and Jacob L. Vigdor, Racial Segregation in the 2000 Census: Promising News (Washington, D.C.: The Brookings Institution Center on Urban and Metropolitan Policy, April 2001. Online at www.brook.edu/dybdocroot/es/urban/census/glaeser.pdf.

32. U.S. Census Bureau definitions of regions were used for this report. See, Bureau of the Census, Geographic Areas Reference Manual (Washington, D.C.: U.S. Department of Commerce, November 1994).

34. U.S. Census Bureau, "GCT-PH1 Population, Housing Units, Area, and Density: 2000."


This study was supported in part by a grant from the Helen Bader Foundation. Maps were prepared by Spencer Barnett and John Pawasarat.


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