Racial and Ethnic Integration in U.S. Metropolitan Neighborhoods:
Patterns, Complexities and Consequences
Dissertation
Presented in Partial Fulfillment of the Requirements
for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Diana Leilani Karafin, B.A., M.A.
Graduate Program in Sociology
The Ohio State University
2009
Dissertation Committee:
Lauren J. Krivo, Advisor
Vincent J. Roscigno
Rachel E. Dwyer
Copyright by
Diana Leilani Karafin
2009
Abstract
In my dissertation, I problematize the current framing and understanding of U.S.
racial and ethnic neighborhood integration in an increasingly heterogeneous society.
Research questions and analyses are shaped by contemporary race theories which
emphasize how societal systems, structures, and racial ideologies condition institutions,
outcomes, and a shifting U.S. racial order (Bonilla-Silva 2004; Mills 2004; Omi and
Winant 1994). I examine the often implied, yet rarely empirically validated, proposal
that long-term racial and ethnic neighborhood integration is a primary remedy for the
inequities and deleterious consequences associated with racial residential segregation. I
construct a descriptive and analytical national portrait of the patterns and socioeconomic
consequences of metropolitan neighborhood integration between 1980 and 2000. I
extend existing research by illuminating national patterns that account for Latinos as well
as Blacks and Whites, and by directly comparing neighborhood and group-level
socioeconomic advantage/disadvantage for a range of integrated and homogenous
neighborhood types. Most importantly, I explicitly examine whether Blacks and Latinos
residing in durable integrated contexts appear to be significantly more advantaged than
those situated in long-term, predominantly minority communities.
Using data for neighborhoods embedded within metropolitan contexts from the
Neighborhood Change Database I first assess descriptive patterns of the frequency and
ii
durability of integration in metropolitan neighborhoods over two decades. I employ a
racial/ethnic neighborhood integration typology which more fully incorporates
differential combinations of Latinos, Blacks, Whites, and Others in neighborhoods than
heretofore employed. I find vast differentiation in the frequency, stability, and paths of
change among various types of integrated and homogenous contexts. White, Black, and
Latino neighborhoods remained the norm across the two decades, though the share of
two-group neighborhoods increased from 17.3% to 29.2% (in particular, White-Black,
White-Latino, and Latino-Black neighborhoods). Regarding the question of stability,
White, Black, and Latino neighborhoods were significantly more stable than the
integrated areas. These patterns were further characterized by the concentration of
Whites in White neighborhoods across the two decades, and substantial flux in the
population composition of all neighborhood types.
I then use hierarchical multinomial models to evaluate the relationship between
neighborhood advantage/disadvantage and the odds a neighborhood remained integrated
or became integrated. The results demonstrate that, net of various metropolitan and
neighborhood population and housing characteristics, the most advantaged integrated
contexts were the least stable and the most likely to transition to all White contexts. In
contrast, the most disadvantaged integrated contexts were the most stable, with those that
do change being more likely to transition to predominantly Black or Latino contexts.
When examining the odds a homogenous neighborhood in 1980 became integrated in
2000, the results indicate that more disadvantaged neighborhoods were significantly more
likely to become integrated than less disadvantaged communities.
iii
The final portion of the research asks whether long-term integrated areas, and the
group-members in them, are significantly more advantaged compared to homogenous and
transitioning contexts (and their group members). The central finding is that while
racially stable White-Black areas were significantly less disadvantaged than racially
stable Black areas, the average level of Black advantage in stable White-Black
neighborhoods was significantly less than the average level for those in long-term Black
neighborhoods. In contrast, Latinos had higher levels of advantage in racially stable
White-Latino neighborhoods compared to those in stable majority Latino neighborhoods
(and stable White-Latino contexts as a whole had less disadvantage than long-term Latino
communities). Overall, my results underscore the problematic nature of making a single
generalization of stable racial and ethnic integration as a “success story.” Situating my
findings within the broad urban stratification and race theory literatures, I discuss the
theoretical implications of my findings for understanding the shifting U.S. racial order
and inequality across the residential landscape.
iv
DEDICATION
Dedicated to Nobuo
v
Acknowledgments
First, I would like to acknowledge the person who has played the most important
role in my growth and development during my graduate school tenure, my adviser Lauren
J. Krivo. I would absolutely not be where I am today without Laurie’s willingness to
stand by an eager, yet sometimes wayward and confused, graduate student. My path to
complete graduate school has been neither linear nor traditional, yet Laurie has remained
a steadfast source of support throughout. Along with serving as my adviser, Laurie has
provided me with numerous opportunities that have enriched my experience at Ohio
State. These include hiring me as a research assistant, collaborating with me on a
research project, introducing me to scholars outside of OSU, and inviting me to join the
Racial Democracy, Crime, and Justice Network (with Ruth Peterson).
Regardless of the particular nature of the struggles, questions, or dilemmas I
have faced, Laurie has been reliable in her wisdom, honesty, and encouragement. Laurie
demands excellence in her own work, and does not compromise her standards despite her
many, constant, competing obligations. Laurie is incredibly present in her meetings and
in the level of detail and thought she puts into her feedback. I am grateful for her
willingness to dedicate so much time to my development. She has left an indelible mark
on my life, both personally and professionally. I remain inspired by Laurie’s passion,
vi
generosity, and kindness for those less fortunate than herself. For my dissertation project
specifically, I am thankful for Laurie’s insight, direction, and patience. Laurie has read
countless drafts that have moved the project forward substantially. Thank you, Laurie,
for the sacrifices you have made to help this undeserving graduate student complete her
dissertation.
I am also especially thankful for the opportunity to work with Vincent Roscigno
in the contexts of committee member, collaborator, and informal adviser. In all of these
roles, Vinnie has demonstrated to me the significance of placing research questions and
findings within bigger and broader theoretical contexts. He has challenged me to never
lose sight of the “so what” question regardless of what I am working on. His creativity,
enthusiasm, and willingness to ask the tough questions have played an important role in
shaping this project. I am also grateful for the countless occasions in which Vinnie
shared advice with me about the field and a work-life balance. Thank you, Vinnie, for
your dedication all these years. Thank you, also, for helping me to see that there is a
place for all in sociology (even someone like me).
Rachel Dwyer, also a member of my committee, has played an important role in
the development of my dissertation project. Her insight early on helped me to better
conceptualize my questions, approach, and contributions. Rachel has a keen awareness
of the most relevant theoretical and methodological debates characterizing the residential
segregation and urban sociology literatures. She has graciously shared her insight with
vii
me, prompting me on numerous occasions to re-consider how my own work should
evolve.
I am also extraordinarily indebted to two professors who are not committee
members, Ruth Peterson and Devah Pager. Many years ago, Ruth hired me as a Research
Assistant to work on her edited volume (with Laurie Krivo and John Hagan) The Many
Colors of Crime: Inequalities of Race, Ethnicity and Crime in America (2006). Ruth also
kindly invited me to join the Racial Democracy, Crime, and Justice network of scholars
(with Laurie Krivo). I was lucky to have the opportunity to work closely with Ruth. Her
uncompromising demand for quality, her sharp wit, and her ability to do the impossible
(squeeze 24 hours of work into 8) continue to motivate me. I am thankful Ruth took a
risk and trusted me to work on such an important project so dear to her and Laurie and
John. I continue to benefit from the cumulative advantages resulting from this early
experience. I remain a permanent and proud member of the multitude of “Ruth fans.”
I am incredibly thankful that Devah Pager also took a risk several years back, and
hired me (with Bruce Western) to work as a Research Assistant on a study of
discrimination in the New York City low-wage labor market. I am grateful for the
research skills garnered through this project. I am inspired by her passion in conducting
the most rigorous work and disseminating findings in an accessible fashion to a broad
spectrum of audiences. I am also thankful that Devah graciously provided me with a
“home,” while I worked away from Ohio State for several years, by inviting me to talks,
viii
workshops, and seminars at Princeton, and providing me with office space. I am grateful
that Devah continues to serve as an informal adviser, and has shared thoughtful and
pointed feedback on my own work on numerous occasions. Anyone who has met Devah
instantly recognizes her remarkable energy and zeal for sociology – and it is impossible
not to be impacted for the better.
I would also like to acknowledge Professors Bob Kaufman, Townsand PriceSpratlen, Korie Edwards, Bruce Western, Miles Hewstone, Diana Kendall, Sharon
Collins, Larry Felice, Edward Crenshaw, Robin Batemen-Driskell, and Larry Lyon. Each
played an instrumental role at various points on my journey, starting with my first
exposure to sociology in Larry Lyon’s introductory course back in 1998. Additionally, I
am appreciative of the group of scholars associated with the Racial Democracy, Crime,
and Justice Network. Your passion in the important agenda-setting work you engage in,
and your commitment to helping engender growth for junior scholars, is much
appreciated. You are a remarkable group, and I consider myself a direct beneficiary of
your dedication to the network and its larger cause. I also wish to thank Colin Odden,
Rob Feldman, Jane Wilson, Michelle Blackwell, and Matthew Moffitt for their kindness
in offering technical help and administrative support on many occasions. In particular,
each generously offered assistance often outside of the boundaries of their specific roles
in the department. It was a challenge to manage progress in the program while living in
New York City, and it would not have been possible without them.
ix
In addition to the support of the faculty and staff I have acknowledged above, I
am grateful for my past and present grad school colleagues. First, I am especially
appreciative of the support of Susan Ortiz and Marguerite Hernandez, who formed a
dissertation support group with me. I can’t imagine how I would have ever finished
without their insight and shared resources. In fact, important and dramatic shifts in my
dissertation stemmed directly from conversations from some of our meetings. Second, I
am extremely thankful for Eileen Bjonstrom, who has constantly been there for me this
past year - whether to answer a question, provide a hug, talk through anxious feelings, or
solve a statistical problem. Thank you also to Priyank Shah, Lori Burrington, Valerie
Wright, Heather Washington, Darlene Saporu, Danielle Kuhl, Shelley Pacholok, Sherry
Mong, Melanie Hughes, Jill Harrison, Lisette Garcia, Reggie Byron, and Ryan Light.
Your many smiles, words of encouragement, advice, and generosity made a difference in
my life.
Finally, I wish to personally thank my friends and family. Your affirmation
played a critical role in helping me to keep plugging along during the rough parts of the
process. I love and admire each of you. Thank you to my dear friends Griff Tester,
Alicia Abernathy, Chad Schone, Jack Karner, Aaron Pickering, Kristin Blakely-Kozman,
Scott Dewitt, Anna Zimdars, Dave Reirson, Dave Jacobs, Lucas Mire, Jen Tennant, Sarah
Picard-Fritsche, and Kelly O’Keefe. I also wish to thank Scott Karafin and Mary
Karafin, who have remained enthusiastic, from the beginning, of my goal to earn a Ph.D.
x
Finally, thank you to my parents, Dagmar and Nobuo, for their constant and
unconditional love.
xi
Vita
1996………………………………….. Hawaii Baptist Academy
2000………………………………….. B.A. Sociology, Baylor University
2002………………………………….. M.A. Sociology, Baylor University
2003 to 2005………………………… Graduate Research and Teaching Associate,
Department of Sociology, The Ohio State
University
2005 to 2009………………………… Graduate Research Associate,
Department of Sociology, Princeton University
2007 to 2008………………………… Senior Research Associate, The Center for Court
Innovation, New York, NY
2008 to present……………………… Graduate Research Fellow, Department of
Sociology, The Ohio State University
PUBLICATIONS
Roscigno, Vincent, Diana L. Karafin, and Griff Tester. 2009. AThe Complexities and
Processes of Racial Housing Discrimination.@ Social Problems 56:49-69.
Pager, Devah and Diana L. Karafin. 2009. ABayesian Bigot? Statistical Discrimination,
Stereotypes, and Employer Discrimination.@ Annals of the American Academy of
Political and Social Science 621:70-93.
xii
Karafin, Diana L. 2008. AHousing Audits@ in Richard T. Schaefer (ed.) Encyclopedia of
Race, Ethnicity, and Society. Thousand Oaks: Sage Publications.
Karafin, Diana L. 2008. ACommunity Courts Across the Globe: A Survey of Goals,
Performance Measures, and Operations@ Prepared for and Published by Open
Society Institute for South Africa.
http://www.osf.org.za/File_Uploads/docs/community_court_world_text_web.pdf
Karafin, Diana L. and Vincent J. Roscigno. 2007. AThe Contexts of Housing
Discrimination.@ Pp.153-170 in The Face of Discrimination by Vincent J.
Roscigno. New York: Rowman & Littlefield.
Roscigno, Vincent, Diana L. Karafin, and Griff Tester. 2007. AThe Multidimensional
Nature of Housing Discrimination.@ Pp. 171-186 in The Face of Discrimination
by Vincent J. Roscigno. New York: Rowman & Littlefield.
Krivo, Lauren J., Ruth D. Peterson, and Diana L. Karafin. 2006. "Perceptions of Crime
and Safety in Racially and Economically Distinct Neighborhoods." Pp. 237-255
in The Many Colors of Crime: Inequalities of Race, Ethnicity and Crime in
America, edited by Ruth D. Peterson, Lauren J. Krivo, and John Hagan. New
York: New York University Press.
FIELDS OF STUDY
Major Field: Sociology
xiii
Table of Contents
Abstract ................................................................................................................... ii
Dedication ................................................................................................................v
Acknowledgments.................................................................................................. vi
Vita ........................................................................................................................ xii
List of Tables .........................................................................................................xv
List of Figures ..................................................................................................... xvii
Chapter 1 Introduction .............................................................................................1
Chapter 2 Research and Theory on Race, Residence, and Inequality ...................17
Chapter 3 Data and Methods..................................................................................53
Chapter 4 Patterns and Sources of Change in Racial and
Ethnic Neighborhood Integration .....................................78
Chapter 5 Advantage and Integration for Whites, Blacks, and Latinos...............112
Chapter 6 Conclusion ...........................................................................................155
References ............................................................................................................171
xiv
List of Tables
Table 3.1 Operationalization of All Variables .......................................................73
Table 3.2 Mean and Standard Deviation for All Variables ...................................76
Table 4.1 Distribution of U.S. Metropolitan Racial/Ethnic
Neighborhoods 1980-2000*.................................................................................102
Table 4.2 Total Percentage of Individual Whites, Blacks, and
Latinos Represented in Each Neighborhood Type -1980 and 2000 ....................103
Table 4.3 Transition Matrix: U.S. Neighborhood Racial
Composition 1980-2000.......................................................................................104
Table 4.4 Median Metropolitan Neighborhood Population Size and
Change in Racially Stable Neighborhoods Between 1980 and 2000 ..................105
Table 4.5 The 1980 Socioeconomic Classification of Racially
Durable Neighborhoods between 1980 and 2000 ................................................106
Table 4.6 Multinomial Hierarchical Linear Model Predicting
1980 to 2000 U.S. Metropolitan Black-White Integrated Neighborhood
Change (Remained integrated is the reference category) ....................................107
Table 4.7 Multinomial Hierarchical Linear Model Predicting
1980 to 2000 U.S. Metropolitan Latino-White Integrated Neighborhood
Change (Remained integrated is the reference category) ....................................108
Table 4.8 Multinomial Hierarchical Linear Model Predicting
1980 to 2000 U.S. Metropolitan White Homogenous Neighborhood
Change (Remained White is the reference category) ..........................................109
Table 4.9 Multinomial Hierarchical Linear Model Predicting
1980 to 2000 U.S. Metropolitan Black Homogenous Neighborhood
Change (Remained Black is the reference category) ...........................................110
xv
Table 4.10 Full Transition Matrix: U.S. Neighborhood Racial
Composition 1980-2000.......................................................................................111
Table 5.1 Socioeconomic Stability and Change for Racially Durable
Neighborhoods between 1980 and 2000 ..............................................................139
Table 5.2 Coefficients and Standard Errors for Key Independent
Variables from Hierarchical Linear Models Predicting 2000 Concentrated
Disadvantage for 1980 White, Black, Latino, White-Black,
White-Latino, and Latino-Black Neighborhoods ................................................140
Table 5.3 Independent Controls and Intercepts for Hierarchical Linear
Models Predicting 2000 Concentrated Disadvantage for 1980 White, Black,
Latino, White-Black,White-Latino, and Latino-Black Neighborhoods...............141
Table 5.4 Hierarchical Linear Models Predicting 2000 White Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ...........146
Table 5.5 Hierarchical Linear Models Predicting 2000 Black Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ...........147
Table 5.6 Hierarchical Linear Models Predicting 2000 Latino Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ...........147
Table 5.7 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups – Predicting 2000 White Advantage ......................................152
Table 5.8 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups – Predicting 2000 Black Advantage ......................................153
Table 5.9 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups – Predicting 2000 Latino Advantage .....................................154
xvi
List of Figures
Figure 2.1 An Institutional-Level Framework of Racial Stratification..................51
Figure 2.2 A Critical Race Framework of Racial Stratification ............................51
Figure 2.3 Map of Tri-Racial System in the United States ....................................52
Figure 5.1 Levels of 2000 Concentrated Disadvantage for Racially
Stable and Transitioning Neighborhoods Between 1980 and 2000 .....................138
Figure 5.2 Predicted Levels of 2000 Concentrated Disadvantage for
Racially Stable and Transitioning Neighborhoods between 1980 and 2000 .......142
Figure 5.3 Levels of 2000 White Advantage in Racially Stable and
Transitioning Neighborhoods Between 1980 and 2000.......................................143
Figure 5.4 Levels of 2000 Black Advantage in Racially Stable and
Transitioning Neighborhoods Between 1980 and 2000.......................................144
Figure 5.5 Levels of 2000 Latino Advantage in Racially Stable and
Transitioning Neighborhoods Between 1980 and 2000.......................................145
Figure 5.6 Predicted Levels of 2000 White Advantage in Racially
Stable and Transitioning Neighborhoods Between 1980 and 2000 .....................149
Figure 5.7 Predicted Levels of 2000 Black Advantage in Racially
Stable and Transitioning Neighborhoods Between 1980 and 2000 .....................150
Figure 5.8 Predicted Levels of 2000 Latino Advantage in Racially
Stable and Transitioning Neighborhoods Between 1980 and 2000 .....................151
xvii
Chapter 1
Introduction
“The problem of the twenty-first century will be the problem of color-blindness-the
refusal of legislators, jurists, and most of American society to acknowledge the causes
and current effects of racial caste and to adopt remedial policies to eliminate them.” –
Bryan Fair 1997
“It is paradoxical to say it, but the success of Barack Obama frightens Black people
almost as much as it excites us… If America really is so bad, then one has to ask: How
does a Black man get to be the Democratic nominee for President of the United States?
What Black folks fear is that a monumental success for one Black man might
simultaneously become a setback for the whole race…If Obama becomes the president,
every remaining, powerfully felt Black grievance and every still deeply etched injustice
will be cast out of the realm of polite discourse. White folks will just stop listening.” –
Lawrence Bobo 2008
1.1 An Historic Moment
Following the recent election of Barack Obama as the the 44th president of the
United States, a reporter for the New York Times declared Obama’s victory “…[swept]
away the last racial barrier in American politics with ease as the country chose him as its
first Black chief executive” (Nagourney 2008). In the ensuing months, a similar
sentiment was expressed across massive amounts of print and virtual space dedicated to
commentary of the 2008 election results and 2009 inauguration. Television, newspapers,
and internet blogs portrayed a clear message - the election of an African American for the
highest office in the land was a historic event symbolizing the strides made in race
1
relations in the post-civil rights era. Even David Allan Grier, the host of the comedy
central show Chocolate News, exclaimed in his opening monologue following the
election, “Holy shit! Did we just elect Barack Obama President of the United States? I've
got to be honest America, I didn't think you had it in you.” Amidst the speculation and
ultimate celebration of the Obama win dominating U.S. media, a contrasting conversation
was concurrently taking place with a markedly different tone. Though receiving much
less media attention, a group of individuals, academics, and leaders in the Black
community expressed deep concern over potential negative consequences of Obama’s
victory for race relations and the fight for racial justice (Bonilla-Silva 2008; Swarns
2008). In particular, they predicted an Obama win would cement an already widely held
belief in the minds of the majority of the public and the political elite that racial injustice
and discrimination no longer serve as major barriers for Blacks in America, and any
remaining inequality must be attributed to the individual (Hunt 2007). In turn, this would
further hinder ongoing efforts to silence academic and activist calls for recognition of the
consequences of historic, current, and evolving structural and institutional forms of
racism embedded in the organizations, policies, systems, neighborhoods, and institutions
that characterize the United States (Mills 2004; Bonilla-Silva 2003; Omi and Winant
1994; Krysan and Lewis 2004). As one voice representing this perspective, Harrison, a
sociologist at Howard University, stated on the eve of the Obama inauguration, “Historic
as this moment is, it does not signify a major victory in the ongoing, daily battle” (cited
in Swarns 2008). How can meaningful progress in the “daily battle” of racial injustice
take place if the American public and the political elite see the Obama victory as
2
confirmation that race no longer matters in America? And what exactly is this “daily
battle?”
We know from decades of social science research that both the celebratory and
concerned conversations over the Obama win took place and continue within a broader
U.S. social context characterized by tremendous racial and ethnic inequality. Racial and
ethnic groups experience differential access to jobs, housing, wealth accumulation,
health, neighborhoods, education, the administration of justice, and punishment (e.g.,
Krivo and Peterson 1996; Oliver and Shapiro 1995; Massey and Denton 1993; Western
2005; Pager 2008; Pager and Karafin 2008; Yinger 1995). It is clear that civil rights
legislation alone did not eradicate the historical remnants, nor prevent new and evolving
forms, of racial injustice in the United States. Though scholars continue to debate
whether the sources of these inequities are rooted in individual or structural processes, a
prominent argument is that one of the most critical sources of racial inequality in the
United States is racial residential segregation (e.g., Du Bois 1903/1990; Myrdal
1944/1972; Pettigrew 1979; Bobo 1989; Massey and Denton 1993; Cutler and Glaeser
1997; Yinger 1995; Ellen 2000; Charles 2003, 2006). Although theoretical reasons vary
as to why racial residential segregation is the crucial link,1 the underlying assertion is the
same – racial inequality in housing, employment, education, and the like are all important
consequences of a highly racially and ethnically segregated U.S. residential landscape.
1
Some see the problem with residential segregation as rooted in social-psychological processes – that
physical separation breeds prejudice and contempt for outgroups. Demographic integration is seen as
necessary to foster more meaningful social integration between groups (e.g., DuBois 1903/1990; Smith
1998; Ford 1972; Helper 1979; Williams 1964; Demarco and Galster 1993; Galster 1992; Pettigrew 1973;
Allport 1954). Others emphasize the disparity in social characteristics and resources associated with
various racially segregated neighborhoods as the real problem – in particular those with large proportions
of African Americans (e.g., Massey and Denton 1993; Wilson 1987,1996; Cutler and Glaeser 1997; Krivo
and Peterson 1996; Crane 1991).
3
Given such a connection, substantial reductions in racial and ethnic residential
segregation, or increases in racial and ethnic integration, are expected to serve as the
catalyst for reductions in inequality across employment, health, housing, education, and
other domains. Not surprisingly then, a push for steady neighborhood integration is the
de facto public policy solution suggested in a large number of studies (e.g., Massey and
Denton 1993; Yinger 1995; Charles 2003, 2006; Galster 1987; Ellen 2000; Smith 1998;
Maly 2000; Oliver and Shapiro 1995; Nyden, Maly, and Lukehard 1994; Cutler and
Glaeser 1997; Farley et. al. 1979).
In this dissertation, I problematize the assertion that racial and ethnic residential
integration will solve the problem of U.S. racial inequality. I question the validity of the
presumed positive relationship between racial residential integration and greater racial
and ethnic equality. Specifically, I empirically assess the assumption that stable2
racially/ethnically integrated neighborhoods provide socially and economically superior
contexts, compared to homogenous and transitioning contexts, for historically
subordinated group members such as Blacks and Latinos. Furthermore, I assess group
levels of advantage and disadvantage across transitioning and non-transitioning
neighborhood contexts. My key hypothesis is that Blacks and Latinos in racially durable
integrated neighborhoods may not always have significantly higher mean levels of
advantage compared to Blacks and Latinos in other homogenous or transitioning areas.
2
In this and subsequent chapters, I use the terms “stable” or “durable” or “non-transitioning” to describe
neighborhoods that maintain similar proportions of various racial and ethnic groups over time. Conversely,
I use the term “transitioning” or “unstable” to refer to neighborhoods that experience a high proportion of
change in representation of one or more racial or ethnic groups (so much so, that the neighborhood “color”
changes). These concepts are developed and explicated further in Chapters 2 and 3.
4
This contention draws from theoretical arguments about the nature of racial inequalities,
which I explain below.
Some recent race theory posits that processes shaping demographic, economic,
and social change are conditioned by a system of White supremacy characterizing the
larger society (Bonilla-Silva 2001, 2004; Bobo 1997; Omi and Winant 1994). They
argue that while the nature of how race operates in the U.S. has changed over time, its
role in the racialized social order remains the same – to maintain White privilege.
Furthermore, racial theorists describe the current U.S. racial ideology as “laissez-faire
racism” (Bobo 1997; Bobo 2004) and “color-blind racism” (Bonilla-Silva 2004; Omi and
Winant 1994). A central point is that the current ideology denies the presence of
systemic, institutional, and structural forms of racism that continue to create and maintain
racial inequality. These systems and structures promote a hierarchical privileging of
Whites over non-White groups in differential ways across space and time (e.g., Bobo
2004; Bonilla-Silva 2001; Iceland and Nelson 2008; Sharkey and Sampson 2008; Zhou
1997; Alba and Nee 1997; White and Sassler 2000).
The ideology also rejects racism and discrimination as contemporary barriers for
historically subordinated groups. Rather, an emphasis on individualism is the norm. The
larger public sentiment is that racially targeted policies are inappropriate and unfair in an
era where race no longer matters (Bobo and Kluegel 1993; Omi and Winant 1994).
Indeed, a majority of Americans provide individualist responses when asked to explain
why racial and other forms of inequality exist (Hunt 2007; Schuman and Krysan 1999;
Kluegel and Smith 1995; Bobo 2004).
5
The key problem is that significant racial inequalities remain, yet within a
societal context where race is no longer recognized as salient in the lives of individuals
and groups (Bonilla-Silva 2004). Racial hierarchies are thus maintained without direct
acknowledgment of race, in a political climate that silences racial discourse (BonillaSilva 2004). My dissertation problem stems directly from these theoretical arguments as
they pertain to race and residence in the urban landscape. Specifically, processes such as
residential segregation and integration and their associated patterns and consequences,
occur within a racialized context of colorblind ideologies and structural, systemic racism.
In light of this broader context, an empirical validation is necessary of the assumption
that stable neighborhood integration is more beneficial, compared to other contexts, for
historically subordinated group members such as Blacks and Latinos. Regardless of the
racial or ethnic composition of neighborhoods and how this changes (or not) over time, I
expect patterns to largely reflect the advantaging of Whites over Latinos and Blacks.
Patterns of social and economic disparities across neighborhoods and the groups within
and across them will likely mirror the larger racialized social order of the United States
with Whites the most advantaged, Blacks the most disadvantaged, and Latinos
somewhere in between. If this is the case, singular emphasis on policies to promote
racial and ethnic integration as a mechanism to diminish inequality may be misguided.
1.2 Race and Residence in America
Since the landmark publication of Massey and Denton’s American Apartheid in
1993, racial residential segregation between Blacks and Whites has been a defining facet
of urban, race, and poverty scholarship. The substantial literature on this topic delineates
6
demographic patterns, causes, and consequences of racial residential segregation in the
United States (Massey and Denton 1993; Lee et. al 2008; Iceland 2004; Farley and Frey
1994; Wilkes and Iceland 2004; Fischer et. al. 2004; Krivo et. al. 1998; Charles 2003).
Despite on-going discussions about the measurement of segregation (see Lee et. al. 2008;
White, Kim, and Glick 2005), a general picture of patterns and shifts in levels of
residential segregation between Whites, Blacks, Latinos, and Asians is clear.
By and large, scholars concur that levels of segregation between Blacks and
Whites are modestly declining but remain disproportionately high (Iceland 2009; Charles
2003). Segregation levels between Latinos and Whites and Asians and Whites are lower
yet are modestly increasing (Charles 2003). Despite on-going debates about the relative
significance of mechanisms perpetuating segregation (Dawkins 2004; Charles 2003;
Quillian 2002), processes related to group preferences, housing discrimination, and
economic inequalities are posited as responsible for these patterns (Charles 2003; Yinger
1995; Massey and Denton 1993; Krysan 2000; Farley and Frey 1994).
Most importantly, sociology has implicated residential segregation as a primary
barrier to racial and ethnic equality in housing, education and economic status, and as a
source of prejudice, stereotypes, and out-group hostility (Du Bois 1903; Myrdal 1944;
Pettigrew 1979; Farley et. al. 1979; Bobo 1989; Massey and Denton 1993; Wilson 1987;
Oliver and Shapiro 1995; Cutler and Glaeser 1997; Charles 2003; Allport 1954; Pettigrew
1973; Blau 1977; Smith 1998; Massey et. al. 1999; Quillian and Pager 2005). Scholars
have paid particular attention to the negative consequences of racial residential
segregation for Blacks in highly segregated Black neighborhoods. Black contexts are
often severely disadvantaged, and many argue this significantly impacts the life chances
7
of residents given the serious social problems within these contexts (Charles 2003; Cutler
and Glaeser 1997; Krivo and Peterson 1996; Massey and Denton 1993; Crane 1991;
Wilson 1987). Cutler and Glaeser (1997) estimate that just a one standard deviation drop
in levels of racial residential segregation between Blacks and Whites would reduce by
one-third Black-White inequality in high school completion rates, single-parenthood,
employment, and income. Some recent research suggests the consequences of
segregation may extend beyond segregated neighborhoods themselves. Krivo, Peterson,
and Kuhl (2009) use violent crime as a case in point and demonstrate that all
neighborhoods within highly segregated cities are impacted by deleterious consequences
associated with high levels of city wide segregation.
It is not surprising then that desegregation and a push for stable neighborhood
integration is the public policy solution suggested in the conclusion and discussion
sections of many studies (e.g., Massey and Denton 1993;Yinger 1995; Charles 2003,
2006; Galster 1987; Ellen 2000; Friedman 2007). Some explicitly frame integration as
the policy goal. For example Charles refers to integrated neighborhoods as “success
stories” and advocates programs that “support stable integration” and encourage Whites
to enter diverse neighborhoods and Blacks to enter White neighborhoods (2003:200).
Others indirectly suggest integration is the obvious solution to problems emanating from
segregation. For example, Quillian (2002) argues that eliminating discrimination alone
will not entirely reduce segregation, as White avoidance of integrated neighborhoods is
also a key process in perpetuating Black-White segregation (see also Ellen 2000).
Though he never directly states that integration should be a goal, his emphasis on the
8
need to understand all the processes at play that prevent declines in segregation may
imply this is the case.3
In proposing stable racial and ethnic integration as a policy solution, whether
explicitly or indirectly, the presumption is that the quality of previously segregated
minority neighborhoods will improve as segregation and its associated consequences
disappear. Most importantly, individual life chances for historically subordinated group
members are expected to improve given the compelling research indicating
neighborhoods affect individual health, family structure, labor-market outcomes,
participation in crime, and so on (e.g., Sampson et. al. 2002; Duncan and Raudenbush
2001).
With the common framing of neighborhood integration as a primary solution for
the racial inequality problem, a burgeoning interest to study neighborhood integration has
emerged over the last few decades. However, in stark contrast to the residential
segregation scholarship, the current state of knowledge pertaining to the magnitude of
U.S. neighborhood integration is not characterized by any kind of consensus. The
handful of existent studies provides conflicting conclusions. Though most agree racial
and ethnic neighborhood integration is increasing to some degree, there is no agreement
about how much it has increased and to what degree integrated neighborhoods ultimately
transition or remain integrated over the course of several decades. Some conclude that
integration is increasingly stable (Ellen 2000; Rawlings et. al. 2004), while others
3
I believe indirect framing of integration as a goal is quite common in the residential segregation literature.
Whether examining patterns of segregation over time or specific processes that perpetuate patterns, it is
extremely common for researchers to claim their work is important because of all the negative
consequences associated with segregation (for example, see Farley and Frey 1994; Charles 2003; Logan,
Stults, and Farley 2004; Crowder and South 2008).
9
conclude integrated contexts are predominantly unstable and likely to transition to
homogenous contexts over time (Friedman 2007; Swaroop 2005). Furthermore,
significant emphasis in this literature is placed on identifying factors that seem to foster
racial and ethnic stability in integrated neighborhoods (e.g., Nyden, Maly, and Lukehart
1997; Peterman and Nyden 2001; Ellen 2000; Swaroop 2005) instead of first assessing
the consequences associated with integration for majority and subordinated group
members. This is surprising, as it would make sense to understand the particular
outcomes and consequences associated with a process before focusing on the factors that
will help support the process, and that may ultimately shape social policies.
Our current understanding of basic patterns and consequences of racial and ethnic
neighborhood integration in the United States remains hazy. It is clear that we need an
assessment of national patterns of integration, and the consequences of these patterns for
majority and subordinate group members over time. Furthermore, the existent work does
not consider how macro patterns are situated within a racialized societal context. Both
theoretical and empirical consequences result. Theoretically, this is consequential as
neglecting the broader racialized context in which processes and outcomes occur may
mean both our questions and answers pertaining to the sources, costs, and solutions for
inequality lack validity. Empirically, this is consequential as we continue to fail to
understand how actual patterns, processes, and consequences of neighborhood integration
play out. This is especially problematic if scholars and politicians continue to advocate
for policies that promote racial and ethnic neighborhood integration as one mechanism to
reduce inequality between majority and subordinated groups. This dissertation seeks to
take an initial step to add clarity to our understanding by detailing a national portrait of
10
patterns and consequences of racial and ethnic neighborhood integration that addresses
some of the major weaknesses characterizing the current literature. I detail the specific
gaps below, and identify the three major dissertation questions and associated analyses
employed to expand our understanding of inequality across the racial residential United
States landscape.
1.3 Dissertation Questions
Patterns of Neighborhood Racial Integration and Change
Current estimates of national patterns of neighborhood integration are not reliable
given a handful of empirical shortcomings. First, I am aware of only four national
studies of neighborhood integration. However, these range in scope from a focus on
between just 10 and 69 metropolitan areas (Friedman 2007; Rawlings et. al. 2004;
Fasenfest et. al. 2004; Ellen 2000). The majority of neighborhood integration studies
focus on much smaller samples, such as communities within a single metropolitan area, a
dozen neighborhoods, or even a single neighborhood (e.g., Maly 2002; Peterman and
Nyden 2001; Smith 1998; Nyden, Maly, and Lukehart 1997; Galster 1998). Furthermore,
all of these studies vary in the time period in which patterns are examined (from a crosssectional approach to an examination of patterns over two decades). This geographic
and temporal variation makes comparisons across studies virtually impossible. To further
complicate matters, the use of divergent definitions of integration is quite common across
these studies. Many focus on just Whites and Blacks, lumping Latinos and Asians and all
others with Whites, or sometimes as a separate “Other” category. I argue these
11
definitions are overly-simplistic and lack specificity by failing to differentiate Latinos
from other groups. This problem, coupled with the other gaps highlighted above, means
that conclusions across these studies lack generalizability, and we do not yet have a clear
understanding of basic, national patterns of racial and ethnic integration in the United
States.
Dissertation Question 1: What are the patterns of neighborhood level
racial/ethnic integration and change in the United States between 1980 and
2000?
The answer to the first dissertation question will provide a simple portrait of
patterns of racial and ethnic neighborhood integration. I examine the proportion of
neighborhoods in 1980, 1990, and 2000 that were racially homogenous, raciallyethnically integrated, and the degree to which these neighborhoods remained
homogenous or integrated across the decades. For transitioning neighborhoods, I also
assess which forms of change were most common. Finally, I contextualize the
neighborhood-level patterns by examining the proportion of individuals from racial and
ethnic groups that reside in the neighborhoods, and the degree to which population shift
occurred within the neighborhoods.
I improve upon existent “national” studies by assessing patterns across the full
spectrum of metropolitan census tracts in the United States, incorporating a truly national
sample.. Furthermore, I develop and employ a 15-group racial and ethnic neighborhood
typology that allows for greater specificity in variation of patterns and outcomes across
groups than allowed for in other definitions used in previous research. This typology is a
first step in moving the literature forward by differentiating among Latinos, Whites,
12
Blacks, and Others, and the multiple possible ways these groups may or may not share
neighborhood space.
Social and Economic Consequences of Racial and Ethnic Integration
The second set of dissertation questions seek to address the theoretical
shortcoming of the current segregation/integration work articulated in the sections above.
Namely, the existent work fails to acknowledge how demographic, social, and economic
neighborhood patterns related to integration and change occur within a larger racialized
U.S. social order. The current work operates from an implicit assumption that
neighborhood integration in and of itself is more beneficial for Blacks and Latinos than
segregated or transitioning contexts. Instead of asking whether or not this is the case,
researchers bypass these questions, and emphasize the need to identify factors that foster
long-term racial and ethnic neighborhood integration. This theoretical limitation is
serious in light of the largely uncontested push for greater racial and ethnic neighborhood
integration in the United States. I contend it is premature to frame all cases of stable
integration as a success.4 When people refer to stable integration as a “rare success
story,” I argue they are assuming that stable racial/ethnic integration translates into
socially and economically superior neighborhood contexts for residents. We do not know
if, how, and when various integrated neighborhoods with historically subordinated group
4
Certainly, some may argue that racial and ethnic neighborhood integration should be a goal for society
regardless of associated consequences or outcomes. These arguments can stem from a philosophical
standpoint, that racial and ethnic neighborhood integration is morally right. Additionally, the potential
social psychological benefits of neighborhood integration for inter-group relations may be emphasized.
Some argue that spatial integration fosters greater social integration and social cohesion between groups
(e.g., see Smith 1998) - via inter-group contact within shared space in neighborhoods –and that these
interactions may help diminish prejudice and stereotypes held by Whites (Deutsch and Collins 1951; Ford
1973; Hamilton and Bishop 1976; Roginson and Preston 1976; Sigelman and Welch 1993; Smith 1994;
Wilson 1996). Along these lines, Ellen (2000:159) argues that even if the negative consequences
associated with segregation disappeared, “the simple fact of racial isolation may be detrimental in that it
fosters racial prejudice.”
13
members (those more likely to experience the negative consequences of residential
segregation) offer more advantaged social and economic climates than other homogenous
or integrated alternatives. I address these issues through two additional research
questions.
Dissertation Question 2: Are neighborhoods that are racially/ethnically stable
over the 1980 to 2000 period more advantaged contexts for historically
subordinated groups than alternative homogenous and transitioning contexts?
This question seeks to ascertain how racially/ethnically stable integrated
neighborhoods compare with homogenous and transitioning areas along indicators of
social and economic advantage and disadvantage. Descriptive analyses delineate the
most advantaged and disadvantaged contexts for majority and subordinated groups.
Analytical models estimate the relationship between racial and ethnic stability and
advantage and disadvantage, net of important metropolitan and neighborhood level
factors. The key question of interest is an assessment of the assumption that long-term
integrated neighborhoods are more advantaged contexts than minority homogenous or
transitioning areas. This question fills a significant gap in the current literature by
explicitly comparing concrete social and economic outcomes between integrated and
homogenous contexts across two decades.
Dissertation Question 3: Are historically subordinated group members in
racially/ethnically stable integrated neighborhoods more advantaged than
members of subordinate groups in homogenous and transitioning contexts?
The third major dissertation question shifts the empirical focus to the social and
economic characteristics of majority and subordinated group members as opposed to
neighborhoods. Here, I assess descriptively and analytically whether economic and
14
social characteristics for Whites, Blacks, and Latinos are higher in 2000 in stable
racially/ethnically integrated contexts compared with transitioning integrated contexts
and stable homogenous contexts.
1.4 Organization of Dissertation
The goal of this project is to move forward our understanding of how
neighborhood characteristics and change are conditioned by the larger racialized social
order of the United States, and specifically how this may be differentially consequential
for neighborhoods with Whites, Blacks, and Latinos. While I cannot test directly how the
racialized system and dominant racial ideology impact neighborhoods and groups, I can
take a first step in accruing empirical evidence of these processes. In Chapter 2, I review
the urban and race literatures as they pertain to racial residential segregation and
neighborhood change. I assess the empirical and theoretical shortcomings of this work.
I also delineate pertinent race theory to develop a critical race account of neighborhood
racial and ethnic composition and change that is situated within the context of a racialized
society. Chapter 3 consists of a detailed explication of data, operationalization of
measures, and overall discussion of my analytic strategy. I develop a 15-group
neighborhood typology which more fully incorporates differential combinations of
Latinos, Blacks, Whites, and Others than heretofore employed. Chapter 4 presents a
detailed portrait of overall national patterns of integration and change in the United States
between 1980 and 2000. In Chapter 5, I compare the social and economic features of
integrated and homogenous neighborhoods, examining whether or not integrated
neighborhoods with Blacks and Latinos are more advantaged than homogenous and
15
transitioning contexts. I also assess whether race-specific indicators of social and
economic advantage and disadvantage are higher in stable integrated neighborhoods.
Finally, in Chapter 6, I summarize the findings and discuss their implications for
sociology and public policy. More broadly, I situate my findings within the broad urban
stratification and race theory literatures, discussing the theoretical implications of my
findings for understanding the shifting U.S. racial order and inequality across the
residential landscape.
16
Chapter 2
Research and Theory on Race, Residence, and Inequality
2.1 Introduction
In this chapter, I review existent scholarship on race and residence in America,
focusing specifically on work pertaining to patterns, sources, and consequences of racial
and ethnic segregation and integration in neighborhoods. The overarching purpose of the
chapter is to develop my dissertation problem – the research questions and my theoretical
expectations - through a discussion of the empirical and theoretical shortcomings in our
current knowledge.
I begin by reviewing the extensive racial residential segregation literature; the
patterns, sources, and consequences of the spatial grouping of individuals in the
metropolitan urban landscape by color and class. Next, I show how racial and ethnic
neighborhood integration is consistently framed in the segregation literature as an
obvious solution for the problems associated with high levels of segregation between
Blacks and Whites, and Latinos and Whites. I discuss a small yet burgeoning literature
aimed at identifying trends and stabilizing factors for the long-term integration of racial
and ethnic minorities and Whites in neighborhoods. I highlight the serious empirical and
theoretical shortcomings of this work, as a result arguing that the framing of integration
17
as a solution, may be premature. I contend that we must first acquire a comprehensive
understanding of the patterns and consequences associated with cases of long-term
neighborhood integration, as they actually play out nationally, in neighborhoods that are
situated within a broader racialized social order. What are the processes responsible for
fostering or dismantling integration? What are the associated social and economic
consequences for groups residing in long-term racially/ethnically integrated
neighborhoods?
I draw on contemporary race theory, in particular the work of scholars such as
Mills (2004), and Bonilla-Silva and Glover (2004), to set forth a critical race approach to
the examination of patterns and consequences of neighborhood integration. According to
this orientation, prime social goods, resources, and rewards continue to be allocated to
Whites given structures set in place by a broader system of White supremacy (Mills
1997; Bonilla-Silva 2001; Bonilla-Silver and Glover 2004). This system shapes all major
societal social structures and institutions. Though the structures and institutions shift
dramatically over time in appearance and form, their function remains the same - to
create and protect White privilege regardless of the consequences for other racial and
ethnic groups. Within the context of the institution of housing, and with regard to racial
and ethnic integration specifically, I argue that this means that the advantaging of Whites
over non-Whites will be apparent, regardless of the racial or ethnic make-up and
durability (or not) of the particular neighborhood context. If true, this may cast serious
doubt on the potential role of long-term racial and ethnic integration in neighborhoods as
a promising solution to the inequitable consequences associated with racial residential
segregation.
18
2.2 Historical and Contemporary Patterns of Race and Residence in America
Racial and ethnic residential segregation, particularly between Blacks and Whites,
remains a persistent feature of U.S. society, despite passage of the Fair Housing Act over
40 years ago. A substantial literature delineates demographic patterns and causes of
racial residential segregation in the United States (Massey and Denton 1993; Lee et. al
2008; Iceland 2004; Farley and Frey 1994; Wilkes and Iceland 2004; Fischer et. al. 2004;
Krivo et. al. 1998; Charles 2003). The most recent analyses of 2000 Census data reveal
that, though Black-White segregation has decreased modestly between 1990 and 2000,
for the most part, Blacks and Whites remain highly residentially segregated from each
other. Indeed, in 25 of the 50 largest metropolitan areas in the U.S., Blacks are extremely
segregated from Whites (Iceland 2009; Wilkes and Iceland 2004; Charles 2003).
Metropolitan areas that have experienced the greatest declines in Black-White
segregation tend to be younger, located in the South or West, have growing housing
markets, and smaller Black populations (Iceland 2009; Farley and Frey 1994). LatinoWhite and Asian-White residential segregation rates actually increased between 1990 and
2000, though they are still significantly lower than those between Blacks and Whites
(Charles 2003). Why are neighborhoods in the United States predominantly racially
segregated? Scholars have grappled for some time with explanations of the patterns
noted above, ranging from arguments about economic constraints of groups, to residential
preferences, and persistent discrimination in the housing market (for a helpful review of
this literature and the competing evidence, see Charles 2003, 2006; Dawkins 2004;
Quillian 2003; Iceland 2009). Others have focused on continuing to work toward
19
methodological advances in measuring segregation (see Lee et. al. 2008; White, Kim, and
Glick 2005).
Why are these patterns and questions important for social scientists to consider?
First, we know that Black segregated neighborhoods are often severely disadvantaged
compared to other contexts, and that this may significantly impact the life chances of
residents given the serious social problems associated with residence in disadvantaged
contexts (Charles 2003; Cutler and Glaeser 1997; Krivo and Peterson 1996; Massey and
Denton 1993; Crane 1991; Wilson 1987). Some recent research suggests the
consequences of segregation may extend beyond segregated neighborhoods themselves.
For example, Krivo, Peterson, and Kuhl (2009) use violent crime as a case in point to
demonstrate how all neighborhoods within highly segregated cities are impacted by
deleterious consequences associated with the most segregated neighborhoods in those
cities.
Second, persistent patterns of racial residential segregation and their associated
consequences are considered important because social scientists have argued for decades
that racial residential segregation is the “structural lynchpin” that maintains racial and
ethnic inequality (Charles 2006:39). Segregation is seen as the final, primary barrier to
racial and ethnic equality across economic, housing, education, wealth, and health
domains, and as a source of prejudice, stereotypes, and out-group hostility (Du Bois
1903; Myrdal 1944; Pettigrew 1979; Farley et. al. 1979; Bobo 1989; Massey and Denton
1993; Wilson 1987; Oliver and Shapiro 1995; Cutler and Glaeser 1997; Charles 2003;
Allport 1954; Pettigrew 1973; Blau 1977; Smith 1998; Massey et. al. 1999; Quillian and
Pager 2005). As a result, of the negative consequences associated with segregation, and
20
the theoretical arguments about its role in perpetuating other forms of inequality beyond
those related to housing, it is not surprising that a push for long-term neighborhood
integration is the de facto public policy solution suggested in the conclusion and
discussion sections of many segregation studies (e.g., Massey and Denton 1993;Yinger
1995; Charles 2003, 2006; Galster 1987).
2.3 The Framing of Integration as a Public Policy Solution
To address the problems that arise from segregation, some explicitly frame
integration as an obvious goal (e.g., Friedman 2007; Ellen 2000; Nyden, Maly, and
Lukehart 1997; Rawlings et. al. 2004). For example Charles refers to integrated
neighborhoods as “success stories” and advocates programs that “support stable
integration” and encourage Whites to enter diverse neighborhoods and Blacks to enter
White neighborhoods (2003:200). Similarly, in a recent research note on neighborhood
integration, Samantha Friedman (2007:12) states:
Future research should be devoted to learning exactly what makes a
mixed-race neighborhood remain that way over a span of several decades. Only
when we have that kind of information can we establish policies that will help us
replicate such success stories. It is then that we can have real optimism for the
future of racial integration.
Others indirectly imply integration is the obvious goal when discussing how their
work is useful in understanding how to curtail segregation. For example, Quillian (2002)
argues that eliminating discrimination alone will not entirely reduce segregation, as
White avoidance of integrated neighborhoods is also a key process in perpetuating BlackWhite segregation (see also Ellen 2000). Indirect framing of integration as a goal is quite
common in the residential segregation literature. Whether examining patterns of
21
segregation over time or specific processes that perpetuate patterns, it is common for
researchers to claim their work is important because of all of the negative consequences
associated with segregation (for example, see Farley and Frey 1994; Charles 2003;
Logan, Stults, and Farley 2004; Crowder and South 2008). Whether they mention
integration or not, to state that we need to diminish segregation because of the negative
consequences may be equivalent to saying we need to increase integration because of the
positive consequences. However, first we need to have a clear sense of whether or not
these positive consequences exist, as I argue in the remainder of this chapter. It is
important to be very clear that I am not simply arguing for maintaining segregation.
Rather, as I explain in the remainder of the chapter, I am skeptical that just diminishing
segregation within the racialized society as it exists would not necessarily have the
positive outcomes implied.
Why has it become so common for much of the residential segregation
scholarship to imply, whether explicitly or implicitly, that integration is the solution?1 I
argue this stems from the overwhelming tendency of this literature to predominantly
focus on one part of the segregation story in the United States – aggregate patterns,
consequences and causes of Black-White segregation over time.2 A tendency to focus on
1
However, several recent studies do highlight potential problems with framing neighborhood integration as
a universally beneficial process for neighborhoods and/or individuals. For example, Dawkins argues public
policies that encourage neighborhood integration should only be pursued when “the social costs associated
with living in segregated contexts exceeds…..the perceived benefits from having same-race neighbors”
(2004:396). Fasenfest, Booza, and Metzger (2004) suggest that integrated neighborhoods should be
encouraged as long as they are economically viable, and indicate many gaps remain in our understanding of
the true nature of integration across the diverse residential landscape of metropolitan America. Farley et.
al. argue integration should be a policy focus as long as “residential segregation impedes equal access to
educational and employment opportunities” (1979:98).
2
Some may argue this is understandable, if not necessary. We know segregated Black contexts are
extremely disadvantaged relative to Latino, Asian, and White segregated contexts. Given the contention,
and accumulated evidence, that Black-White segregation in particular remains a dominant force that
maintains Black-White inequality, a focus on the causes and consequences of Black-White segregation
22
the most disadvantaged form of segregation and its role in maintaining broader inequality
naturally encourages a de facto push for integration. Other portions of the segregation
story receive much less attention. For example, we rarely focus on wealthy Whites who
presumably benefit from segregation (Dwyer 2007). More generally, discussions of
racial residential segregation rarely fully incorporate the diverse spectrum of benefits and
consequences of segregation for groups across differential settings.
Why is it important to think about how integration is framed in the literature? In
proposing stable racial and ethnic integration as a policy solution, the presumption is that
the quality of neighborhoods and individual life chances will improve as segregated
contexts and their associated consequences disappear. Largely absent is the question:
What are the benefits and consequences of integration for groups and neighborhoods, and
how does this vary across space and time? Without knowing more about the nature of the
various contexts that remain integrated (as well as those that change), it is premature to
frame stable integration as a success. Perhaps some integrated communities are
characterized by improved neighborhood conditions and life chances for groups of
residents (relative to segregated contexts), while others are not? But we currently lack
empirical evidence of these assertions, and we are not often asking these questions.
In the next section, I review in more detail the existent scholarship on
neighborhood integration, summarizing the current state of knowledge. I highlight the
empirical limitations of this work and the resulting lack of confidence in our present
remains critical. At the same time, studies that move beyond a focus on Black-White segregation are
increasingly important given huge demographic shifts in the U.S. population over the last few decades - if
we are to understand complex changes involving other groups across space and time (and how these
changes impact Black-White inequality).
23
understanding of basic national patterns and consequences of racial and ethnic
integration.
2.4 Neighborhood Integration Studies - Definitions, Patterns, and Examining
Change
Defining Integration and Stability
The first issue of concern in the burgeoning array of integration studies pertains to
how to define racial and ethnic neighborhood integration. Some scholars, examining
racial and ethnic heterogeneity in neighborhoods, construct diversity indices such as the
Herfindahl concentration index or the index of polarization (e.g., Putnam 2007; Graif
2007; Okediji 2005; Garcia-Montalvo and Reynal-Querol 2005; Sampson 2008). These
indices typically represent the odds that any two individuals randomly chosen from a
neighborhood will be from the same group or category. Diversity indices are powerful in
their capability to capture single or multiple forms of diversity of different groups in
neighborhoods in a single measure – such as language, ancestry, ethnicity, race,
immigration, and so forth. They are also beneficial for capturing within group diversity
(see Graif 2007; White et. al. 2005). In general, they allow for sophisticated comparisons
in levels of diversity across neighborhoods.
Diversity indices are not commonly employed in the integration literature. This
may be because they are designed to provide insight on the characteristics of
neighborhoods (e.g., diversity), but are not as useful in serving as definitional constructs
for neighborhoods. The indices typically produce a score (typically a probability), with a
higher number reflecting greater diversity and a lower number less diversity. It would be
24
difficult to construct a meaningful typology of racial and ethnic integration solely with
some type of diversity index. A typology classifying neighborhoods of varying degrees
of diversity in general would be possible with index scores, but this would not
differentiate the specific racial/ethnic contents of the various neighborhoods. For
example, a segregated Black context and a segregated White context would feasibly be
categorized together, as both would not appear “diverse” with this type of calculation.
Scholars more often employ relative or absolute definitions of integration. First,
relative definitions are characterized by the explicit consideration of the proportional
representation of different groups in a neighborhood relative to their proportional
representation within a larger context in which the neighborhood is located, such as a
state, metropolitan area, or county (Maly 2000; Galster 1998; Smith 1998). Typically,
these definitions produce a score which indicates the degree to which the racial
composition in a smaller geographic unit (i.e., neighborhood) diverges from the racial
composition in a larger geographic unit in which the smaller unit is located (i.e., county,
metropolitan area, state, etc.). The primary benefit of a relative definition is that it
accounts for the supply of racial and ethnic groups living in a city or metropolitan area.
Some argue relative approaches are problematic when examining integration over
multiple decades because the supply of racial and ethnic groups across the decades will
vary- making comparisons difficult (Friedman 2007). A further potential problem, as
Ellen (2000) persuasively argues, is that neighborhoods defined as integrated through a
relative approach may in some cases conflict with a meaningful understanding of
demographic integration. For example, a neighborhood located in a metropolitan area
with 1% Blacks would be considered integrated with a relative approach if the
25
neighborhood itself had at least 1% Black representation. Can we really consider a
neighborhood comprised of 99% White residents and 1% Black residents integrated
(Ellen 2000)?
Absolute definitions of neighborhood integration are significantly more common
in the integration literature. Typically a researcher using an absolute approach will
devise a mutually exclusive neighborhood typology with specific threshold requirements
for each category in the typology. These definitions are typically based on the
proportionate representation of racial and ethnic groups within neighborhoods, with
neighborhoods classified as integrated when they meet the threshold requirements for
integration in the particular typology employed (e.g., Friedman 2007; Rawlings et. al.
2004; Fasenfest et. al. 2004; Ellen 2000, Swaroop 2005, Denton and Massey 1991). For
example, Ellen (200) considers a neighborhood integrated when between 10 and 50% of
the neighborhood is Black.
Absolute definitions of integration are sometimes criticized as arbitrary and
atheoretical (Smith 1998). Integration is purely based on thresholds set by the researcher,
which may or may not have a sound theoretical or empirical basis. Furthermore, absolute
definitions fail to account for potential mathematical constraints determined by the
available proportion of different racial and ethnic groups in the larger context in which
cities are located.
Amongst scholars using an absolute approach in defining integration, significant
variation exists in the racial and ethnic groups included as well as the criteria for a
neighborhood to be considered integrated. In particular, the current set of national
studies all focus primarily on definitions that differentiate between either Blacks and
26
Whites only (Ellen 2000; Rawlings 2004), or Blacks, Whites, and Others (Fasenfest et. al.
2004; Friedman 2007). Notably, in both types of definitions, Latinos are lumped with
either Whites (Ellen 2000; Rawlings 2004), or in a general “Other” category with all nonBlacks and non-Whites (Friedman 2007; Fasenfest et. al. 2004). Not differentiating
Latinos from other groups is a serious limitation/distortion, especially since the Latino
population is now larger than the Black population (U.S. Census Bureau 2009). These
decisions may potentially considerably hamper our ability to understand how varied and
complex forms of neighborhood integration unfold. These definitions lack face validity
in that they do not accurately represent patterns of racial and ethnic settlement and
change across neighborhoods by glossing over variation in patterns. From the
assimilation and segregation literatures, we know that distinct residential patterns
between Latinos, Asians, Whites, and Blacks exist (Charles 2003; Iceland and Nelson
2008; Lee et. al. 2008). Definitions of neighborhood integration should account for this
reality.
Further problems with the current definitions of integration stem from differential
criteria required of group representation, within various definitions of integration, for a
neighborhood to be considered integrated. For example, Ellen considers a neighborhood
integrated when Blacks comprise between 10 and 50 percent of the neighborhood (2000).
Rawlings and colleagues define neighborhoods with less than 5% Blacks as exclusively
White, between 5 and 10% Black as predominantly White, between 10 and 50% Black as
mixed-majority White, 50-90% Black as mixed-majority Black, and greater than 90%
Black as predominantly or exclusively Black (2004). Fasenfest and colleagues devise a
typology, also adopted by Friedman (2007), consisting of three single-race neighborhood
27
types (White, Black, or other), and four mixed-race neighborhood types (mixed White
and other, mixed White and Black, mixed Black and other, and mixed multiethnic).
According to their typology, a single race neighborhood exists where one group
predominates and no other group has greater than 10% representation. A mixed-race
neighborhood requires more than one group having 10% representation.
Finally, studies in the neighborhood integration literature also vary in their
operationalization of what constitutes long-term integration, or stability, across two
points in time. For example, Lee and Wood (1991) define stability as a no more than five
percentage point change in a groups representation in a neighborhood over two points in
time. Ellen (2000) defines less than a 10 percentage point change in a groups
representation over two decades as stable. Friedman develops a typology distinguishing
between neighborhoods that became more White, more non-White, or remained in the
same category over time (2007).
Patterns of Racial and Ethnic Neighborhood Integration
In addition to the problems associated with varied definitions of integration
employed in the literature, as described above, the literature is further limited in the lack
of a sufficient number of studies of integration on a national scale. I am aware of only
four published studies on integration that include a national sample of neighborhoods in
the United States (Friedman 2007; Rawlings et. al. 2004; Fasenfest et. al. 2004; Ellen
2000). This provides limited evidence regarding generalizations about national patterns
of this outcome. An additional set of studies have examined patterns within a smaller
sample of locales (Smith 1998; Maly 2000; Saltman 1990; Lee and Wood 1991; Nyden,
Maly, and Lukehart 1997; Peterman and Nyden 2001).
28
Of the four published studies examining national patterns of neighborhood
integration between the 1970’s to 2000, all conclude that there has been an increase in
racial and ethnic neighborhood integration. However, the studies report varying levels of
growth over the different time periods. For example, Ellen (2000, 1998) finds that
between 1980 and 1990, integrated contexts increased from 25% to 35.1% of
neighborhoods in her sample. On the other hand, Friedman reports that integrated
contexts actually became more common (increasing from 31.6% in 1980 to 53% in 2000)
than contexts with only one racial or ethnic group (from 68% in 1980 to 47% in 2000).
Fasenfest et. al. (2004) conclude that integrated contexts increased from 45% to 52% of
metropolitan neighborhoods between 1990 and 2000.
The case of White-Black neighborhoods provides a lucid example of the disparate
conclusions emerging from these studies. While some conclude that the proportion of
Black-White neighborhoods has increased over time (Rawlings et. al. 2004; Ellen 2000),
others claim that this proportion has significantly decreased (Friedman 2007; Fasenfest
et. al. 2004). Ellen (2000) claims that Black-White neighborhoods represented 9% of all
neighborhoods in 1980, compared to Friedman’s (2007) claim of 7%. In 1990, Ellen
(2000) notes Black-White neighborhoods increased to 10.4% of all neighborhoods, while
Fasenfest et. al. (2004) state the proportion is 6%. In 2000, Rawlings et. al. (2004)
conclude that Black-White neighborhoods represent fully 33% of all U.S. neighborhoods,
compared to Fasenfest et. al.’s (2004) finding of 4% and Friedman’s (2007) finding of
5.4%. It is very difficult to discern which of these findings most closely represents actual
patterns in the U.S. residential landscape.
29
Though all of the national studies assert some kind of increase in the prevalence
of overall neighborhood integration in the United States between 1970 and 1990 and/or
2000, the durability of these neighborhoods is widely contested. Rates of stability for
integrated neighborhoods in this literature range from 28.4% to 80% depending on the
study. For example, on one extreme, Rawlings et. al. (2004) found that 80% of integrated
neighborhoods in 1980 remained so in 1990 and in 2000. Ellen (2000) found that more
than 56% of integrated neighborhoods in 1970 remained stably integrated in 1990. In
contrast, Friedman (2007) is much less optimistic about the stability in her sample,
concluding that only 28.4% of integrated neighborhoods in 1980 remained integrated in
2000.
Conflicting conclusions in the levels and stability of integration outlined above
likely are the result of two factors. First, to my knowledge, no published studies examine
neighborhood integration over the same period of time with the same geographic focus.
In examining trends between 1980 and 2000, Friedman (2007) restricts her sample to
metropolitan areas with populations of over one million in 2000, resulting in a sample of
32,911 tracts in 61 metropolitan areas. Fasenfest, Booza, and Metzger (2004) examine
patterns between 1990 and 2000 in the ten largest metropolitan areas, resulting in a
sample of 12,447 tracts. On the other hand, Rawlings et. al. (2004) limit their sample to
metropolitan areas where Latinos represent no more than 20% of the population and
Blacks are not the dominant minority. This results in a final sample of 25,134 tracts in 69
metropolitan areas. Finally, Ellen examines cross-sectional patterns of integration in all
metropolitan areas in 1970 (42,412 tracts), but limits her analysis of stability in these
neighborhoods between 1970 and 1990 to the 34 metropolitan areas (17,179) with over
30
one million people, at least 5% of whom are Black and less than 30% who are Latino.
The smaller scale integration studies similarly are characterized by divergent sample and
geographic foci. For example, Maly (2000) focuses on 833 tracts in 77 Chicago
community areas between 1980 and 1990, Smith examines patterns between 1980 and
1990 in 1637 tracts in Florida. Finally, Nyden, Maly and Lukehart conduct a crosssectional case study analysis of integration in 14 stable integrated neighborhoods in 9
cities.
A second and perhaps more influential source of the conflicting conclusions
pertains to the use of differential definitions of integration employed. In contrast to the
sophisticated and widely accepted measures of segregation found in the literature
(Massey and Denton 1988; Charles 2003), and on-going advances in this area (Lee et. al.
2008; Lee et. al. 2006; White, Kim, and Glick 2005) no consensus about accepted
measures of integration exists.
Racial and Ethnic Neighborhood Change
A final important component of the integration literature entails attempting to
understand the factors that foster long-term integration in neighborhoods. Scholars have
mainly focused on White loss from integrated neighborhoods as a primary barrier to
maintaining integration over a long period of time (Ellen 2000; Swaroop 2005).
Sociologists often highlight the movement of Whites as a central mechanism of
neighborhood racial transition. An emphasis on White-loss is rooted in theories of
invasion-succession (Park 1936; 1952; Park and Burgess 1925; Alinsky 1941; Hawley
1950; McKenzie 1968), “White flight,” (Crowder 2000; Galster 1990; Quillian 1999; Lee
and Wood 1991; Massey and Denton 1993) and neighborhood “tipping points” (Clark
31
1991; Goering 1978; Schelling 1971, 1972; Grodzins 1958) as underlying patterns of
racial and ethnic transition. In general, this body of work emphasizes the volatile and
unstable nature of racially and ethnically diverse neighborhoods-most often referring to
Black-White neighborhoods. Accordingly, White neighborhoods which experience even
a modest influx of Black residents are expected to inevitably transition to segregated
Black contexts.
In debates about persistent high levels of Black-White segregation in the United
States, processes of White-flight (Massey and Denton 1993; Galster 1990; Massey et. al.
1994; South and Crowder 1998), and more recently White-avoidance (Quillian 2002;
Ellen 2000; South and Crowder 2000) are portrayed as central mechanisms. This is
further reiterated in examinations of Whites’ neighborhood racial composition
preferences and the potential role of racial prejudice and race-associated stereotypes in
White exit from integrated neighborhoods (Krysan and Bader 2007; Krysan 2002; Harris
2001; South and Crowder 2000; Charles 2000).
A substantial literature points to the saliency of the White-flight hypothesis in
understanding neighborhood transition in Black-White neighborhoods in past decades
(Crowder 2000; Galster 1990; Goering 1978; Quillian 1999; Schelling 1971, 1972).
However, a separate body of work questions the generalizability of the White-flight
hypothesis, uncovering significant regional, temporal, and spatial variation in the
relevancy of the hypothesis (Lee 1985; Lee and Wood 1991; Denton and Massey 1991;
Massey and Mullan 1984; Massey 1983; Frey 1979; Marshall and O’Flaherty 1987;
Molotch 1969). Additionally, Massey (1983) and Massey and Mullan (1984), in
examining the applicability of processes of ecological invasion-succession for the
32
assimilation of Latinos in metropolitan neighborhoods, conclude that the model does not
fit.
Processes of White-flight do not represent the full spectrum of forms of change
across the U.S. residential landscape. For example, Friedman demonstrates that more
than a negligible amount of cases of neighborhood racial transition between 1980 and
2000 directly contradicts outcomes expected by the White-flight hypothesis (2007). She
finds that while 14.8% of Black-White neighborhoods in 1980 transitioned to segregated
Black contexts in 2000, 8.2% transitioned to predominantly White neighborhoods and
21.6% to multiethnic contexts.3 While this is certainly not a new idea, research in this
area has yet to aggressively move beyond a White-loss focus.4 With a few exceptions,
using proportion White-loss as a dependent variable in models of change (e.g.,Friedman
2007; Ellen 2000, 1998, 1996; Swaroop 2005; Smith 1998) remains the norm providing only limited insight into actual processes of neighborhood transition.
Both Ellen (2000) and Friedman (2007) adamantly argue that the focus on Whites
in both conceptualizing “integration” and modeling change is warranted given the greater
resources, amenities, and outlets for mobility tied to White neighborhoods. Ellen further
states that “fleeing Whites are typically considered the greatest threat to integration.”
(2000:18). However, some race theorists may contend that this argument reinforces the
idea that Blacks and other subordinated groups must live in White neighborhoods to
access quality homes, schools, jobs, and so forth. Some may see this logic alluding to a
superiority of White and White neighborhoods as “natural,” thus serving as one more
3
Though her typology of integration is limited in that it includes an overly general “Other” category to
capture Latinos, Asians, and Other non-White or non-Black groups.
33
example of the perpetuation of White supremacy in our social scientific framing of social
problems (Piven and Cloward 1980; Zuberi and Bonilla-Silva 2008; Bonilla-Silva 2001).
Additionally, some race scholars may contend this focus also potentially hinders
theoretical advancement in the study of racial inequality. They argue that a singular
emphasis on White movement as a barrier to neighborhood integration follows another
firmly entrenched tradition in the social sciences – a focus on “assimilation as the
solution to America’s (and the world’s) racial problems” (Zuberi and Bonilla-Silva
2008:331). According to these theorists, as long as race “determine[s] the structures that
organize the distribution of life chances and well-being,” only “radical and fundamental
changes to the social order” (Zuberi and Bonilla-Silva 2008:330) are effective in
eliminating “the color line” (Du Bois 1903).
2.5 Research Questions
In Sections 2.3 and 2.4 above, I have outlined the theoretical and empirical
problems characterizing the current neighborhood integration literature. I contend that
the central problem is the failure to grapple theoretically with the question of whether or
not durable racial and ethnic integration can serve as a meaningful solution for the
consequences associated with segregation. We have not considered theoretically why
this may or may not be the case, nor asked questions about potential consequences of
integration for Whites, Blacks, and Latinos.
There are also important empirical problems that need to be addressed, as
described above. The handful of published integration studies with national samples
provide conflicting conclusions about the prevalence and stability of neighborhood
34
integration in the United States, partly because some of them are not fully national in
scope. Their divergent conclusions likely are the result of the use of varied geographic
and temporal contexts examined, and differential definitions of long-term integration
employed. Furthermore, the definitions that are employed often lack face validity when
failing to differentiate Latinos from other groups. Finally, studies that attempt to
understand the factors associated with stability in integrated neighborhoods focus almost
exclusively on the factors associated with White loss, potentially ignoring the full range
of possible processes associated with racial and ethnic change in neighborhoods. As a
result of these problems, I believe we lack a sufficient understanding of basic, national
patterns of the prevalence, durability, and consequences of neighborhood integration.
In an effort to begin to address some of these problems, and to move our
understanding of national patterns forward, I will address the following research
questions in my dissertation:
Research Question 1:
What are the patterns of racial/ethnic neighborhoood integration and change in
the United States between 1980 and 2000? Why do neighborhoods become
integrated? Why do integrated neighborhoods remain integrated or change to
another racial/ethnic type?
Research Question 2:
Are racially/ethnically stable integrated neighborhoods between 1980 and 2000
more advantaged contexts than alternative homogenous and transitioning
contexts?
Research Question 3:
Are historically subordinated group members in racially/ethnically stable
integrated neighborhoods more advantaged than group members in alternative
homogenous and transitioning contexts?
35
2.6 A Critical Race Approach to the Study of Racial and Ethnic Neighborhood
Integration
I have outlined above the research questions to be addressed in my dissertation
project. In this section, I seek to draw on contemporary race theory to develop a
theoretical approach to the study of integration which accounts for the broader societal
context in which processes of neighborhood racial and ethnic change are situated.
Specifically, I set forth a critical race perspective on processes of racial and ethnic change
in the urban residential landscape. This perspective is explicitly shaped by consideration
of the broader racialized social order in which all institutions, including housing, operate.
Further, I develop theoretical expectations about the research questions to be addressed.
These relate to expectations about the prevalence and durability of integration, as well as
the potential (or not), of long-term neighborhood racial and ethnic integration in helping
to ameliorate negative consequences associated with racial residential segregation.
White Supremacy, Institutions, and Racial and Ethnic Inequality
Figure 2.1 depicts an institutional approach to the study of racial stratification
which some scholars adopt. The large dotted box represents the collectivity of
institutions that make up society. The five boxes, with solid lines, in the middle of this
larger rectangle, represent some of the most important institutions, including housing,
labor, education, government, and family. The box on the far right of the figure, labeled
“racial/and ethnic inequality,” represents the aggregate patterns of inequitable outcomes
along racial and ethnic lines that are associated with the various institutions. The arrows
connecting the institutions to the racially stratified outcomes on the right represent the
mechanisms, or how, the institutions cause the observed inequality.
36
With this approach, some scholars focus on examining levels of inequality
associated with various institutions. Others focus on understanding the mechanisms
within, or associated with, these institutions that are responsible for creating and/or
maintaining these inequitable patterns. Mechanisms identified may range from structural
practices, policies, and procedures characterizing institutions, to interactional processes
between actors, which are conditioned by the structures in which they are situated (e.g.,
Blau 1964; Parkin 1979;Tomaskovic-Devey 1993; Roscigno 2007). In recent years, a
growing number of stratification scholars have advocated for a renewed focus on
identifying the mechanisms responsible for the creation of inequitable outcomes (e.g.,
Reskin 2003; Charles 2003; Massey 2005; Sampson 2002). This is clearly important for
understanding the complex and nuanced ways in which these patterns are created.
Yet, regardless of the focus on the outcomes themselves or the mechanisms at
play, as well as the specific institution in which these processes unfold, the underlying
theoretical approach and resulting implications for reducing inequality as depicted in
Figure 2.1 are the same – understanding levels and causes of racially inequitable
outcomes within institutions will provide us with the necessary information to craft new,
or alter existent policies, necessary to reduce the racially stratified patterns. The key
point is that this approach presumes appropriate shifts at the institutional level – social
policies, organizational procedures, legislation, structural changes to engender
interactional changes, etc. – are the central mechanisms to ultimately reduce inequality
for historically subordinated racial and ethnic group members. Key examples of these
kinds of historical shifts include introduction of the Fair Housing Act, the Voting Rights
Act, Affirmative Action, Equal Employment Opportunity laws and policies, and the like.
37
Cultural and/or individual explanations are sometimes proffered - by the general public,
politicians, and some in the academy - when racial and ethnic inequality persists despite
these changes.
Within the context of housing specifically, a clear example of this type of
approach can be found in the long-standing debate about the role of discrimination, group
preferences, or economic constraints in perpetuating racial residential segregation.
Scholars who view housing discrimination as a primary cause of segregation continue to
advocate improved policies to diminish new and evolving forms of discrimination forty
years after the Fair Housing Act (Massey 2005; Ross and Turner 2005; Charles 2003;
Yinger 1995; Roscigno, Karafin, and Tester 2009). Others emphasize divergent racial
housing preferences, in addition to discrimination, as central to understanding housing
outcomes for different groups. In addition to continued efforts to eliminate
discrimination in the housing markets, they argue their scholarship should inform
strategies/policies that may be employed to reduce institutional and individual prejudice
toward Blacks and Latinos in the context of housing (Charles 2006) and to stem White
aversion to integrated neighborhoods (Krysan and Bader 2007; Friedman 2007; Krysan
2002; Emerson, Chai, and Yancey 2001; Ellen 2000).
However, some critical race scholars may contend that the approach portrayed in
Figure 2.1 is ultimately deficient, as it fails to recognize the larger racialized system
impacting the institutions and how they operate. Figure 2.2 depicts what can be
considered a critical race model of the relationship between institutions and racial and
ethnic stratification. The key difference between the two figures is the recognition in
Figure 2.2 of a larger system of White supremacy; an exogenous force ignored in Figure
38
2.1. This force shapes and conditions the institutions, practices, policies, procedures, and
interactions that create and reify racial and ethnic inequality in the society.
But what exactly is “White supremacy?” The philosopher Mills defines White
supremacy as a “political, economic, and cultural system in which Whites
overwhelmingly control power and material resources, conscious and unconscious ideas
of White supremacy are widespread, and relations of White dominance and non-White
subordination are daily reenacted across a broad array of institutional and social settings”
(Mills 1997:37).5 Bonilla-Silva describes White supremacy as “racially based political
regimes that emerged post fifteenth century” (2001:15) that is similar in function for race
theory, to the constructs of patriarchy in feminist theory or capitalism in Marxist theory
(Mills 1998; 2004; Bonilla-Silva 2001). White supremacy operates to reproduce
structures of domination that guarantee the allocation of resources in such a way as to
maintain White advantage, whatever the cost to others, and independently of beliefs,
whether they are racially or otherwise constructed (Mills 2004; Omi and Winant 1994;
Jensen 2005). As such, the system of White supremacy is not an anomaly in an otherwise
largely egalitarian liberal democracy; rather, it has been and remains the normative
system shaping the institutions within the social structure (Mills 2004).
In my dissertation, and as I further develop the ideas implied in Figure 2.2 below,
it is important to explain clearly how I use the term “White supremacy” in relation to
other scholars and how the term is used in race theory in general. While race theorists
5
Mills concedes that the term “White supremacy” may be considered extremist, and that many associate
the term with slavery, the Ku Klux Klan, and a past era of legally mandated discrimination (Mills 2004).
Yet, I believe he builds a strong case for philosophers and scientists working on race to work to advance
the theoretically development of White supremacy to better address “the crucial reality that the normal
workings of the social system continue to disadvantage Blacks in large measure independently of racist
feeling” (Mills 2004:241).
39
often use the general term “racial system” to refer to the way in which structures in a
society are aligned to hierarchically arrange and reward groups along racial lines, I confer
with Mills (2004, 1998) and Bonilla-Silva (2001), that all racial systems are characterized
by White supremacy. As such, I use the term “White supremacy” in the context of this
dissertation to refer explicitly to the past and present racial system in the United States.
This perspective may be construed as radical, as it contrasts sharply with those in
fields such as sociology, philosophy, or political science, that frame racism and
contemporary inequality as irrational and incongruent with the larger philosophy and
structure of the society (Bonilla-Silva 2001). Some focus predominantly on how
inequality results from particular policies or interactions within institutions. The
problems are understood to be institutional, and not in accordance with the dominant
philosophy, in support of racial and ethnic equality, characterizing the larger society.
Though some readily admit the centrality of a system of White supremacy in the “Old
World,” they frame contemporary manifestations of inequality as anomalies within a
social structure in the “New World” that is largely liberal and egalitarian. (Mills 2004).
It is not surprising then, that both pragmatically and in relation to the theory itself,
that the presence and role of the system as a whole is sometimes ignored, and hence
operates somewhat invisibly (Goar 2008; Bonilla-Silva 1999). However, some race
scholars do contend the system of White supremacy has an identifiable “face.” The
“face” of the system can be interpreted as the dominant racial ideology characterizing the
society. A racial ideology “provides the rationalization for social, political, and
economic interactions among the races” (Bonilla-Silva 2001:43). It may shift
dramatically over time in shape and form. Historically, the ideology has been
40
characterized by overt prejudice and racism toward those considered non-White
(reflective of the more overt racist regimes of earlier periods in American history). In
recent decades, some prominent race scholars have described the ideology as
“colorblind” (Bonilla-Silva 200 ; Forman 2004), a “new racism” (Bonilla-Silva 2008,
2001), or “laissez-faire racism” (Bobo 2004; Bobo, Kluegel, and Smith 1997).6
Irrespective of the chosen label, these scholars argue that the current ideology is
characterized by more subtle, covert, or institutional forms of racism that are difficult to
detect, and operate within a larger context in which race and racial concerns are seen as
irrelevant and inconsequential (Bonilla-Silva 1999). This is especially problematic as the
racial stratification system continues to operate amidst a climate where race is no longer
recognized as relevant (Bonilla-Silva 1999; Bonilla-Silver and Glover 2004).
Moreover, in a similar fashion to the evolution of the “face” of White supremacy
over time, institutions, the intervening variables in Figure 2.2, also adapt in ways
congruent with the current racial climate. Omi and Winant describe this process as a
constant political contestation, with a vast interplay of racial projects that determine
historical and contemporary institutional depictions of the larger racial climate (1994).
However, while Omi and Winant argue that the process of racial formation is constantly
evolving (1994), the purpose of the system of White supremacy itself is always the same;
to promote the advantaging of Whites over others. However, how the system impacts
institutions and inequality changes over time. Furthermore, who is considered White may
change, as the fluidity of Whiteness, race, and ethnicity has been extensively documented
by historians and sociologists (e.g., Lee and Bean 2007; Ignatiev 1995; Warren and
6
Subtle differences do exist between these theoretical constructs. See Forman 2004, for a helpful
discussion delineating these differences.
41
Twine 1997; Gans 1999). The implication, given the fixed purpose of the system of
White supremacy, is that strategies to reduce stratification through policy changes at or
within the institutional level may not always be significantly effective in diminishing
inequality. Polices may effect some change, but other mechanisms may emerge to
reinforce the hierarchy. Regardless of their particular characterization at any one time,
according to this perspective, institutions and their associated practices and policies are
shaped by a system of White supremacy and its associated racial ideology, that ensures
mechanisms are in place to protect White privilege.
The final critical component of Figure 2.2 is the feedback loop connecting
racial/ethnic inequality to the system of White supremacy. This signifies how the
patterns of inequality, for which the larger system of White supremacy is ultimately
responsible, also reinforce the system itself. This may entail the aggregation of the
interpretation by actors, of observed racial/ethnic differences, as confirmation of their
beliefs which are congruent with the current racial ideology. As Bonilla-Silva (2001)
argues, this is important as the ideology is not simply “(a mere reflection of the racialized
system) but becomes the organizational map that guides actions of racial actors in
society). This component of the framework highlights the important interplay between
structure and agency in the study of stratification.
It is important to qualify that I am not arguing that significant strides in reducing
inequality never come about through institutional change, such as those resulting from
legislation following the Civil Rights Movement. I am also not claiming that the study of
social mechanisms is unnecessary or unimportant. On the contrary, it is imperative to
continue to work to understand the processes that create and maintain inequality,
42
especially as they shift in form and function over time (see Gross 2009 for an excellent
recent theoretical discussion on the current practice and limitations of social mechanism
inquiry in the social sciences). These processes are the key means through which the
system of White supremacy works in maintaining White advantage. However, the key
point I am making is that new mechanisms to ensure perpetual racialized outcomes will
form as others fade, so long as the system of White supremacy persists as the dominant
context in which our dominant institutions operate. If the system of White supremacy is
not dismantled, regardless of how the institutions and all of their associated practices,
policies, organizations, groups, and individuals change over time, part of their core
function will entail maintaining a racial order in which Whites receive the most desirable
social positions, goods, and resources.
What are the implications of this model for the potential role of neighborhood
integration as a remedy for the inequality associated with racial residential segregation
for Blacks and Latinos? And how can the model, which is somewhat abstract, help
inform how we consider theoretically and analytically the significance of neighborhood
racial and ethnic composition? The general implication, of course, is that patterns of
long-term neighborhood integration, and their associated consequences, are conditioned
by the system of White supremacy in the same way that patterns and consequences of
residential segregation are conditioned. Thus both segregation and integration will
similarly be associated, overall, with White advantage and non-White disadvantage. Yet,
this seems overly general relative to the complex, intricate, and ever changing racial
order in the United States. Research questions to test hypotheses generated from the
model require more explicit consideration and incorporation of this racial order, beyond a
43
general description of the advantaging of Whites over others across time and space.
Bonilla-Silva and Glover’s (2004) recent theoretical proposition of an emerging tri-racial,
Latin American-like racial system in the United States may be especially helpful in
crafting more nuanced, and testable, research questions pertaining to the success (or not)
of long-term racial and ethnic integration in reducing the inequality associated with racial
residential segregation. These authors build a compelling case that this tri-racial system
of stratification is emerging as a new hierarchy that exists within the current racial order.
In the next section, I outline Bonilla-Silva and Glover’s (2004) theory and discuss the
specific expectations the theory might predict about outcomes pertaining to long-term
racial and ethnic neighborhood integration in the United States. I conclude with a
discussion of the limitations of my approach.
A Tri-Racial System of Stratification
Bonilla-Silva and Glover (2004) argue that a new U.S. racial system is emerging
that is becoming Latin-American like. The racial system is characterized in Latin
American countries by a denial of the saliency of race, and views of inequality between
groups as non-racial. It is also characterized by a movement to adopt a national identify,
such as “We are all Brazillians,” even amidst a context of marked inequality by color.
This system maintains racial hierarchies, yet does so under conditions in which race is
increasingly not recognized (and this acts to further reinforce the system itself). Most
troubling, the authors argue, is that this system exists despite the fact that racial
minorities in these countries are often far worse off compared to racial minorities in
Western nations.
44
What does the new racial order, emanating from the system, look like? The new
order is tri-racial in nature, consisting of three hierarchically arranged groups. Figure 2.3
provides a heuristic map of the tri-racial system, as presented by Bonilla-Silver and
Glover (2004:150-151). The first group, at the top, is “Whites”; which consists of
Whites, new Whites, assimilated White Latinos, Some White-looking multiracials,
assimilated (urban) Native Americans, and a few Asian-origin people. The second group,
labeled “Honorary Whites,” is considered the intermediary group; light-skinned Latinos,
Japanese Americans, Korean Americans, Asian Indians, Chinese Americans, Middle
Eastern Americans, and most multiracials comprise this category. Finally, the third
group, at the bottom, is referred to as the “Collective Black” which includes Filipinos,
Vietnamese, Hmong, Laotians, dark-skinned Latinos, Blacks, new West Indian and
African immigrants, and reservation-bound Native Americans. The composition of the
three groups is not fixed, and the position of some groups both within and between the
strata may change over time. For the most part, phenotype and cultural characteristics
determine where particular groups are classified. Patterns in the distribution of societal
resources, goods, and rewards will mirror the hierarchy of the system, with Whites the
most advantaged, honorary Whites slightly less advantaged, and the Collective Black the
least advantaged.
The most important part of the tri-racial system is that the intermediary group,
“Honorary Whites” is seen as a buffer between the top and bottom group, serving to
diffuse potential conflict between “Whites” and the “Collective Black” and helping
further cement color-blind racism. This is accomplished as Honorary Whites grow in
size, play a more important social role in the society, and develop unique interests
45
separate from the Collective Black and Whites. Bonilla-Silva and Glover (2004) contend
the function of this intermediary group in diffusing conflict is similar to “a complex class
stratification system…whereas class polarization leads to rebellion, a multiplicity of
classes and strata leads to diffused social conflict” (2004:153).
Why is a tri-racial order emerging in the United States? Bonilla-Silva and Glover
contend the new order is a direct response of the White elite to the impending reality of a
“darkening of America” where racial minorities are projected to outnumber Whites as
early as 2050 (2004:157).7 How can an understanding of the tri-racial system help
formulate theoretical expectations about the promise of racial and ethnic neighborhood
integration in the United States as a solution to the consequences associated with racial
residential segregation? My argument is that patterns and outcomes associated with
neighborhood integration are conditioned by this racialized system of White supremacy.
Housing as an institution is no different from other institutions in that it is conditioned by
the system, and ultimately is structured in such a way as to produce outcomes that are
advantageous to Whites and less so for non-Whites. As such, regardless of where groups
tend to reside, with the system of White supremacy firmly in place, I would expect
patterns that reflect the advantaging of Whites. I hypothesize that the evidence will not
show that historically subordinated group members are substantially more advantaged in
long-term integrated contexts when compared to group members in segregated or areas
7
The authors argue this response contrasts with past strategies to further Whiten the population, such as
immigration or fluidity in who is considered White. They argue the new system is the more likely response
now given an amalgamation of factors: 1. large demographic shifts and greater heterogeneity in the United
States - a “rapid darkening of America” (Bonilla-Silva and Glover 2004:155) 2. the emergence of a new
form of racism characterized by practices that are covert, institutional, and seemingly nonracial (resulting
in a color-blind ideology) 3. the globalization of race relations, 4. the multiracial movement in America
resulting in the elimination or dilution of the collection of racial data, and 5. the decline (or end) of racebased policies in the United States.
46
undergoing transition. The theoretical justification, as I have outlined above, is that the
processes responsible for creating and maintaining long-term integration are influenced
by the same system that perpetuates racial residential segregation.
More specifically, if the tri-racial system proposed by Bonilla-Silva and Glover
(2004) is representative of the current racial order in the United States, I would expect
patterns and outcomes to largely mirror the hierarchical structure of the tri-racial system.
In the assessment of the overall prevalence and durability of neighborhood integration,
the first set of research questions to be addressed, I would expect cases of integration
involving groups from different strata in the tri-racial system to be less likely to remain
integrated over time (compared to neighborhoods with groups from the same strata in the
hierarchy). I would also expect integration between Whites and Honorary Whites to be
more common and potentially more stable than forms involving Whites and the
Collective Black. When examining the economic and social characteristics of
homogenous and integrated contexts in the United States over time, the second set of
research questions to be addressed, I would similarly expect stratified outcomes that
mirror the tri-racial system, with Whiter contexts most advantaged, collective Black
contexts least advantaged, and contexts with Honorary Whites somewhere in between. A
theoretically interesting and important question pertains to the cases, if any, of long-term
integration between groups from different strata in the tri-racial system, such as between
Whites and Honorary Whites or Whites and the Collective Black.8 Will the social and
economic character of these neighborhoods and the groups in them support the ideas
8
However, I am limited in conclusions I can make about Honorary Whites, as I rely on pan-ethnic
definitions which do not differentiate between Latino group members that would be considered White,
Honorary White, or part of the Collective Black, according to the hierarchy (see Chapter 3).
47
promulgated in the literature about their superior status relative to segregated minority
areas? Or will the evidence suggest minorities in these contexts are not significantly
more advantaged relative to those in other areas, supporting the critical race perspective
outlined above?
2.7 Limitations
Before proceeding to Chapter 3, in which I detail the data and methods used to
address the research questions explicated in Chapters 1 and 2, it is important to discuss
the limitations of my approach to the dissertation problem. First, I must highlight that I
cannot directly test the theoretical models depicted, nor do I claim to do so. My approach
is limited in that I can only seek to produce evidence consistent with the view point that a
push for neighborhood integration, as any social policy, is limited in its potential to
significantly diminish inequality given a larger, powerful system of White supremacy. I
cannot directly test this argument, nor make any causal claims in relation to my findings.
Though this is a significant limitation, I see this work as an important first step, in
relation specifically to the segregation/integration issue, in challenging other scholars to
grapple with the larger context in which racialized patterns unfold. I see this as a direct
response to Mills’ call for social scientists to “challenge the mainstream liberal ‘anomaly’
framing of race by developing the concept of White supremacy” (2004:240).
Second, my theoretical approach focuses predominantly on one aspect of racial
and ethnic inequality, that pertaining to levels of advantage and disadvantage in
neighborhoods and the groups residing in them. Other significant forms of inequality,
such as interactional forms, are not considered. Stewart (2004) provides a cogent critique
of this common tendency in race stratification scholarship, in that it assumes that human
48
capital is equally valuable for all racial and ethnic groups (and genders and classes) in the
larger society. This is equated with the idea, in the study of mean levels of race-specific
advantage, for example, that Whites and Blacks with equal levels of advantage receive
the same benefits attached to that level of advantage in the larger society. Or, for
neighborhoods, that a neighborhood considered middle-class and White is largely
identical in access to resources and benefits, as is a neighborhood that is middle-class and
Black. A significant literature has documented that this is often not the case for groups
such as African-Americans and Women in the labor and housing markets, the criminal
justice system, perceptions of safety; the neighborhoods in which groups reside, and so
forth (e.g., Patillio 1999; Pager 2003; Yinger 1995; Tester 2008; Krivo, Peterson, and
Karafin 2006).
Stewart states that a significant consequence of this tendency is the misplaced
emphasis on “interpreting the unique characteristics of outliers as the keys to racial
uplift” (2004:112). Stewart explains that outliers uncovered in quantitative research of
racial and ethnic inequality, the cases where no inequality is found, are often viewed as
possessing some special or unique set of characteristics which must be uncovered and
emphasized in policy decisions to reduce inequality. In the segregation and integration
scholarship, this translates into an approach in which the character of cases of long-term
integration (the outliers) are assessed to shape policies to better foster long-term
integration. However, the problem with this approach, as Stewart argues, is that it
ignores the significant role of interactive processes in perpetuating racial inequality. This
effect cannot be readily detected in quantitative models, and policy efforts based solely
on quantitative models will not account for this.
49
In conclusion, I have outlined theoretical and empirical gaps in our current
understanding of racial and ethnic neighborhood integration in this chapter. I have
drawn from recent race theory to set forth a critical race approach to the study
neighborhood integration, and explicated three research questions to expand our current
understanding. In the next chapter, I provide detailed information on the data and
methods employed to address the 3 primary research questions comprising this
dissertation.
50
Institutions
Housing
Labor
Education
Racial/Ethnic
Inequality
Government
Family
Figure 2.1 An Institutional-Level Framework of Racial Stratification
Institutions
Housing
Labor
White
Supremacy
Education
Government
Family
Figure 2.2 A Critical Race Framework of Racial Stratification
51
Racial/Ethnic
Inequality
“Whites”
 Whites
 New Whites (Russians, Albanians, and so on)
 Assimilated White Latinos
 Some (White-looking) multiracials
 Assimilated (urban) Native Americans
 A few Asian-origin people
“Honoarary Whites”
 Light-skinned Latinos
 Japanese Americans
 Korean Americans
 Asian Indians
 Chinese Americans
 Middle Eastern Americans
 Most multiracials
“Collective Black”
 Filipinos
 Vietnamese
 Hmong
 Laotians
 Dark-skinned Latinos
 Blacks
 New West Indian and African immigrants
 Reservation-bound Native Americans
Source - Bonilla-Silva and Glover (2004)
Figure 2.3 Map of Tri-Racial System in the United States
52
Chapter 3
Data and Methods
3.1 Introduction
In this chapter, I detail the data and methods used in subsequent chapters to
examine national patterns and consequences of racial and ethnic neighborhood
integration. First, I discuss the source and characteristics of the data. Next, I outline the
process of selecting the sample of metropolitan neighborhoods to be used in the analysis.
Third, I elaborate on operationalizations of the measures used in the analysis. Finally, I
explain the analytic strategy I employ to address each of the research questions guiding
the project.
3.2 Data and Sample Selection
Data
The primary source of data for this study is the Neighborhood Change Data Base
(NCDB) (Tatian 2003). The NCDB provides selected long-form census data at the tractlevel from the 1980, 1990, and 2000 U.S. censuses. The dataset is especially helpful for
tract-level comparative analysis of population, housing, and economic characteristics
over time. This is because the data for all years are normalized to 2000 census tract
boundaries, as shifting tract boundaries are common between annual census counts,
making comparisons across decades difficult. Through a process of normalizing census
53
boundaries with GIS software to account for these boundary changes, accurate
comparisons of tract-level characteristics over time are made possible (see Tatian 2003)
for a more specific explanation of the methodology used). This correction ensures that
analysts interested in longitudinal comparisons are indeed comparing the same
geographic unit over time. To supplement data available in the Neighborhood Change
Data Base, a few variables were retrieved from the 1980 short and long form U.S. Census
Data in 2000 boundaries (Geolytics 2007).
It is important to note that I use the census tract, the smallest unit of analysis in
the NCDB, as a proxy for neighborhood. The neighborhood, according to classic urban
sociological theory, is understood to be a distinct ecological unit nested within a larger
unit, and influenced by both internal and external ecological, political, and cultural forces
(Park 1916; Suttles 1972; Sampson, Morenoff, and Gannon-Rowley 2002). Many
researchers use tracts to represent neighborhoods in studies of urban sociology,
neighborhood effects, and crime (e.g. Sampson, Morenoff, and Gannon-Rowley 2002;
Krivo, Peterson, and Kuhl 2009) because they offer an extensive array of data collected
by the Census Bureau not available at other smaller levels of aggregation. In theory,
census tracts are comprised of an average of 4,000 residents, and are considered
homogenous across population, economic, and living characteristics (U.S. Census
Bureau). Though convenient, scholars continue to debate the use of census tracts as
meaningful representations of neighborhoods (e.g., Lee et. al. 2008; Grannis 1998;
Sampson, Raudenbush, and Earls 1997). For example, census tract boundaries are often
constructed without consideration for physical boundaries, such as major highways or
rivers or railroad tracks, which significantly alter how neighborhoods are divided.
53
Though the use of tracts is not ideal, no other source of data exists for making
longitudinal comparisons of neighborhoods across several decades.
The NCDB data are particularly fitting for the research questions guiding this
project, as they allow for a national assessment of patterns of racial and ethnic
neighborhood integration by making possible the comparison of shifting racial and ethnic
compositions in census tracts over time. Furthermore, the population, housing, and
economic information available in the data allows for an examination of the
socioeconomic character of long-term integrated neighborhoods compared with
homogenous and transitioning contexts, taking into account important neighborhood and
metropolitan factors.
Sample Selection
The primary focus of my dissertation project entails assessing national patterns
and socioeconomic consequences of long term racial and ethnic neighborhood
integration. Hence, I draw from the NCDB to construct a national sample of
metropolitan neighborhoods between 1980 and 2000. While data for tract characteristics
in 1970 are available in the NCDB, I opt to exclude these data given severe limitations.
First, the 1970 data are limited because fewer metropolitan areas were tracted in 1970.
Further, the racial and ethnic classifications (particularly in relation to options for Latino
respondents) used in the 1970 census are incongruent with those used in subsequent
censuses.
The NCDB consists of a total of 65,443 census tracts. I include a subset of all
tracts based on several criteria. First, I include only tracts located in metropolitan areas
in 2000, eliminating tracts located in rural areas. This equates to a total of 51,467 tracts.
54
Next, I exclude tracts: with less than 300 people,1 metropolitan areas (and the associated
tracts) that did not qualify as metropolitan in 1980,2 tracts where less than 90% of the
tract was covered in 1980,3 and tracts with greater than 50% of the population in group
quarters such as dormitories, jails, or prisons. After eliminating these tracts, the final
sample includes 40,047 tracts in 325 metropolitan areas, which is 61% of the cases
available in the NCDB.
3.3 Measures
Defining Long Term Racial and Ethnic Neighborhood Integration
Table 3.1 provides a summary of the operationalizations of all the measures, and
Table 3.2 presents the means and standard deviations of these measures for the complete
sample of metropolitan neighborhoods examined in this study. In the current study, I
seek to address some of the limitations discussed in Chapter 2 regarding definitions of
racial and ethnic neighborhood integration employed in the literature to date. I use an
absolute conceptualization of neighborhood integration comprised of a mutually
exclusive 15-category typology of neighborhood racial and ethnic type for multiple
combinations of White, Black, Latino, and Other groups. An absolute typology is a
useful tool to classify neighborhoods by racial and ethnic type according to theoretically
1
I use 300 persons as a cut-off for excluding very small tracts in accordance with the National
Neighborhood Crime Study (Krivo and Peterson 2007)
2
In all, six 2000 metropolitan areas were not considered metropolitan areas in 1980. These are BarnstableYarmouth, MA, Flagstaff, AZ-UT, Greenville, NC, Jonesboro, AR, Myrtle Beach, SC, and Punta Gorda,
FL.
3
The U.S. was not 100% tracted until 1990. There are numerous cases of tracts that were not at all or only
partially tracted in 1980. The NCDB includes a flag for these cases, as well as a variable which indicates
the percentage of the tract that was tracted in 1980. I use a relatively conservative standard for inclusion of
partially tracted neighborhoods. Alternative standards for inclusion would only increase the sample
slightly (e.g., with a requirement that 70% of the tract was covered, I would only gain 954 cases). A
careful analysis of the “excluded” tracts that were less than 90% tracted revealed that the majority were
located in outlying areas of MA’s with considerable growth and expansion in the 80’s and 90’s, such as Las
Vegas, Los Angeles, and Houston.
55
justified threshold requirements (as reviewed in Chapter 2). This typology improves on
those currently employed by differentiating between Whites, Latinos, and Blacks.
Though an improvement in terms of specificity compared to past studies examining
neighborhood integration, the reliance on the broad pan-ethnic categories of Black,
Latino, White, and Other means that potentially important within-group heterogeneity is
ignored. This may be particularly important for Latinos, for whom there is considerable
variation in national origin, immigration and nativity statuses. Nonetheless, pan-ethnic
categories are useful for the current analysis seeking to uncover broad, national level
patterns of racial and ethnic neighborhood integration, and they are commonly employed
in the literature.
The overarching premise of the typology is that multiple groups must reach some
critical threshold for integration to be achieved. Prior work has typically required only
10% representation from two or more groups for a neighborhood to be considered
integrated when using an absolute approach (e.g., Ellen 2000; Swaroop 2005). Although
any absolute approaches to defining integration could be considered arbitrary, there is no
specified empirical or theoretical bases for the 10% cut-off. Further, this small
representation lacks face validity because it does not represent the conceptualization of
neighborhood integration as a significant portion of two or more groups sharing
community space. In choosing a threshold requirement for the definition of integration I
employ, I instead draw on recent scholarship on racial and ethnic neighborhood
preferences. This literature suggests that the majority of Whites are comfortable with up
to a 20% representation of Blacks, Latinos, or Asians in their neighborhood (e.g., Charles
56
2006; Krysan 2000). However, beyond this threshold, Whites are known as a group to
avoid or flee neighborhoods perceived to be integrated.
As a result, requiring neighborhoods to contain more than a 20% representation of
two or more racial and ethnic groups to be considered integrated reflects preferences
known of Whites; a group with a well-documented historical tendency to live primarily
with other Whites. Blacks and Latinos maintain different conceptualizations of what
“integrated” means and what they are comfortable with (Charles 2006; Bobo and Charles
1996; Krysan and Bader 2007). However, well before the integration Blacks and Latinos
are comfortable with is achieved, Whites either move out or avoid these neighborhoods.
Furthermore, Blacks and Latinos do not enjoy the same degree of freedom as Whites to
always pursue the neighborhoods they prefer and can afford, given continued
discrimination in the housing markets (Ross and Turner 2005; Yinger 1995).
Following this basic logic, single-race neighborhoods (White, Black, Latino, and
Other) are defined as those with more than 80% of the population of one group, with less
than a 20% representation of any other group. Two-group neighborhoods include those
with two groups each having between 20 and 80% representation, and any other group
having less than 20% representation. The typology includes six two-group
neighborhoods: Black-White, Latino-White, Black-Latino, White-Other, Latino-Other,
and Black-Other.4 Similarly, three group neighborhoods require three groups to comprise
between 20 and 80% of the neighborhood, with no other group having more than 20%
representation. In the typology, these are the following four types of neighborhoods:
White-Black-Latino, White-Black-Other, Black-Latino-Other, and White-Latino-Other.
4
Throughout the dissertation, the ordering of the groups for integrated neighborhoods are interchangeable.
For example, a Latino-White neighborhood is equivalent to a White-Latino neighborhood.
57
Finally, 4-group neighborhoods, a form of neighborhood integration I expect to be quite
rare, requires between 20 and 80% representation of four distinct racial or ethnic groups.
In the typology, this is a neighborhood classified as White-Black-Latino-Other. 5
It is important to note that this typology provides improved specificity, and
greater face validity, relative to those commonly seen in the literature for several reasons.
First, the typology includes Latinos as a distinct group. Second, a more encompassing
range of two, three, and four group forms of integration (eleven in all) provides more
detail over past work that typically focuses on between just two to seven neighborhood
types. Finally, with fifteen total categories, the typology provides greater detail on
potential trajectories of neighborhood transition and change over time, such as transition
from one form of integration to another.
The final component to discuss pertaining to the definition of integration I use in
this dissertation pertains to the conceptual distinction between neighborhoods that are
integrated long-term versus those that are integrated at one point in time, but not in the
long-term. This is important, as the research questions I address focus on assessing
claims in the segregation literature about the benefits ascribed to meaningful cases of
long-term, racially stable integrated neighborhoods. To differentiate between long-term
racially integrated neighborhoods and those in flux, I define a neighborhood as stably
integrated if it is classified in the same category in the typology over a period of twenty
5
In her dissertation, Swaroop (2005) develops a similar typology to measure integration. However, our
definitions differ in their threshold requirements of group representation for neighborhoods to be
considered integrated.
58
years.6 The twenty year requirement promotes a conservative approach to defining
stability in that neighborhoods must avoid major fluctuations in race and ethnic
composition over a significant period of time to be considered stably integrated.
Before proceeding to a description of the dependent and independent variables
included in the analyses, it is important to address the issue of multiracial reporting in the
2000 census, and how this is addressed in the NCDB and impacts my typology. In the
2000 census, respondents were provided with the opportunity to self-identify as more
than one race for the first time, and 1 in 40 elected to do so (Lee and Bean 2007). The
NCDB follows a specific strategy developed to bridge racial and ethnic classifications
from earlier censuses with the 2000 census. The strategy is comprised of an algorithm
used to prioritize the classification of those who check two or more races (see Taitian
2003 for explanation of the bridging definitions used and the logic and rules of the
algorithm). For example, the first step in the algorithm is the classification of anyone
who identified as Black (in addition to any other race in which they also self-identified),
as Black. Someone who identified as White and Black would then be classified as Black
according to this rule. A set of additional hierarchically arranged rules in the algorithm
determine the single racial classification of all possible cases of multiracial reporting
(Taitian 2003).
Dependent Variables
All of the dependent variables in the analysis are comprised of outcomes or values
in 2000, while the independent and control variables represent values in 1980 or change
6
Throughout my dissertation I use the terms “stable” “long-term” and “non-transitioning” to refer to
integrated or homogenous neighborhoods in 1980 that are classified in the same racial/ethnic neighborhood
category in 2000.
59
between 1980 and 2000, in order to maintain appropriate time ordering in models. The
first four dependent variables reflect multinomial categorical neighborhood change
variables for analyses in Chapter 4. In examining neighborhood racial change here, I
diverge from past work that often predicts a continuous dependent variable of White-loss
from White-Black neighborhoods. The specific transitions examined follow descriptive
patterns of change outlined in Chapter 4. Therefore, they are spelled out in more detail at
that point.
The second set of dependent variables are all continuous, and represent 2000
neighborhood concentrated disadvantage and race-specific advantage for Whites, Blacks,
and Latinos in 2000. These variables and the associated analyses are included in Chapter
5. Concentrated Disadvantage 2000 is an index (α=.91) comprised of average z-scores
for five variables representing disadvantage in neighborhoods; the extent of femaleheaded households, percent of residents below poverty, proportion of households that
received public assistance, joblessness, and the proportion of persons in professional or
managerial occupations (reverse coded). This index is comparable to others used in
urban and crime studies (e.g. Krivo, Peterson, and Kuhl 2009; Krivo and Peterson 2008).
White Advantage 2000 is an index (α=.78) which consists of average z-scores for the
proportion of White residents who have a bachelors or advanced/professional degree, the
proportion of White households with an annual income that is equal to or greater than
$75,000, and the proportion of White persons in the tract below the poverty rate last year
(reverse coded).
Black Advantage 2000 is an index (α=.81) which consists of average z-scores for the
proportion of Black residents who have a bachelors or advanced/professional degree, the
60
proportion of Black households with an annual income that is equal to or greater than
$75,000, and the proportion of Black persons in the tract below the poverty rate last year
(reverse coded).
Latino Advantage 2000 is an index (α=.73) which consists of average z-scores for the
proportion of Latino residents who have a bachelors or advanced/professional degree, the
proportion of Latino households with an annual income that is equal to or greater than
$75,000, and the proportion of Latino persons in the tract below the poverty rate last year
(reverse coded).
For the three race-specific measures of advantage outlined above, it is important
to note that z-scores were calculated using the mean and standard deviations for the
average values for the combined populations of Whites, Blacks, and Latinos.7 This
allows for comparisons of the advantage indices across Whites, Blacks, and Latinos. If
the indices were constructed with the z-scores calculated independently using average
values specific to each group, the mean index value for each group would approximate 0,
masking significant differences among Whites, Blacks, and Latinos in levels of
advantage.
Key Independent Variables
The primary independent variables in the first set of multivariate analyses
(Chapter 4) pertain to the socioeconomic character of neighborhoods. I include a
measure for racial/ethnic inequality in poverty in neighborhoods (a measure of the Black
7
The means and standard deviations used to calculate the z-scores for the various factors in the White,
Black, and Latino advantage indices were as follows: College (mean 21.94 and standard deviation 21.65);
Affluent (mean 22.33 and standard deviation 23.12), Poverty (mean 88.74 and standard deviation 13.47).
These means and standard deviations represent the average values for Whites, Blacks, and Latinos
combined.
61
or Latino poverty rate in 1980 divided by the White poverty rate in 1980). Some argue
that class differences are the driving force behind neighborhood change, and that when
economic inequality between minorities and Whites is negligible, neighborhood stability
is much more likely (Allport 1954). In contrast, Nyden, Maly, and Lukehart (1997)
contend that economic heterogeneity fosters stable integration. Others find no evidence
of the significance of economic inequality between Blacks and Whites in the stability of
mixed-race neighborhoods (Galster and Keeney 1993) or in impacting the relationship
between neighborhood diversity and social capital (Putnam 2007).
I also include a concentrated disadvantage index for 1980 (α=.897) comprised of
measures of female-headed households, poverty, public assistance, joblessness, and
professional occupations (reverse coded).8 Racially segregated Black neighborhoods are
often contexts with high levels of concentrated disadvantage (Krivo et. al. 1998).
Disadvantaged neighborhoods may foster stability for segregated contexts because highly
disadvantaged areas may be seen as less desirable places to enter, and current residents
may have fewer resources to leave.
In predicting racial/ethnic change between 1980 and 2000, I also include a
measure of the change in median income in a tract between the two decades. For Latinos
and Asians, the literature suggests increases in socioeconomic status are associated with
higher levels of integration with Whites (Charles 2003: Alba et al. 1999). Furthermore,
significant growth in the median income in inner city segregated neighborhoods is
8
The variable professional occupations represents the proportion of persons 16 and older who are
employed in professional, technical occupations or as managers, executives, or administrators. I reversecode this variable to ensure the direction of the outcome is the same substantive direction as the other
measures included in the disadvantage index. This means larger values across all the included variables are
equated with higher levels of disadvantage.
62
sometimes associated with processes of gentrification (Freeman 2005; Freeman and
Braconi 2004; Crowder and South 2005).
The primary independent variables for the second set of multivariate analyses
(Chapter 5)
are racial/ethnic neighborhood stability dummy variables. Remained White is a dummy
variable where 1=A White neighborhood in 1980 remained predominantly White in 2000.
Remained Black is a dummy variable where 1=A Black neighborhood in 1980 remained
predominantly Black in 2000. Remained Latino is a dummy variable where 1=A Latino
neighborhood in 1980 remained predominantly Latino in 2000. Remained White-Black
is a dummy variable where 1=A White-Black neighborhood in 1980 remained
predominantly White-Black in 2000. Remained White-Latino is a dummy variable
where 1=A White-Latino neighborhood in 1980 remained predominantly White-Latino in
2000. Remained Latino-Black is a dummy variable where 1=A Latino-Black
neighborhood in 1980 remained predominantly Latino-Black in 2000. Finally,
Transitioned is a dummy variable where 1=A homogenous or integrated neighborhood in
1980 transitioned to some other racial/ethnic neighborhood type 2000.
Neighborhood Control Variables
An extensive literature documents metropolitan and neighborhood factors
associated with residential segregation and urban inequality (Farley and Frey 1994;
Massey and Denton 1993; Charles 2003; Iceland 2009). This literature serves as a useful
reference in thinking about why integrated neighborhoods housed in metropolitan areas
may remain stable or transition over time, as well as the factors that are important in
considering why neighborhoods and groups are more or less disadvantaged than others.
63
In particular, key demographic, economic, and housing indicators of neighborhoods and
the structuring of neighborhoods in metropolitan areas are especially important for these
outcomes. It is important to note that I detail below all of the neighborhood and
metropolitan controls used in the analyses in the analytical chapters. However, not all of
the variables are included in all of the models specified.
Demographic Factors
Neighborhood change may be influenced by several key demographic factors.
We know that central city neighborhoods are often disadvantaged and characterized as
highly segregated Black contexts (Massey and Denton 1993; Wilson 1987). We also
know that neighborhoods with a high proportion of immigrants may be less stable given
Whites’ relatively low threshold of comfort with minority neighbors (Charles 2006;
Krysan and Bader 2007; Charles 2001). To control for potential central city and
immigrant effects, I include a dummy variable, central city, signifying that 90% or more
of a tract is located in a central city. The 90% threshold is necessary because tracts are
often split across central city and suburban lines. To account for immigration, I include a
measure of the proportion foreign born, which represents the proportion of the tract
population that is foreign born. Additionally, I include a control for population size and
population change for tracts in the sample.
Socioeconomic Factors
For the models in Chapter 5 predicting race-specific advantage in 2000, I include
a set of socioeconomic controls for the neighborhoods in 1980. Specifically, I control for
median income, adjusted to 2000 dollars, and the % change in median income between
1980 and 2000. Both variables are continuous, with the change variable calculated by
64
constructing a proportion change variable comparing 1980 neighborhood median income
(in 2000 dollars) with 2000 neighborhood median income.
Housing
Several neighborhood housing characteristics are important to consider. I include
controls for growth in the housing market in a tract, which represents the percentage
change in the number of housing units in a tract between 1980 and 2000. It is plausible
that patterns of neighborhood racial transition and stability are constrained by the state of
the housing stock within neighborhoods (Brueckner and Rosenthal 2005; Rosenthal
2006). A growing housing market may provide more opportunities for stable integration
while stagnation is characteristic of metropolitan areas with high segregation (Farley and
Frey 1994). However, a growing housing market may also provide Whites with more
opportunities to flee integrated neighborhoods for more homogenous, predominantly
White areas.
Homeowners in a neighborhood may promote stability, as they have more
financial and emotional investments in their neighborhoods. They may be less likely to
leave, compared to renters, given the constraints tied to owning a home. Neighborhoods
with a high degree of renters may be less stable. Renters have greater flexibility to move,
are less financially invested in their homes, and are less likely to have strong ties to the
community compared to homeowners. An alternate interpretation would indicate that
higher levels of homeownership in integrated contexts may predict neighborhood
transition because of prejudice or negative stereotypes homeowners have about Blacks,
and because of the greater consequences they perceive in staying given their financial
investment (Harris 2001; 1999; Ellen 2000). To control for the potential effect of the rate
65
of homeownership in a tract, I include a measure for proportion owner occupied, which
represents the proportion of housing units in a tract that were owner-occupied in 1980.
Neighborhoods with many long-term residents have larger proportions of
inhabitants involvement in community activities and closer bonds in the neighborhood
(Lee et. al 1994). Logan and Sterns argue that a high degree of population turnover is
associated with less cohesiveness among residents and a greater likelihood of racial
change (1981). To account for the effect of residential instability, I include a control of
the proportion of households in 1980 who did not live in the census tract in the last five
years.
Metropolitan Controls
The segregation literature demonstrates the significant variation in patterns of
segregation across metropolitan areas that differ along various demographic, economic,
and housing characteristics. As such, I include controls for key metropolitan factors.
Newer metropolitan regions in the West and South are less segregated than those in the
Northeast and Midwest (Iceland 2009; Farley and Frey 1994). To control for regional
effects, I include dummy variables for neighborhoods located in metropolitan areas in the
Northeast, South, and Midwest (with West as the reference category).
Large and growing metropolitan areas are less segregated (Glaeser and Vigdor
2001). Logically, this would suggest that they would have increasing levels of
integration in neighborhoods compared with smaller or stagnant metropolitan areas. As
such, I include a measure of the % of population change between 1980 and 2000 in the
metropolitan area.
66
Metropolitan areas with higher levels of Hispanic and Asian immigration have
been associated with reductions in Black-White segregation (White and Glick 1999),
perhaps because some of the primary immigrant destinations are not heavily populated
with Blacks and are characterized by less racial tension (Farley and Frey 1994). Others
argue the effect of immigration may be due to Hispanics and Asians serving as a “buffer”
group (Iceland 2004, 2008) between Whites and Blacks. Krivo and Kaufman argue that
the influx of Asian and Latino immigrants in metropolitan areas could push Whites past a
fixed tolerance for minority contact, thus making Black-White desegregation less likely
(1999). Additionally, some argue that immigration of Latinos and Asians may bolster
segregated immigrant and ethnic enclaves (Glaeser and Vigdor 2001; Iceland 2004). I
include an aggregate measure of the metropolitan proportion foreign and the change in
proportion foreign born to control for these possible effects.
Decreased levels of segregation are associated with decreases in Black-White
income inequality, and this has been extensively examined in the literature (e.g., Krivo
and Kaufman 1999; Charles 2003; Farley and Frey 1994). I include a measure of
racial/ethnic inequality in poverty, calculated by constructing a ratio of Black to White
poverty (or Latino to White or Black to Latino) for the metropolitan area in 1980.
To account for the potential effect of varying levels of population growth for
groups in metropolitan areas for the outcomes examined, I include a measure of the
racial/ethnic growth difference in the metropolitan area. This is comprised of the ratio of
Black population growth in the metropolitan areas between 1980 and 2000 and White
population growth in the metropolitan area between 1980 and 2000 (a similar logic is
used to calculate Latino-White growth difference). White (1984) links changes in racial
67
composition in neighborhoods to the rate of increase of the Black and White populations
in the city. Denton and Massey (1991) find a significant correlation between the LatinoWhite growth difference in a metropolitan area and White loss in neighborhoods.
Finally, I include a control for residential segregation in the metropolitan area –
the Index of Dissimilarity, which represents the proportion of residents who would have
to move to a different tract to achieve absolute integration. Depending on the particular
analyses, the Index of Dissimilarity will measure segregation between Whites and
Blacks, Latinos and Whites, or Blacks and Latinos.
3.4 Analytic Strategy
Descriptive
Prior to examining the outcomes described in section 3.3, I conduct descriptive
analyses to begin to construct a national portrait of patterns of racial and ethnic
neighborhood integration in the United States between 1980 and 2000. I describe the
prevalence of homogenous and integrated neighborhoods in 1980, 1990, and 2000. I
examine the durability of integrated and homogenous neighborhoods over the two
decades by constructing a transition matrix which presents the distribution and nature of
change or stability for the sample of neighborhoods. I also contextualize these patterns
by examining the proportion of Latinos, Whites, and Blacks in metropolitan America that
live in the various neighborhoods, and the average amount of neighborhood and racespecific population change within long term integrated neighborhoods.
The second set of descriptive analyses are comprised of an assessment of patterns
of disadvantage associated with racially stable and transitioning neighborhoods, and
68
levels of advantage for the group members living in them. I examine patterns of mean
levels of concentrated disadvantage in 2000 for racially stable neighborhoods between
1980 and 2000. Next, I assess the degree of economic flux across the racially stable
neighborhoods over the two decades. Are the same integrated neighborhoods that are
advantaged in 1980 also advantaged in 2000? And for those that experience
socioeconomic flux, which neighborhoods improved and which declined? Finally, I shift
the unit of analysis from neighborhoods to race-specific mean levels of advantage. I
compare mean levels of advantage for Whites, Blacks, and Latinos residing in racially
stable and transitioning integrated contexts.
Analytical
I use multilevel models (Raudenbush, Bryk, and Congdon 2007; Raudenbush and
Bryk 2002) to conduct the analyses for the project.9 This method is particularly well
suited for the research questions I address, because I am examining outcomes for
neighborhoods that are nested within larger metropolitan areas. With multilevel models,
I am able to simultaneously assess the influence of both neighborhood (level-one units)
and metropolitan (level-two units) predictors and controls on each of the various
outcomes of interest. This is especially important for a study of neighborhood
integration, as the segregation literature indicates patterns of segregation and integration
are likely to be constrained by the nature of the metropolitan area within which
neighborhoods are housed (e.g., Farley and Frey 1994; Massey and Denton 1993; Iceland
2009). An additional feature of multilevel models is the correction of any problems with
independence of error terms and heteroskedasticity (Raudenbush and Bryk 2002).
9
I estimate all models with HLM 6.04 software.
69
I conduct three major sets of analyses. It is important to note that all binary
variables are uncentered, and all continuous variables are grand-mean centered to
facilitate ease of interpretation of results. Grand-mean centering is a technique in which
the continuous independent variables are scaled to change the meaning of the intercept
from a value of 0, to the expected outcome value when all of the predictors equal the
grand mean value. This ensures that coefficients can be interpreted as meaningful effects
on the neighborhood-level outcomes, within the metropolitan areas, net of the
neighborhood characteristics included in the models (Raudenbush and Bryk 2002).
Preliminary unconditional models were estimated to test for significant variation
in the outcomes. The variance component and chi-square tests for all of the
unconditional models are significant at p<.05. Finally, I examined the correlation of all
the variables in the models to ensure there were no problems associated with
multicollinearity that would bias the estimates.
First, to examine how neighborhood disadvantage, net of important housing and
demographic factors, is associated with stability and change for homogenous and
integrated neighborhoods, I estimate separate multinomial multilevel models for White,
Black, White-Black, and White-Latino neighborhoods in 1980. The dependent variables
for each of these models is categorical, with stability serving as the reference group. A
multinomial model is necessary because the dependent variable is comprised of three
nominal categories. Effects estimated are compared to the chosen omitted category for
the dependent variable. For example, for the Black-White model, I simultaneously
estimate the likelihood that a Black-White neighborhood in 1980 1. Became Black
instead of remaining White-Black in 2000, and 2. Became White instead of remaining
70
White-Black in 2000. Results for the other models predicting stability and change are
interpreted in a similar fashion, as an estimated likelihood that a neighborhood changed
in a particular way instead of remaining stable (the reference category). Results for these
models are presented in Chapter 4.
Second, to examine how long term racial and ethnic stability in homogenous and
integrated neighborhoods is related to concentrated disadvantage in 2000, I estimate a
hierarchical linear model with a sample of neighborhoods in 1980 that were classified as
White, Black, Latino, White-Black, White-Latino, and Latino-Black, regardless of their
classification in 2000. I regress 2000 concentrated disadvantage on various 1980
neighborhood and metropolitan controls, and the key variables of interest, dummy
variables for racially stable neighborhoods across the two decades (with one dummy
variable serving as the omitted reference group). I fit separate models, alternating the
dummy variable omitted, in order to test the significance of the difference in the effects
of racial/ethnic stability on concentrated disadvantage between all possible comparisons
of racial/ethnic trajectories for the neighborhoods. I conclude this section by calculating
predicted values for mean levels of concentrated disadvantage in 2000 based on the mean
observed neighborhood and metropolitan factors in the data. Results for this model are
presented in the first half of Chapter 5.
Third, to examine how long term racial and ethnic stability in homogenous and
integrated neighborhoods, net of controls, is related to race-specific advantage in 2000, I
estimate separate models for neighborhoods with Whites, Blacks, and Latinos. The
sample for each model includes the neighborhoods where the groups are represented in
large proportions. The key independent variables are the racial/ethnic stability dummies
71
in the first set of rows in each table (with only the relevant dummies included for each of
the separate models). As with the neighborhood-level analysis outlined in step 2 above, I
fit separate models with each racial/ethnic trajectory serving as the omitted reference
category. Doing so tests the significance of the difference in the effects with each other
in predicting mean levels of advantage for Whites, Blacks, and Latinos. Finally, I
calculate predicted values for mean levels of race-specific advantage in 2000 based on
the mean observed neighborhood and metropolitan factors in the data. Results for these
models are presented in the latter half of Chapter 5.
72
Table 3.1 Operationalization of All Variables
Variable
Operationalization
DEPENDENT VARIABLES
Black-White Neighborhood
Change 1980 to 2000
0=Became Black 1=Became White 2=stable (reference
category)
Latino-White Neighborhood
Change 1980 to 2000
0=Became Latino 1=Became White 2=stable (reference
category)
White Neighborhood Change
1980 to 2000
0=Became White-Black 1=Became White-Latino
2=Remained White (reference category)
Black Neighborhood Change
1980 to 2000
0=Became White-Black 1=Became Latino-Black
2=Remained Black (reference category)
Concentrated Disadvantage –
2000
(α=.91)
Average of z-scores for:
-Female-headed households with children in
tract divided by total households in tract
-Proportion of persons in tract below poverty
rate last year (1979)
-Proportion of households in tract with public
assistance income last year (1979)
-Proportion of persons 16+ who are in civilian
labor force and not employed
-Reverse coded proportion of persons 16+ who
are employed in professional, technical
occupations or as managers, executives, or
administrators
Average of z-scores for:
-Proportion of White residents 25+ who have a
bachelors or advanced/professional degree
-Proportion of White households with an annual
income over $75,000
-Reverse coded White persons in tract below the
poverty rate last year (1999) divided by total
White tract population
White Advantage – 2000
(α=.78)
Black Advantage – 2000
(α=.81)
Latino Advantage – 2000
(α=.73)
Average of z-scores for:
-Proportion of Black residents 25+ who have a
bachelors or advanced/professional degree
-Proportion of Black households with an annual
income over $75,000
-Reverse coded Black persons in tract below the
poverty rate last year (1999) divided by total
White tract population
Average of z-scores for:
-Proportion of Latino residents 25+ who have a
bachelors or advanced/professional degree
-Proportion of Latino households with an annual
income over $75,000
-Reverse coded Latino persons in tract below
the poverty rate last year (1999) divided by total
White tract population
Continued
73
Table 3.1 Continued
KEY INDEPENDENT VARIABLES
Socioeconomic
Black-White poverty inequality
Latino-White poverty inequality
Concentrated disadvantage
(α=.90)
Median Income
% Change in median income
Neighborhood Racial/Ethnic
Stability 1980 to 2000
Transitioned
Black poverty rate in 1980 divided by White poverty rate
in 1980
Latino poverty rate in 1980 divided by White poverty rate
in 1980
Average of z-scores for:
-Female-headed households with children in
tract divided by total households in tract
-Persons in tract below poverty rate last year
(1979) divided by total tract population
-Proportion of households in tract with public
assistance income last year (1979)
-Proportion of persons 16+ who are in civilian
labor force and not employed
-Reverse coded proportion of persons 16+ who
are employed in professional, technical
occupations or as managers, executives, or
administrators
Median income 1980 – adjusted to 2000 dollars
% of change in median household income 1980 to 2000
1=Neighborhood classification changed between 1980
and 2000 0=Neighborhood classification did not change
between 1980 and 2000
Remained White
1=Neighborhood remained predominantly White between
1980 and 2000 0=Neighborhood did not remain
predominantly White between 1980 and 2000
Remained Black
1=Neighborhood remained predominantly Black between
1980 and 2000 0=Neighborhood did not remain
predominantly Black between 1980 and 2000
Remained Latino
1=Neighborhood remained predominantly Latino
between 1980 and 2000 0=Neighborhood did not remain
predominantly Latino between 1980 and 2000
Remained White-Black
1=Neighborhood remained predominantly White-Black
between 1980 and 2000 0=Neighborhood did not remain
predominantly White-Black between 1980 and 2000
Remained White-Latino
1=Neighborhood remained predominantly White-Latino
between 1980 and 2000 0=Neighborhood did not remain
predominantly White-Latino between 1980 and 2000
Remained Latino-Black
1=Neighborhood remained predominantly Latino-Black
between 1980 and 2000 0=Neighborhood did not remain
predominantly Latino-Black between 1980 and 2000
NEIGHBORHOOD CONTROLS
Demographic
Central city
1=90% or more of tract located in central city 0=Less
than 90% of tract in central city
Proportion foreign born
Proportion of tract population foreign born
Population
Tract population size in 1980
Continued
74
Table 3.1 Continued
Population Change
Socioeconomic
Median Income
% Change in median income
Housing
Growth in housing units 1980 to
2000
Proportion owner occupied
Percentage change in tract population size between 1980
and 2000
Median income 1980 – adjusted to 2000 dollars
% of change in median household income 1980 to 2000
Percentage change in number of housing units in tract
Proportion of housing units in tract that are owneroccupied
Proportion recent mover
Proportion of households who did not live in tract in the
last five years (1975-1980)
METROPOLITAN CONTROLS
Region – Northeast
1=Northeast 0=Not in Northeast
- South
1=South 0=Not in South
- Midwest
1=Midwest 0=Not in Midwest
- West
1=West 0=Not in West
Population change
% of population change in the metropolitan area between
1980 and 2000
Black-White growth difference
Ratio of Black population growth in metropolitan area
between 1980 and 2000 and White population growth in
metropolitan area between 1980 and 2000
Latino-White growth difference Ratio of Latino population growth in metropolitan area
between 1980 and 2000 and White population growth in
metropolitan area between 1980 and 2000
Proportion Foreign Born
Proportion of persons who were foreign born in the
metropolitan area in 1980
Change in proportion foreign
% change in the proportion of persons foreign born in the
born
metropolitan area between 1980 and 2000
Black-White poverty inequality Ratio of the Black-White poverty rate difference in
neighborhoods in the metropolitan area in 1980
Latino-White poverty inequality Ratio of the Latino-White poverty rate difference in
neighborhoods in the metropolitan area in 1980
Black-White dissimilarity index Proportion of Black or White residents who would have
to move to a different tract to achieve absolute integration
Latino-White dissimilarity
Proportion of Latino or White residents who would have
index
to move to a different tract to achieve absolute integration
Latino-Black dissimilarity index Proportion of Latino or Black residents who would have
to move to a different tract to achieve absolute integration
75
Table 3.2 Mean and Standard Deviation for All Variables
Variable
Mean
Standard Deviation
Black-White neighborhood change
1980 to 2000
--
--
Latino-White neighborhood change
1980 to 2000
--
--
White Neighborhood Change 1980 to
2000
--
--
--
--
.000
.856
.440
.492
-.130
.937
-.143
.831
.276
.574
.053
.013
.039
.033
.009
.447
.494
.225
.112
.195
.178
.002
.365
6.911
3486.171
61.158
.481
7.868
1669.164
166.786
DEPENDENT VARIABLES
Black Neighborhood Change 1980 to
2000
Neighborhood Concentrated
Disadvantage – 2000
White Advantage – 2000
Black Advantage – 2000
Latino Advantage – 2000
Neighborhood Racial/Ethnic Stability
1980 to 2000
Transitioned
Remained White
Remained Black
Remained Latino
Remained White-Black
Remained White-Latino
Remained Latino-Black
Demographic
Central city
Proportion foreign born
Population
Population Change
Socioeconomic
Concentrated disadvantage 1980
Median Income 1980 – adjusted to
2000 dollars
% Change in median income
Black-White poverty inequality
Latino-White poverty inequality
Black-Latino poverty inequality
.000
.841
41703.278
14446.062
18.924
1.451
1.376
1.052
30.356
4.162
2.681
2.614
Continued
76
Table 3.2 Continued
Housing
Growth in housing units 1980 to 2000
Proportion owner occupied
Proportion recent mover
68.588
68.227
54.122
165.457
22.906
16.010
Region - Northeast
- South
- Midwest
- West
Population change
Black-White growth difference
Latino-White growth difference
Black-Latino growth difference
Proportion Foreign Born
Change in proportion foreign born
.230
.311
.235
.224
30.031
-6.644
-14.393
.836
7.120
87.524
.421
.463
.424
.417
27.912
30.883
44.748
4.990
6.268
84.163
Black-White poverty inequality
3.262
1.137
Latino-White poverty inequality
2.543
1.202
Black-Latino Poverty Inequality
1.422
.712
Black-White dissimilarity index
Latino-White dissimilarity index
Latino-Black dissimilarity index
69.714
44.206
60.306
12.821
12.345
13.117
77
Chapter 4
Patterns and Sources of Change in Racial and Ethnic Neighborhood Integration
4.1 Introduction
In this chapter, I begin the process of assessing the suitability of long-term racial
ethnic integration as a policy initiative given theoretical arguments about the racialized
context of the U.S. social order. Prior to examining the character of long-term integrated
neighborhoods (i.e., their associated social and economic outcomes), we must first
understand the degree to which long-term racial/ethnic integration actually occurs, and
the factors that significantly impact the odds that a neighborhood will become or remain
integrated. The extent to which long-term racial integration is possible, given broader
societal factors and constraints, plays a substantial role in determining the range of
potential impact (positive, negative, or negligible) on neighborhood and group-level
racial inequality. I begin by providing a descriptive portrait of patterns and changes in
racial and ethnic neighborhood integration in U.S. metropolitan areas between 1980 and
2000, followed by results for models that specify the significant factors responsible for
promoting or maintaining integration. The questions I ask in this chapter are simple, yet
provide detailed information about national trends in metropolitan neighborhood
integration. How many neighborhoods were racially integrated during the two decades?
Who actually lived in these neighborhoods? What happened to these neighborhoods –
78
did they stay the same or change over time? And finally, why did some stay the same
and others change?
To address these questions, I employ both descriptive and analytic methods.
First, I describe the prevalence of homogenous and integrated neighborhoods in 1980,
1990, and 2000. Second, I examine the degree to which these neighborhoods transition
or remain similar in racial/ethnic composition over the two decades. Throughout the
chapter, I place particular emphasis on the necessity to ensure the results are interpreted
within the broader context of where individuals live and how much individual-level
change occurs within neighborhoods. I do this by including an individual-level
assessment of the proportion of Latinos, Whites, and Blacks in metropolitan America that
live in the various neighborhoods. Additionally, I assess overall neighborhood
population and race-specific population change within long term integrated
neighborhoods. Finally, I specifiy multinomial hierarchical models to estimate the odds
an integrated or homogenous neighborhood in 1980 remained the same or transitioned to
some other type of neighborhood in 2000.
4.2 The Prevalence of Racial and Ethnic Neighborhood Integration – 1980 to 2000
How common was integration?
Table 4.1 presents frequency distributions of racial and ethnic neighborhood types
for 1980, 1990, and 2000. It is immediately clear that racial/ethnic integration was not
particularly common. The vast majority of neighborhoods were homogonous across the
two decades. However, the proportion of neighborhoods dominated by a single group
declined from 82.7% of all tracts in 1980 to 77.9% in 1990 and decreased again to 70.8%
79
in 2000. This is due exclusively to a large decline in the proportion of White areas.
While three-quarters of neighborhoods were predominantly White in 1980, this is the
case for just 58% of areas in 2000. At the same time, Latino dominated areas increased
substantially, with the number nearly tripling across the two decades, from 570 to 1649.
The percentage and overall number of predominantly Black and Other neighborhoods
also increased slightly during this period.
It is also clear that the proportion of integrated neighborhoods grew over time. In
2000, almost 30% of neighborhoods were integrated compared to just under 17% in
1980. Neighborhoods comprised predominantly of two groups were the most common
form of integration, increasing from just 16.4% of neighborhoods in 1980 to 26.4% in
2000. In both decades, Latino-White and Black-White were the most numerous by a
large margin. The prevalence of each also increased over the decades, with this growth
being particularly sizeable for White-Latino areas. The percentage of White-Latino areas
increased from 6.9% to 10.9%. White-Black neighborhoods increased from 7.5% to
9.4%. Black-Latino (2.6%) and White-Other (2.6%) neighborhoods were much less
common, though both more than doubled in number over the two decades. Though
relatively rare as a whole, the percentage of three-group neighborhoods grew
substantially from .9% to 2.8% of all neighborhoods. There were virtually no four-group
neighborhoods throughout the twenty year period.
Who Lived in These Neighborhoods?
The results in Table 4.1 show the distribution of neighborhoods by race-ethnic
type for the three decades. It is important to contextualize these patterns by assessing
where individuals actually lived. In this section, I address the question of what
80
percentage of individuals overall, and Blacks, Latinos, and Whites specifically, actually
lived in each of these neighborhood types.
Table 4.2 presents frequency distributions of the percentage of individuals, overall and by
race/ethnicity, living in each of the homogenous and integrated contexts for 1980 and
2000. Not surprisingly, the overall individual-level patterns largely mirror the
neighborhood-level results. The results in columns 1 and 5 indicate that the majority of
individuals lived in the most common forms of homogenous and integrated contexts in
1980 and 2000 – White, Black, Latino, White-Latino, White-Black, and Latino-Black. In
1980, fully 98.1% of all individuals in the sample resided in one of these six
neighborhood types. In 2000, fully 92.9% of all individuals were represented in one of
these types of neighborhoods.
Second, the majority of individuals lived in single-group neighborhoods in both
decades, though the proportion dropped somewhat over time. In 1980, 82.5% of
individuals lived in homogenous neighborhoods and 17.5% lived in integrated
neighborhoods. In 2000, the proportion of individuals living in homogenous
neighborhoods dropped to 70.4%, and the proportion living in integrated neighborhoods
grew to 29.6%.
When examining the racial/ethnic distribution of individuals across the areas,
located in columns 2-4 and 6-8 of the table, several noteworthy patterns emerge. First,
all racial/ethnic groups were more likely to reside in integrated neighborhood types in
2000 than they were in 1980. However, Whites were substantially less likely than Blacks
and Latinos to reside in integrated contexts, with just 10.8% in 1980 and 19.4% in 2000
located in integrated neighborhoods. In contrast, 35.2% of Blacks in 1980 and 44.2% in
81
2000 lived in integrated neighborhoods. Latinos were the most likely in 1980 and 2000
to live in an integrated neighborhood (50.8% and 53.2%, respectively).
Not surprisingly then, Whites were substantially more likely to reside with
residents of their same racial/ethnic background than both Blacks and Latinos. In 1980,
close to 90% of Whites lived in predominantly White contexts, and nearly 80% did so
twenty years later. The patterns for Blacks and Latinos contrast sharply with those for
Whites. Nearly 50% of Blacks in 1980 and about 37% in 2000 lived in mainly Black
areas. Latinos were the least likely of the three groups to live in same-group
neighborhoods, with just 16.4% in 1980 and 26.1% in 2000 living in predominantly
Latino areas. However, though least likely to live in same-group neighborhoods
compared to Blacks and Whites, Latinos were the only group in which the percentage
likely to do so increased between 1980 and 2000. This pattern may not be surprising in
light of evidence of growth in Latino-White residential segregation during this time
period (Iceland 2009; Charles 2003).
It is important to note the significance of the above results in relation to those
presented in Table 4.1. They suggest the decline in the number and percentage of
predominantly White neighborhoods revealed in Table 4.1, from 74.8% to 58.5%, is not
necessarily indicative of a substantial decline in the concentration of Whites over the two
decades. The shift in the percentage of Whites living in integrated neighborhoods did not
match the shift in the declining percentage of primarily White neighborhoods. While the
change in the number of primarily White neighborhoods was -27.8%, the change in the
number of individual Whites living in mainly White areas was only -11.6%; a difference
of over 16%. This is significant, as despite the increase in the number of integrated
82
neighborhoods shared by Whites and Blacks and Latinos, most Whites continued to live
primarily with other Whites in both 1980 and 2000. Similarly, though the figures in
Table 4.1 also suggest a slight increase in the number and percentage of Black
neighborhoods (from 6.3% to 7.7%), the results in Table 4.2 show a decline in the
percentage of Blacks who live in neighborhoods comprised primarily of Blacks (from
48.8% to 36.8%).
Another important pattern in Table 4.2 pertaining to homogenous neighborhoods
involves the presence of the small but notable percentage of Blacks and Latinos who
lived in predominantly White areas. While a negligible portion (less than 1%) of Whites
lived in Black or Latino neighborhoods, a considerable percentage of Blacks and Latinos
lived in predominantly White areas in both decades. Specifically, almost 16% of Blacks
lived in White neighborhoods in 1980 and over 17% did so in 2000; 30% of Latinos in
1980 and 19% in 2000 lived in White contexts. It is unclear though, whether this is
indicative of White neighborhoods on the path to future integration, or instead, the longterm presence of a “token” representation of Blacks or Latinos in these neighborhoods.
A final noteworthy pattern in Table 4.2 is the concentration of Whites in a few
neighborhood types, and the spread of Blacks and Latinos across more types of areas.
Columns 2 and 6 in Table 4.2 show that over 98% of Whites in 1980 and nearly 95% in
2000 lived in just three neighborhood types - White, White-Latino, and White-Black. In
contrast, nearly 99% of Blacks in 1980 and over 94% in 2000 were spread across six
neighborhood types – Black, White-Black, White, Latino-Black, White-Latino, and
White-Black-Latino. Latinos were spread across the largest number of contexts. In
1980, 97.2% of Latinos, were spread more heavily across seven contexts - White-Latino,
83
White, Latino, Latino-Black, White-Black, Black, and White-Black-Latino. The
percentage increased slightly to 97.8% in 2000.
While Tables 4.1 and 4.2 show a clear increase between 1980 and 2000 in the
proportion of integrated neighborhoods and the number of individuals living in them,
they do not indicate whether or not neighborhoods integrated in 1980 remained so in
2000. In the next section, I address this question, asking: how have the neighborhoods
transitioned across the decades?
4.3 Racial and Ethnic Stability and Change in Metropolitan Neighborhoods
How common was long-term integration?
Table 4.3 presents a transition matrix of U.S. racial and ethnic neighborhood
change between 1980 and 2000. Neighborhoods examined include only those that were
one of the six most common neighborhood types in 1980 – White, Black, Latino, WhiteLatino, White-Black, and Latino-Black.1 These neighborhoods represent fully 98.1% of
all metropolitan neighborhoods and 98.1% of all individuals in 1980.2 All potential
trajectories of change are considered for these six neighborhood types, as represented in
the fifteen distinct categories in the columns of the matrix. Each cell represents the
proportion of neighborhoods that were a particular type in 1980 (the row category) and a
particular type in 2000 (the column category). The values in bold along the diagonal
represent long-term stability, indicating the proportions of neighborhoods in 1980 that
were classified the same way in 2000. The values in the off diagonal represent the
1
The additional tables section at the end of Chapter 4 presents a full transition matrix inclusive of all 15
neighborhood types.
2
These percentages are calculated from results presented in Table 4.1 and 4.2.
84
proportions of transitioning (or unstable) neighborhoods in 1980 that took one of fourteen
other possible trajectories.
It is immediately clear from the table that there is considerable variation in
whether different types of neighborhoods in 1980 remained stable in type or transitioned
to another type in 2000. When comparing single-group and integrated neighborhoods as
a whole, integrated neighborhoods appear significantly less stable than single-group
neighborhoods. Namely, 88.6% of Latino, nearly 85% of Black, and over 76% of White
neighborhoods in the sample in 1980 remained single-race neighborhoods in 2000. For
integrated neighborhoods, patterns of stability depended on the neighborhood type,
ranging from 47.3% to 72.1% in the sample of two-group neighborhoods. Only about
half of White-Latino (47.3%) and White-Black neighborhoods (52.4%) in 1980 remained
integrated in 2000. Of all the two-group neighborhoods, Latino-Black contexts
experienced the least amount of transition, with 72.1% remaining stable (just 5% less
than White only neighborhoods).
While the results above suggest great variation in the odds of maintaining
racial/ethnic stability across two decades, depending on the type of neighborhood, we do
not know from these tables how much, if any, population and racial/ethnic change
occurred within racially stable neighborhoods. Table 4.4 presents the median
proportional and numeric neighborhood population change in racially and ethnically
stable neighborhoods. As a whole, substantial flux – either growth or decline - is evident
across all the neighborhood types. Black and White-Black contexts declined in
population size, while all other contexts experienced growth. Among the stable
integrated contexts with Whites, White-loss occurred in both White-Black (25% on
85
average) and White-Latino (19% on average) areas. The impact of this loss, coupled with
concurrent growth of Blacks and Latinos, was not sufficient to alter the classification of
these neighborhoods as stable. However, these patterns support the depiction of
integrated neighborhoods in the urban literature, even seemingly stable ones, as
characterized by White-loss.
What happened to unstable neighborhoods?
For those neighborhoods that experienced sufficient growth or decline in
representation of racial and ethnic groups to alter the classification of the neighborhood
over time, what happened? Specifically, what were the most common forms of change
for previously homogenous and integrated areas? Cells off of the diagonal in Table 4.3
show the many paths unstable neighborhoods took. Unstable White neighborhoods were
most likely to become either White-Latino (9.9%) or White-Black (7.0%). The majority
of Black neighborhoods that transitioned between 1980 and 2000 became Latino-Black
(10.7%) with the next most common change being to White-Black contexts (3.3%).
Unstable Latino neighborhoods most likely became either White-Latino (4.9%), LatinoBlack (3.2%), or Latino-Other (2.6%).
Among the sample of two-group neighborhoods, the majority of change was
characterized by transition from an integrated to a single-group context, though in several
cases more than a negligible number of areas transitioned from one integrated context to
another. For unstable Latino-White neighborhoods, a large proportion became Latino
(32.5%), though about 5% become White or White-Other. While the most common form
of change for formerly Black-White neighborhoods was to become Black (24.3% of
86
cases), over 10% became White. The majority of unstable Latino-Black neighborhoods
that transitioned became Latino (17.9%), while just 3.3% became Black.
4.4 Why Did Neighborhoods Become Integrated, Become Homogenous, or Stay the
Same?
The first three sections of Chapter 4 examined the prevalence and stability of
homogenous and integrated neighborhoods from 1980 to 2000, as well as the population
distribution and change within them. The results showed that integrated neighborhoods
were quite unstable compared to homogenous neighborhoods – particularly White-Black
and White-Latino areas which had a near 50% chance of transitioning to a homogenous
neighborhood over the period. On the other hand, homogenous neighborhoods were
primarily stable, with just a small proportion transitioning to integrated contexts. The
question that remains is what explains the variation in the durability of these integrated
and homogenous neighborhoods? Why did some of these communities experience racial
and ethnic flux, while others remained racially ethnically stable? What factors increased
the odds that an integrated neighborhood remained so over time? Were there meaningful
differences between those integrated neighborhoods able to remain constant over the long
haul compared to those that changed?
In the second half of this chapter, I address these questions by examining the
neighborhood and metropolitan characteristics associated with stability and instability
between 1980 and 2000 for the most common homogenous and integrated
neighborhoods. In particular, I assess whether the socioeconomic characterization of
these communities played a significant role in predicting their likelihood to change or
87
stay the same. If the socioeconomic characterization of a neighborhood is important net
of other factors, how does it matter for the different communities?
First, I examine the socioeconomic distribution of racially stable neighborhoods,
both integrated and homogenous, in 1980. Next, the analytical analyses are comprised of
multinomial hierarchical linear models to assess the demographic, housing, and
soceioeconomic factors that predict the likelihood that neighborhoods remained racially
and ethnically stable over time. My primary goal is to determine the relationship
between disadvantage/advantage and neighborhood racial/ethnic stability and change, net
of other factors. Here, I focus on the most common forms of integrated and homogenous
neighborhoods across the two decades – White, Black, White-Black, and White-Latino
neighborhoods. The first set of models examines the relationship between
advantage/disadvantage and stability between 1980 and 2000 for neighborhoods that
were integrated in 1980, net of important demographic and housing factors at the
metropolitan and neighborhood level. The second set of models examines the
relationship between advantage/disadvantage and transitioning from a homogenous
neighborhood in 1980, to an integrated neighborhood in 2000, net of important
demographic and housing factors at the metropolitan and neighborhood level.
4.5 The Socioeconomic Character of Racially/Ethnically Durable Neighborhoods
Table 4.5 presents a frequency distribution of the economic classification in 1980
of the neighborhoods that were racially/ethnically durable between the two time points.
Middle Advantaged neighborhoods are those within one standard deviation below or
above the mean disadvantage level of all metropolitan neighborhoods in the U.S. in 1980.
88
Disadvantaged neighborhoods are those with disadvantage scores at or below one
standard deviation from the mean for all neighborhoods. Advantaged neighborhoods are
considered as those with disadvantage scores at or above one standard deviation from the
mean for all neighborhoods.3
The first three rows in the table look at patterns for homogenous White, Black,
and Latino neighborhoods. The bottom three rows examine the patterns for integrated
White-Latino, White-Black, and Latino-Black neighborhoods. As a whole, results follow
theoretical expectations. The first row of Table 4.5 shows that nearly 99% of White
neighborhoods were moderately or highly advantaged in 1980. For all other
neighborhoods, a hierarchical patterning of advantage is clear, with those partially
comprised of Whites at the top, and neighborhoods with few Whites at the bottom.
Specifically, in both decades, the majority of integrated neighborhoods with many Whites
(White-Latino and White-Black) were substantially more advantaged than neighborhoods
comprised mainly of Latinos or Blacks. For example, 83.8% of White-Latino
neighborhoods in 1980, and 70.9% of White-Black neighborhoods in 1980, were middle
or highly advantaged. In stark contrast, the majority (63.7%) of Latino neighborhoods
were disadvantaged in 1980, as were over four fifths of Black neighborhoods (81.5%).
Finally, integrated Latino-Black neighborhoods were the most disadvantaged in 1980;
91.9% had very high levels of disadvantage.
These patterns suggest that integrated neighborhoods, so long as they are
comprised partially of Whites, do appear to be more socioeconomically advantageous
environments for Blacks and Latinos compared to predominantly Black and Latino
3
See Chapter 3 for more detail about how the disadvantage index and scale was constructed.
89
neighborhoods. However, Table 4.5 also suggests a racially hierarchical patterning of the
relationship between advantage and disadvantage for racially stable neighborhoods. As
predicted by the race theory explicated in Chapter 2, neighborhoods with Whites are the
most advantaged, neighborhoods with Blacks the least advantaged, and neighborhoods
with Latinos situated somewhere in the middle. The presumed economic advantage for
integrated neighborhoods with Blacks and Latinos compared to their homogenous
counterparts holds, as long as a large proportion of Whites are also present in these
integrated settings. The case of Latino-Black neighborhoods, which were the most stable
both racially and economically in terms of disadvantage, further demonstrates this is the
case.
Yet, conclusions from these descriptive analyses are limited for several reasons.
It is important to remember that, as revealed in Chapter 4, only approximately 47% of
White-Latino and 52% of White-Black neighborhoods in 1980 remained so in 2000. To
completely understand the relationship between advantage/disadvantage and
neighborhood racial stability and change, we must assess whether the neighborhoods
included in the descriptive table are meaningfully different from those not included transitioning contexts. Specifically, we must examine how advantage/disadvantage is
associated with neighborhoods with Blacks, Whites, and Latinos that remain
homogenous, become integrated, remain integrated, or become homogenous. It is
possible that, controlling for important neighborhood and metropolitan demographic and
housing factors, the presumed advantage associated with stable White-Black and stable
White-Latino neighborhoods, may disappear. In the next section, I address this issue
90
through analytical models predicting stability and change for White-Black, White-Latino,
White, and Black neighborhoods.
4.6 Integrated Neighborhoods, Advantage/Disadvantage, and Racial/Ethnic
Stability and Change
Table 4.6 presents results from the hierarchical multinomial logit analyses
predicting White-Black neighborhood change between 1980 and 2000. The table is
comprised of two columns of results, as the dependent variable is a categorical change
variable where 0=became Black, 1=became White, and 2=remained stable (the reference
category). The coefficients in column 1 specify the likelihood that a Black-White
neighborhood in 1980 became Black in 2000 instead of remaining Black-White. The
coefficients in column 2 specify the likelihood that Became White neighborhood in 1980
became White in 2000 instead of remaining Black-White.
The multivariate analyses reveal several interesting patterns. First, net of
demographic, housing, and metropolitan characteristics, integrated Black-White
neighborhoods in 1980 with lower levels of disadvantage were more likely to transition
to White neighborhoods than remain integrated. More disadvantaged Black-White
neighborhoods were more likely to transition to Black neighborhoods than remain
integrated. Black-White neighborhoods with more racial inequality in poverty rates were
more likely to remain integrated than become Black. This supports Nyden, Maly, and
Lukehart’s (1997) argument that greater economic heterogeneity may foster stable
integration.
In terms of other neighborhood factors, White-Black neighborhoods were more
likely to become Black and less likely to become White (than remain integrated) when
91
located in the central city. Black-White neighborhoods with more homeowners and less
population turnover were more likely to become Black than to remain stable. While this
may contradict the idea that homeownership fosters stability, some argue that White
homeowners may feel particularly sensitive to diversity in their neighborhood if they are
prejudiced or hold stereotypical views associated with Black neighbors (Harris 1999,
2001; Ellen 2000). Whites may actually be more likely to leave integrated contexts
because of perceived concerns over their financial investment (Ellen 2000). Finally,
Black-White neighborhoods with more housing growth were more likely to become
White than remain stable.
Results for the metropolitan controls show that Black-White neighborhoods
located in the Northeast, Midwest, and South were less likely to become White and more
likely to become Black than remain stable than those neighborhoods in the West. For
neighborhoods in the South, it is possible that this may be a simple function of the lower
proportion of Black residents in Southern metropolitan areas (see Krivo and Kaufman
1999).4 Black-White neighborhoods situated in metropolitan areas with higher levels of
racial inequality in poverty and Black-White segregation were more likely to become
Black than remain stable. Higher levels of immigrants in 1980 as well as increases in the
flow of immigrants in metropolitan areas are both positively associated with Black-White
neighborhoods becoming Black as opposed to remaining integrated. This contradicts the
argument that Latino and Asian immigrants may serve as a buffer between Blacks and
Whites in metropolitan areas, fostering less segregation (Iceland 2009), and supports the
4
I was not able to control for proportion Black at the metropolitan level because of insufficient variation
across the metropolitan areas in the sample of Black-White neighborhoods that became White, Black, or
remained integrated between 1980 and 2000.
92
argument that increases in Latino and Asian immigrants may actually impede integration
as Whites are pushed past their fixed tolerance for minority contact (Krivo and Kaufman
1999). Finally, as expected, Black-White neighborhoods were more likely to transition to
Black contexts as opposed to remaining stable when located in more segregated
metropolitan areas.
Table 4.7 presents results from the same model for neighborhoods that were
Latino-White in 1980. The dependent variable represents the most common racial/ethnic
trajectories for Latino-White neighborhoods between 1980 and 2000 – remaining LatinoWhite, becoming Latino, or becoming White. Results for the Latino-White sample
largely mirror those for the Black-White sample, with a few exceptions. Most
importantly, as with Black-White neighborhoods, disadvantage seems to undermine
integration while integration is reinforced by economic inequality between Whites and
Latinos. More highly disadvantaged Latino-White neighborhoods were more likely to
become Latino than remain stable. Those with lower levels of disadvantage were more
likely to become White. Neighborhoods with more residential instability were also morelikely to become Latino than remain integrated. However, in contrast to Black-White
neighborhoods, Latino-White neighborhoods in the central city were no more likely to
transition to Latino or White contexts than remain integrated. Also, neighborhoods with
more immigrants were more likely to become Latino than remain integrated. Those with
relatively fewer immigrants in 1980 were more likely to remain integrated than become
White. Finally, neighborhoods with a higher proportion of homeowners were more
likely to become Latino or remain integrated than become White.
93
Metropolitan level controls for Latino-White neighborhood change differed
somewhat from those important for Black-White neighborhoods. Similar to the BlackWhite models, higher levels of segregation increased the likelihood that a Latino-White
neighborhood became Latino. Unlike Black-White neighborhoods, racial/ethnic poverty
inequality at the metropolitan level had no effect on neighborhood transition for LatinoWhite neighborhoods. Additionally, region is mostly not significant for the Latino-White
models in contrast to the Black-White models. Surprisingly, the proportion of
immigrants in the metropolitan area had no significant effect on the likelihood that a
neighborhood became Latino or remained Latino-White (though change in immigration is
significant).
4.7 Homogenous Neighborhoods, Advantage/Disadvantage, and Racial/Ethnic
Stability and Change
Table 4.8 presents results from the multivariate analyses predicting White
neighborhood change between 1980 and 2000, with stability as the reference category.
Column 1 presents coefficients for neighborhoods that became White-Black versus
remaining stable, and column 2 presents coefficients for neighborhoods that became
White-Latino versus remaining stable. Coefficients have the same type of meaning as in
the previous two tables; coefficients specify the likelihood that a neighborhood remained
homogenous or became integrated over the two decades.
The multivariate analyses reveal several important patterns. Most importantly,
net of demographic, housing, and metropolitan factors, White neighborhoods were more
likely to become integrated White-Black or White-Latino than remain White, if they were
more disadvantaged in 1980. Conversely, less disadvantaged White neighborhoods were
94
more likely to remain White than become integrated. Additionally, White neighborhoods
in the central city with fewer homeowners and more Black-White poverty inequality were
more likely to become White-Black than remain White. White neighborhoods were also
more likely to become White-Latino than remain White if they were located in the central
city with fewer homeowners and more Latino-White poverty inequality. Neighborhoods
with more racial inequality in poverty rates, less homeownership, and less growth in the
housing market, were more likely to become White-Black than remain White. Finally,
neighborhoods with a growing housing market were more likely to remain White than
become integrated.
At the metropolitan level, neighborhoods in the Northeast and Midwest were
more likely to become White-Black than remain White, but less likely to become WhiteLatino than remain White than those in the West. White neighborhoods in the South
were also more likely to become White-Black than remain White compared to those in
the West, but were no more or less likely than those in the West to become White-Latino
or remain White. White neighborhoods in metropolitan areas with declining population,
more Black-White poverty inequality, more Black-White growth difference, and more
Latino-White growth difference were more likely to become Black-White than remain
White. Finally, White neighborhoods in metropolitan areas in 1980 with more population
growth, more immigrants in 1980 and growth in immigrants over the two decades, more
Latino-White segregation, and more Latino-White growth difference, were more likely to
become Latino-White than remain White.
Table 4.9 presents results from the multivariate analyses predicting Black
neighborhood change between 1980 and 2000, with stability as the reference category.
95
Column 1 presents coefficients for neighborhoods that became White-Black versus
remaining Black, and column 2 presents coefficients for neighborhoods that became
Latino-Black versus remaining Black. Most importantly, results indicate a clear
relationship of disadvantage being associated with greater odds of a neighborhood
remaining Black or becoming Latino-Black.
Furthermore, neighborhoods outside of the central city, with a greater share of
immigrants, growth in housing units, and less homeowners were more likely to become
White-Black than remain Black. It is possible, given the larger share of immigrants, that
these neighborhoods are not African American but Black immigrant neighborhoods.
Black neighborhoods in metropolitan areas in the West were more likely to become either
White-Black or Latino-Black than those in any other region. Neighborhoods in
metropolitan areas with more immigration were more likely to remain Black than become
White-Black.5
4.8 Discussion and Conclusion
The analyses in this chapter delineate the complicated nature of patterns of
neighborhood integration and change in metropolitan America between 1980 and 2000.
As a whole the story of metropolitan neighborhood racial and ethnic change appears to be
characterized best by one of flux. Table 4.4 showed that even seemingly stable
neighborhoods experienced marked fluctuations in population size and character. All of
these findings cast doubt on the simple conclusion that metropolitan neighborhoods are
increasingly racially and ethnically diverse; they may be, but potentially only for a period
5
As a result of lack of significant variation in outcomes and several level-2 controls, it was not possible to
fit models for Latino and Latino-Black neighborhoods.
96
of time. This signifies potentially serious problems with simple assertions about the rise
of neighborhood integration and associated benefits for Blacks and Latinos.
Even so, at the most basic level, single-group areas remained the norm, with over
two-thirds characterized as such during the time period, it appears that a greater
proportion of neighborhoods were integrated in 2000 (29.2%) than in 1980 (17.3%).
However, when these patterns are further deconstructed and interpreted within the
broader context of the subsequent analyses presented in the chapter, a more complicated
story begins to emerge.
First, it may appear, from the drop in the proportion and number of largely White
neighborhoods in Table 4.1, that White concentration has also similarly sharply declined.
However, the results in Table 4.2 show otherwise. Whites continued to remain
significantly more likely to reside mostly with other Whites in 2000; the small rate of
change in the distribution of Whites in predominantly White neighborhoods did not
match the larger rate of change in the number and proportion of White neighborhoods.
Interestingly, a considerable proportion of Blacks and Latinos were also likely to
reside in homogenous neighborhoods. However, unlike the patterns for Whites, this
includes same-group as well as different-group (White) homogenous contexts. While
slightly over 50% of Blacks and 46% of Latinos lived in single-group neighborhoods in
2000, a substantial proportion of these individuals (over 17% of Blacks and over 25% of
Latinos) lived in predominantly White neighborhoods. Table 4.4 also indicates that, on
average, long-term White neighborhoods were characterized by Black population growth
and Latino population growth. While the segregation literature has understandably
focused on segregated Black or Latino neighborhoods in studies of neighborhood
97
inequality and the consequences of long-term residential segregation for minorities, Table
4.2 shows that nearly 74% of Latinos and over 63% of Blacks lived in contexts other
than same-group neighborhoods in 2000. These findings highlight the necessity of
accounting for the actual neighborhoods where large portions of historically subordinated
group members reside when studying group or neighborhood-level inequality. For my
dissertation specifically, this finding highlights the necessity to compare the social and
economic character of the full range of homogenous and integrated settings where these
group members are likely to reside.
One of the most important findings from the chapter, when contemplating the
larger dissertation question about the validity of stable integration as a beneficial policy
initiative, pertains to the odds an integrated neighborhood in one decade will remain so
two decades later. Though more neighborhoods became integrated, homogenous
neighborhoods as a whole were significantly more stable than integrated neighborhoods.
Approximately 50% of the most common integrated areas in 1980, Black-White and
Latino-White neighborhoods, remained so in 2000. Latino-Black neighborhoods,
increasing in number and proportion but still only 2.6% of all neighborhoods in 2000,
were significantly more stable than Black-White and Latino-White areas; over 72%
remained Latino-Black over the two decades. These findings suggest that both stability
and instability are nearly equally likely in cases of integration of non-Whites with Whites
in neighborhoods, and that cases of integration between non-White groups are much
more likely to remain stable than cases with Whites and non-Whites.
It is difficult to know how to interpret the implication that Black-White and
Latino-White neighborhoods, the most common form of neighborhood integration in the
98
United States, likely have a fifty-fifty chance of remaining integrated long-term. Is this a
positive finding (a fifty percent chance) or negative (only a fifty percent chance). The
multivariate results in the second half of the chapter help to begin to answer this question
by assessing how levels of advantage/disadvantage, one important feature of
neighborhood quality, predicted whether or not neighborhoods remained stable or
transitioned.
Collectively, the multivariate results in Tables 4.6-4.9 present a clear association
between advantage and the presence of Whites in neighborhoods. This is not surprising.
The analyses revealed a striking pattern for both Latino-White and Black-White
neighborhoods: more advantaged integrated neighborhoods were more likely to transition
to predominantly White contexts than remain stable, and the more disadvantaged contexts
were more likely to transition to Latino or Black contexts. These findings suggest
neighborhood advantage may undermine integration and maintain White segregation.
Disadvantage may foster integration for previously homogeneous White neighborhoods,
and maintain segregation for homogenous Black neighborhoods. Despite the higher
mean levels of advantage revealed in the descriptive tables for racially stable WhiteBlack and White-Latino neighborhoods compared to Black and Latino neighborhoods,
the statistical models call into question any generalized assertion of a positive
relationship between socioeconomic advantage and long term racial/ethnic integration.
Simply put, these patterns contradict the framing of integration as a means of reducing
the deleterious consequences associated with segregated Black and Latino
neighborhoods, as integrated neighborhoods that are more advantaged are less likely to
remain integrated over time.
99
The analysis in this chapter provides a useful starting point to assess the
socioeconomic and social consequences associated with integration for Blacks, Whites,
and Latinos. The results demonstrate that advantage may undermine stability for BlackWhite and Latino-White neighborhoods, and foster stability for White neighborhoods.
However, the multivariate analyses are limited in several ways. First, they only focus on
four of the six most common racial/ethnic neighborhood types in the United States in
1980 and 2000; I was unable to estimate odds that Latino and Latino-Black
neighborhoods remained the same or changed because of data limitations.
Second, how do we interpret the finding that at least one form of integration, that
between Blacks and Latinos, is incredibly durable? Are long-term Latino-Black
neighborhoods the “success story” simply in that they are so likely to remain integrated
compared to White-Black and Latino-White neighborhoods? We must learn more about
the social and economic character of these neighborhoods before any such assertions can
be made.
Finally, and most importantly, the analyses do not indicate how neighborhoods
with Blacks, Latinos, and Whites, as well as the group members themselves in these
neighborhoods, actually fare, when compared to transitioning and homogenous contexts.
To address these issues, a different analytical strategy must be employed, in which the
dependent variable must shift from neighborhood change to some type of measure of
advantage or disadvantage at a particular point in time (with independent controls for
earlier points in time). Chapter 5 adopts this approach, and explores these questions, by
comparing the 2000 socioeconomic characterization of racially stable neighborhoods and
100
their group members (between 1980 and 2000) with racially unstable neighborhoods and
their group members.
101
Table 4.1 Distribution of U.S. Metropolitan Racial/Ethnic Neighborhoods 1980-2000*
1980
1990
2000
N
29953
2514
570
77
33114
%
74.8
6.3
1.4
0.2
82.7
N
27344
2721
1043
94
31202
%
68.3
6.8
2.6
0.2
77.9
N
23439
3092
1649
183
28363
%
58.5
7.7
4.1
0.5
70.8
White & Latino
White & Black
Latino & Black
White & Other
Latino & Other
Black & Other
Integrated two-group
subtotal
2765
3014
476
267
26
8
6.9
7.5
1.2
0.7
0.1
<.01
3303
3372
740
580
152
31
8.2
8.4
1.8
1.4
0.4
0.1
4367
3764
1048
1023
310
43
10.9
9.4
2.6
2.6
0.8
0.1
6556
16.4
8178
20.3
10555
26.4
White, Black, & Latino
White, Black, & Other
Black, Latino, & Other
White, Latino, & Other
Integrated three-group
subtotal
220
32
6
117
0.5
0.1
<.01
0.3
315
44
25
271
0.8
0.1
0.1
0.7
579
79
65
391
1.4
0.2
0.2
1.0
375
0.9
655
1.7
1114
2.8
2
<.01
12
<.01
15
<.01
40047
100
40047
100
40047
100
White
Black
Latino
Other
Homogenous subtotal
White, Black, Latino &
Other
Total
*White, Black, and Other refer to non-Latino White, non-Latino Black, and non-Latino
Other
102
Table 4.2 Total Percentage of Individual Whites, Blacks, and Latinos Represented in Each
Neighborhood Type -1980 and 2000
1980
2000
Total
% All
74.06
6.68
1.53
0.19
%
Whites
88.47
0.48
0.21
0.03
%
Blacks
15.62
48.80
0.43
0.01
%
Latinos
30.09
2.65
16.44
0.14
Total %
All
59.49
5.71
4.75
0.46
%
Whites
79.36
0.51
0.67
0.08
%
Blacks
17.36
36.78
1.50
0.11
%
Latinos
19.01
1.53
26.13
0.24
6.76
7.73
1.26
0.70
0.07
0.02
4.52
5.31
0.11
0.42
0.01
<.01
2.11
25.91
4.85
0.25
0.03
0.07
35.00
3.62
7.00
0.74
0.44
0.02
11.81
8.61
2.61
2.58
0.88
0.09
8.65
6.73
0.28
2.06
0.15
0.02
5.17
24.76
8.23
0.84
0.36
0.25
31.58
3.27
8.04
1.61
2.63
0.08
0.60
0.25
1.54
2.40
1.54
0.79
3.31
3.20
0.07
0.03
0.19
0.09
0.19
0.11
0.41
0.13
0.02
<.01
0.04
0.07
0.19
0.03
0.40
0.38
0.32
0.15
0.13
1.32
1.05
0.55
0.43
2.13
At least 20% All
0.01
<.01
0.02
0.02
0.04
0.02
0.08
0.06
Total
100
100
100
100
100
100
100
100
White
Black
Latino
Other
White & Latino
White & Black
Latino & Black
White & Other
Latino & Other
Black & Other
White, Black, &
Latino
White, Black, &
Other
Black, Latino, &
Other
White, Latino, &
Other
103
Table 4.4 Median Metropolitan Neighborhood Population Size and Change in Racially
Stable Neighborhoods Between 1980 and 2000 (N=28851)
1980
population
(1)
ΔTotal
(2)
ΔWhite
(3)
ΔBlack
(4)
ΔLatino
(5)
3342
14%
(479)
6%
(203)
286%
(47)
205%
(73)
3503
-22%
(-743)
-62%
(-46)
-21%
(-667)
-12%
(-1)
Latino
3688
15%
(530)
-48%
(-138)
-16%
(-1)
22%
(648)
White-Latino
3322
25%
(853)
-19%
(-309)
123%
(50)
107%
(1088)
White-Black
3310
-5%
(-155)
-25%
(-391)
13%
(153)
107%
(39)
Latino-Black
3348
9%
(231)
-53%
(-71)
-16%
(-231)
37%
(512)
Racially Stable
Neighborhoods
White
Black
104 …
ⁿ N=28,851
τ
The top values reported in the cells in columns 2-5 represents the Median % population change for the specified group between 1980 and 2000.
The bottom values reported in the cells is the median numeric change in the population size for the specified group between 1980 and 2000.
Table 4.4 Median Metropolitan Neighborhood Population Size and Change in Racially
Stable Neighborhoods Between 1980 and 2000 (N=28851)
1980
population
(1)
ΔTotal
(2)
ΔWhite
(3)
ΔBlack
(4)
ΔLatino
(5)
3342
14%
(479)
6%
(203)
286%
(47)
205%
(73)
3503
-22%
(-743)
-62%
(-46)
-21%
(-667)
-12%
(-1)
Latino
3688
15%
(530)
-48%
(-138)
-16%
(-1)
22%
(648)
White-Latino
3322
25%
(853)
-19%
(-309)
123%
(50)
107%
(1088)
White-Black
3310
-5%
(-155)
-25%
(-391)
13%
(153)
107%
(39)
Latino-Black
3348
9%
(231)
-53%
(-71)
-16%
(-231)
37%
(512)
Racially Stable
Neighborhoods
White
Black
105 …
ⁿ N=28,851
τ
The top values reported in the cells in columns 2-5 represents the Median % population change for the specified group between 1980 and 2000.
The bottom values reported in the cells is the median numeric change in the population size for the specified group between 1980 and 2000.
Table 4.5 The 1980 Socioeconomic Classification of Racially Durable Neighborhood
between 1980 and 2000
1980 Socioeconomic Classification
Racially Stable
Neighborhoods
Disadvantaged
(1)
Middle
(2)
Advantaged
(3)
White
1.3%
85.5%
13.2%
Black
81.5%
18.4%
.1%
Latino
63.7%
36.3%
.0%
White-Latino
16.1%
81.1%
2.7%
White-Black
29.0%
69.8%
1.1%
Latino-Black
91.9%
8.1%
.0%
106
Table 4.6 Multinomial Hierarchical Linear Model Predicting 1980 to 2000 U.S. Metropolitan
Black-White Integrated Neighborhood Change (Remained integrated is the reference category) ⁿτ
Became Black
Became White
Coeff.
Std. Err.
Coeff.
Std. Err.
0.584
-0.129
0.126**
0.061*
-0.697
0.018
0.163**
0.020
1.018
0.018
0.280**
0.022
-1.136
-0.036
0.212**
0.024
-0.004
0.033
0.035
0.002
0.004**
0.007**
0.006
0.001
0.006
0.002*
0.004
0.008
1.744
2.630
1.390
0.473**
0.471**
0.476**
-1.425
-1.330
-1.554
0.513*
0.479**
0.517**
-0.011
0.160
0.005*
0.030**
0.000
0.046
0.005
0.038
0.003
0.001*
0.002
0.001
0.421
0.015
0.045
0.110**
0.009
0.010**
-0.143
0.017
-0.012
0.142
0.015
0.010
-4.382
0.524
-.325
0.476
Neighborhood Characteristics
Socioeconomic
Concentrated disadvantage
Black-White poverty inequality
Demographic
Central city
Proportion foreign born
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
Metropolitan Characteristics
Region – Northeast
Region – South
Region – Midwest
(West - ommitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 19802000
Black-White poverty inequality
Black-White growth difference
Black-White dissimilarity index
Intercept
Source: Neighborhood Change Data Base
*p<.05 **p<.01 (two-tailed)
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
τ
Neighborhood level N=2616; Metropolitan level N=192
107
Table 4.7 Multinomial Hierarchical Linear Model Predicting 1980 to 2000 U.S. Metropolitan
Latino-White Integrated Neighborhood Change (Remained integrated is the reference category)ⁿτ
Became Latino
Became White
Coeff.
Std. Err.
Coeff.
Std. Err.
Socioeconomic
Concentrated Disadvantage
Latino-White poverty
2.057
-0.379
0.313**
0.103**
-1.344
0.129
0.252**
0.078
Demographic
Central city
Proportion Foreign Born
0.382
0.065
0.274
0.015**
-0.425
-0.057
0.408
0.018**
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
-0.001
0.038
0.016
0.001
0.007**
0.007*
0.004
-0.050
-0.012
0.001**
0.008**
0.017
0.931
1.190
1.054
0.845
0.328**
0.768
0.680
-.904
2.625
0.664
0.525
0.778**
Neighborhood Characteristics
Metropolitan Characteristics
Region – Northeast
Region – South
Region – Midwest
(West - ommitted category)
1980-2000 Population Growth
Proportion foreign born
Change in Proportion Foreign Born 19802000
Latino-White Poverty Difference
Latino-White growth difference
Latino-White dissimilarity index
0.011
0.040
0.006
0.039
0.002
0.023
0.007
0.033
0.010
-0.029
0.082
0.077
0.003**
0.258
0.058
0.023**
0.003
0.509
0.111
-0.047
0.003
0.339
0.110
0.029
Intercept
-2.404
0.357**
-3.479
0.480**
Source: Neighborhood Change Data Base
*p<.05 **p<.01 (two-tailed)
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
τ
Neighborhood level N=2338; Metropolitan level N=98
108
Table 4.8 Multinomial Hierarchical Linear Model Predicting 1980 to 2000 U.S. Metropolitan
White Homogenous neighborhood Change (Remained White is the reference category) ⁿτ
Became White-Black
Became White-Latino
Coeff.
Std. Err.
Coeff.
Std. Err.
Socioeconomic
Concentrated disadvantage
Black-White poverty inequality
Latino-White poverty inequality
1.252
.016
.020
.143**
.004**
.010*
3.179
.011
.024
.213**
.008
.010*
Demographic
Central city
Proportion foreign born
1.138
.029
.152**
.023
.501
.047
.129**
.028
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
-.002
-.009
.022
.001**
.003**
.004**
-.002
-.006
.004
.000**
.004
.004
1.181
3.175
1.704
.462*
.385**
.435**
-2.651
-.798
-1.934
.618**
.487
.619**
-.015
-1.470
.001
.004**
4.079
.001
.500
.109
.045
.008
-.015
-.008
.102**
.096
.014**
.002**
.008
.010
.028
20.947
.007
-.222
.357
.029
.005
.011
.073
.007**
4.344**
.002**
.188
.184
.015
.002*
.015
.021**
-6.526
.436**
-4.286
.488**
Neighborhood Characteristics
Metropolitan Characteristics
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White poverty inequality
Latino-White poverty inequality
Black-White growth difference
Latino-White growth difference
Black-White dissimilarity index
Latino-White dissimilarity index
Intercept
*p<.05 **p<.01 (two-tailed)
Source: Neighborhood Change Data Base
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
τ
Neighborhood level N=28029; Metropolitan level N=323
109
Table 4.9 Multinomial Hierarchical Linear Model Predicting 1980 to 2000 U.S. Metropolitan
Black Homogenous Neighborhood Change (Remained Black is the reference category) ⁿτ
Became White-Black
Became Latino-Black
Coeff.
Std. Err.
Coeff.
Std. Err.
Socioeconomic
Concentrated disadvantage
-.733
.190**
.240
.199
Demographic
Central city
Proportion foreign born
-.810
.032
.375*
.016*
-.332
.004
.328
.028
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
.026
-.049
-.018
.003**
.008**
.013
.007
-.031
-.016
.004
.013
.016
-2.583
-3.466
-2.573
.897**
.947**
1.013*
-2.276
-4.077
-4.091
1.091*
.959**
1.258**
.001
-18.155
.012
6.499**
.021
3.246
.012
4.648
Neighborhood Characteristics
Metropolitan Characteristics
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White poverty inequality
Latino-Black poverty inequality
Black-White growth difference
Latino-Black growth difference
Black-White dissimilarity index
Latino-Black dissimilarity index
Intercept
-.003
-.405
.699
-.011
-.020
.009
-.024
.003
.281
.415
.011
.090
.038
.025
.002
.004
-.811
-1.407
.009
.464
.048
-.045
.469
.751
.015
.391
.045
.042
.658
.915
.116
.839
*p<.05 **p<.01 (two-tailed)
Source: Neighborhood Change Data Base
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
τ
Neighborhood level N=2484; Metropolitan level N=138
110
ADDITIONAL TABLES
Table 4.10 Full Transition Matrix: U.S. Neighborhood Racial Composition 1980-2000
2000 Neighborhood Type
111…
1980
Neighborhood
Type
1
w
2
b
3
l
4
o
5
w-l
6
w-b
7
l-b
8
w-o
9
l-o
10
b-o
11
w-b-l
12
w-b-o
13
b-l-o
14
w-l-o
15
w-l-b
Total
white
76.8
0.6
0.3
0.0
9.9
7.0
0.3
2.8
0.1
0.0
1.2
0.2
0.1
0.8
0.0
100.0
black
0.1
84.8
0.1
0.0
0.0
3.3
10.7
0.0
0.0
0.4
0.1
0.0
0.4
0.0
0.0
100.0
latino
0.0
0.0
88.6
0.0
4.9
0.2
3.2
0.0
2.6
0.0
0.2
0.0
0.0
0.4
0.0
100.0
other
0.0
0.0
0.0
93.5
0.0
0.0
0.0
6.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
100.0
white and latino
4.7
0.3
32.5
0.3
47.3
0.1
2.8
0.8
5.1
0.1
1.6
0.0
0.3
3.8
0.0
100.0
white and black
10.1
24.3
0.5
0.0
1.4
52.4
4.9
0.2
0.1
0.3
4.7
0.7
0.3
0.1
0.0
100.0
latino and black
0.4
3.4
17.9
0.0
0.6
0.4
72.1
0.0
1.5
0.4
1.9
0.0
1.3
0.2
0.0
100.0
white and other
1.9
0.0
0.0
29.6
1.5
1.1
0.0
53.9
3.0
0.7
0.0
2.2
0.4
5.2
0.4
100.0
latino and other
0.0
0.0
23.1
7.7
0.0
0.0
0.0
0.0
65.4
0.0
0.0
0.0
0.0
3.8
0.0
100.0
black and other
0.0
25.0
0.0
0.0
0.0
0.0
25.0
0.0
12.5
37.5
0.0
0.0
0.0
0.0
0.0
100.0
0.9
3.6
18.6
0.0
9.1
3.2
44.5
0.9
3.6
0.5
10.5
0.0
4.1
0.5
0.0
100.0
6.3
0.0
0.0
18.8
0.0
6.3
0.0
18.8
9.4
18.8
0.0
9.4
9.4
0.0
3.1
100.0
0.0
0.0
50.0
0.0
0.0
0.0
16.7
0.0
33.3
0.0
0.0
0.0
0.0
0.0
0.0
100.0
0.0
0.0
7.7
4.3
6.0
0.9
0.0
2.6
65.0
0.0
0.0
0.9
0.9
12.0
0.0
100.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50.0
0.0
0.0
0.0
50.0
0.0
0.0
100.0
white, black, and
latino
white, black, and
other
black, latino, and
other
white, latino, and
other
white, latino,
black, other
Chapter 5
Advantage and Integration for Whites, Blacks, and Latinos
5.1 Introduction
A primary objective of my dissertation is to examine the contention that residence
in long term racially/ethnically integrated neighborhoods is more beneficial for Blacks
and Latinos than in transitioning or homogenous minority contexts. Results from
Chapter 4 appear to support a critical race skepticism toward those who frame
neighborhood integration as a panacea for Blacks and Latinos and the larger inequality
problem characterizing neighborhoods in the United States. Specifically, regarding the
question of prevalence, Chapter 4 showed that long-term racial/ethnic integration
between Whites and Blacks or Latinos is simply not that common. Chapter 4 also
examined how neighborhood advantage and disadvantage predicted the likelihood that
integrated neighborhoods remained integrated or changed over time, and the likelihood
that homogenous neighborhoods became integrated. The results showed that while
integrated neighborhoods appear to have higher mean levels of advantage relative to
homogenous minority neighborhoods (so long as Whites are also present in the
neighborhood), increased advantage seems to undermine integration of Whites and
minorities in the long term. The less disadvantaged an integrated context was, the more
112
likely it was to transition to a White neighborhood than remain integrated, or remain a
White neighborhood to begin with. The more disadvantaged an integrated neighborhood
was, the more likely it was to remain integrated or become predominantly Black or
Latino. These findings call into question the claims by some integration proponents that
long-term racial/ethnic integration will ameliorate the problems for Blacks and Latinos
that are attributed to consequences associated with racial residential segregation. If long
term neighborhood integration decreases the consequences associated with segregation
for Blacks and Latinos, it seems the relationship between the socioeconomic character of
neighborhoods and likelihood of remaining integrated found in Chapter 4 should be in the
opposite direction. Specifically, for neighborhoods and residents to benefit from longterm integration, increased advantage in integrated neighborhoods should ideally bolster
long-term stable integration for neighborhoods with Blacks, Latinos, Whites, and Others.
The problem is that several scholars and public officials have argued that our
analytical focus should entail understanding the forces (demographic, social, etc.) that
contribute to instability and stability in integrated neighborhoods without an adequate
exploration of the hypothesized benefits of integration for those of color. They argue that
doing so will help us to better understand how to shape practices and policies that might
foster long term racial and ethnic stability in integrated neighborhoods. However,
research has not yet demonstrated whether maintaining integrated neighborhoods is an
appropriate goal. This is because we have not sufficiently explored whether
neighborhoods that remain racially/ethnically constant over a long period of time are
significantly more socioeconomically advantaged than those that transition or are
113
homogenous and constant, particularly for neighborhoods with historically subordinated
group members.
I contend that analytical models are necessary that predict levels of advantage for
cases of long-term integration relative to cases of instability or long-term racial/ethnic
homogeneity, which will be the focus of this chapter. I believe this is the most important
component of my dissertation, in that it directly asks if long-term integrated
neighborhoods are in fact significantly different than transitioning and durable
homogenous neighborhoods. As such, the central purpose of this chapter is to
empirically assess whether or not racially/ethnically stable integrated neighborhoods are
more advantageous contexts for areas with historically subordinated group members,
compared to unstable and homogenous alternatives.
To address this question, the analyses in this chapter are comprised of both
descriptive and analytical elements. First, I examine patterns of mean levels of
concentrated disadvantage in 2000 for racially stable neighborhoods between 1980 and
2000. Next, I assess the degree of economic flux across the racially stable neighborhoods
over the two decades. Are the same integrated neighborhoods that are advantaged in
1980 also advantaged in 2000? And for those that experience socioeconomic flux, which
neighborhoods improved and which declined? I then specify multilevel models to
examine whether, net of important metropolitan and neighborhood controls, long term
integrated neighborhoods were significantly less disadvantaged than alternative contexts.
The dependent variable for these models is concentrated disadvantage in 2000.
With a clear sense of the economic characterization and socioeconomic
flux/stability of racially stable neighborhoods between the two periods, in the second
114
analytical portion of the chapter, I seek to narrow the focus of the analysis to levels of
advantage for group members themselves (as opposed to neighborhoods). Though a
focus on group-level concentrated disadvantage would be ideal to maintain consistency
with the first sets of analyses (which focused on neighborhood level concentrated
disadvantage), data limitations make this difficult. 1 Specifically, the data do not contain
all of the same race-specific measures used to construct the neighborhood disadvantage
index. However, the social and economic race-specific measures that are readily
available for a group-level socioeconomic index are a better conceptual fit with the
construct advantage; affluence, college education, and poverty (reverse-coded).
The key question with these analyses, is whether historically subordinated group
members display meaningfully higher levels of advantage in neighborhoods that
remained racially/ethnically integrated in the preceding two decades compared with
members in neighborhoods that transitioned or remained homogenous. First, I compare
mean levels of advantage for Whites, Blacks, and Latinos residing in racially stable and
transitioning integrated contexts. Finally, I specify separate multilevel models for
neighborhoods with Whites, Blacks, and Latinos between 1980 and 2000. The key
dependent variables for the three models are 2000 race-specific advantage indices. In
these models, I seek to ascertain how, net of metropolitan and neighborhood controls,
mean levels of White, Black, and Latino advantage in long-term integrated
neighborhoods compare with those in transitioning or long-term homogenous areas.
1
See Chapter 3 for greater detail about the data limitations, construction, and validation of the
neighborhood-level disadvantage and group-level advantage indices. Chapter 3 also provides information
pertaining to efforts to validate the indices, including results from exploratory factor analysis and alpha
reliability statistics.
115
5.2 Long-Term Racial/Ethnic Stability and Concentrated Disadvantage
How do racially stable and transitioning neighborhoods compare along mean
levels of neighborhood disadvantage? Figure 5.1 presents a bar chart displaying levels of
concentrated disadvantage in 2000 for transitioning and racially stable homogenous and
integrated contexts between 1980 and 2000. The horizontal axis represents the mean
level of concentrated disadvantage for the complete sample of metropolitan
neighborhoods which is an index value of zero. Values above the horizontal axis
represent higher levels of disadvantage relative to the sample, while values below the
horizontal axis represent lower levels of disadvantage relative to the sample.
The second bar in the figure shows the disadvantage score in 2000 for stable
predominantly White neighborhoods across the two decades. Stable predominantly
White areas were the least disadvantaged in 2000 of all the racially stable neighborhoods
and the transitioning neighborhooods, with an index score of -.433. The remaining bars
in the figure, to the right of the column for Whites, represent the other five neighborhood
types. The column to the left of the bar for White neighborhoods represents unstable
neighborhoods. Each of these index scores are above the index mean of zero. This
shows that aside from the White areas, all other neighborhood types that were racially
stable or unstable had higher average levels of concentrated disadvantage compared to
metropolitan neighborhoods as a whole.
Another important pattern to note in Figure 5.1 is that stable integrated
neighborhoods with numerous Whites had lower levels of disadvantage than those
without many Whites (both homogenous and integrated). Specifically, the White-Black
neighborhoods had an average index score of .455 and the White-Latino neighborhoods
116
had an average score of .285; Latino-Black neighborhoods, in contrast, had a
significantly higher mean score of 2.111.
Finally, in line with theoretical expectations about the hierarchical privileging of
Whites over Latinos over Blacks, neighborhoods with many Latinos (both integrated and
homogenous) had lower levels of disadvantage than those with Blacks (both integrated
and homogenous). Latino-Black neighborhoods are the one exception to this pattern.
These neighborhoods had, by a wide margin, the highest levels of concentrated
disadvantage (2.111) of all of the groups in 2000, even stable predominantly Black areas
(with an index score of 1.673). This is somewhat surprising, as this contrasts theoretical
expectations that long-term predominantly Black neighborhoods would be the most
disadvantaged of all contexts.
What do the findings revealed in Figure 5.1 mean for the larger assessment of
potential socioeconomic benefits of long-term racial ethnic stability in neighborhoods?
One may deduce from Figure 5.1 that stable White-Latino and White-Black
neighborhoods are clearly more likely to be advantageous contexts for Blacks and
Latinos given their remarkably lower mean levels of concentrated disadvantage in 2000
compared to consistently Black and Latino neighborhoods. However, Figure 5.1 is a
snapshot of levels of concentrated disadvantage in 2000; one point in time for the sample
of neighborhoods with longevity in their racial/ethnic makeup. What is the relationship
between racial/ethnic stability and socioeconomic stability, growth, or decline?
Table 5.1 provides detailed information about the direction of economic stability
and change for the racially durable neighborhoods in the sample. Each row in the table
represents one of the six most common single and two-group neighborhoods that
117
remained racially stable between 1980 and 2000. The first three columns report the
percentage of each of the neighborhood types that remained or became economically
advantaged across the two decades. The fourth and fifth columns show the percentage of
each of the racially stable neighborhoods that remained or became economically
disadvantaged. To assess patterns of change in the economic characterization of these
neighborhoods, I rely on the same advantage scale used in Chapter Four to classify
neighborhoods as disadvantaged, moderately advantaged, or advantaged.2 However, in
this table, advantaged and moderately advantaged are combined into a single category.
The results indicate that the majority of all of the racially stable neighborhoods,
both homogenous and integrated, were also economically stable, though there are
important discrepancies in the type of economic stability. Overall, consistent with results
in Table 4.5, patterns in Table 5.1 show a clear racial hierarchy of neighborhoods that are
mainly or partially White being significantly more advantaged than those with few
Whites. White neighborhoods were overwhelmingly stably advantaged (nearly 87%).
When factoring in the White neighborhoods that declined but remained advantaged
(4.4%), and those that improved and became advantaged (7.7%), nearly 99% of White
neighborhoods across the two decades were advantaged.
For neighborhoods partially comprised of Whites, nearly three-quarters of WhiteLatino (73.3%) and over half of White-Black (60.3%) areas were consistently
advantaged. Though a greater overall proportion of White-Latino neighborhoods were
advantaged (whether became, declined, or improved) than White-Black neighborhoods
2
See Chapter 3 for more detail about how the disadvantage index and scale was constructed.
118
(85.4% compared to 73.7%), a greater proportion of White-Black neighborhoods became
advantaged (12.7%) than White-Latino neighborhoods (9.8%).
In stark contrast to neighborhoods with numerous White residents, the majority of
neighborhoods in which Latinos, Blacks, or both predominate were consistently
disadvantaged. Integrated neighborhoods with Latinos and Blacks were the most stably
disadvantaged (nearly 90%), followed by those that are predominantly Black (76.3%) or
Latino (55.2%). Though a greater overall proportion of Black than Latino neighborhoods
remained or became disadvantaged (82.8% and 74.5%, respectively), significantly more
Latino than Black neighborhoods became disadvantaged. As a whole, racially stable
Latino neighborhoods were the most economically unstable of all the neighborhood
types.
Collectively, the results presented in Figure 5.1 and Table 5.1 suggest that longterm integrated or homogenous neighborhoods, so long as a significant proportion of
Whites are present, are more advantaged than homogenous or integrated contexts without
Whites (such as predominantly Black, Latino, or Latino-Black neighborhoods).
However, do these patterns hold when important metropolitan and neighborhood
demographic, housing, and social factors are taken into account? For Blacks and Latinos
specifically, are long-term racially integrated neighborhoods significantly different in
neighborhood advantage/disadvantage relative to homogenous and transitioning
alternatives?
Tables 5.2 and 5.3 present results from a series of multivariate models predicting
2000 neighborhood concentrated disadvantage for the most common neighborhood types.
The sample includes all neighborhoods that were White, Black, Latino, White-Black,
119
White-Latino, or Latino-Black in 1980. The key independent variables are the seven
variables presented in the rows in Table 5.2 – dummy variables for each the racial/ethnic
neighborhood trajectories of the neighborhoods in the sample. The various coefficients
reported in each of the columns in Table 5.2 are from seven separate models specified;
each differs only in terms of the racial/ethnic neighborhood trajectory dummy omitted as
the reference category. It was essential to run the separate models in order to test the
significance of the difference in the effects of racial/ethnic stability on concentrated
disadvantage between each possible comparison of racial/ethnic trajectories for the
neighborhoods. Each column in the table is labeled with a number and identifies the
omitted category for that particular model; transitioning neighborhoods, remained White,
remained Black, remained Latino, remained White-Black, remained White-Latino, and
remained Latino-Black. Table 5.3 presents the coefficients and standard errors for each
of the neighborhood and metropolitan characteristics that served as controls in the seven
models. It is important to note that these effects remain the same, regardless of the
racial/ethnic category chosen to serve as the reference group.3
Statistical significance for any of the neighborhood dummies in Table 5.2, net of
the neighborhood and metropolitan controls presented in Table 5.3, would indicate a
significant relationship (positive or negative depending on the sign) between a
neighborhood remaining racially/ethnically stable between 1980 and 2000 and its 2000
level of concentrated disadvantage. To support the assertions made in the segregation
literature about the advantages of stable neighborhood integration for minorities, the
coefficients for integrated neighborhoods should be significant and smaller than the
3
The intercepts for each of the seven models are different.
120
effects for neighborhoods that remained Black or remained Latino. This would indicate
that stable integrated neighborhoods have lower levels of concentrated disadvantage than
those that transitioned.
For integrated neighborhoods which include a large number of Whites, the results
in Table 5.2 suggest significantly lower mean levels of disadvantage relative to
predominantly minority contexts. Specifically, the coefficients comparing White-Black
with Black neighborhoods (column 3) and White-Latino with Latino neighborhoods
(column 4) are negative and significant. This means that both integrated neighborhoods
had significantly lower levels of disadvantage compared to their homogenous minority
counterparts in 2000. However, both White-Black and White-Latino neighborhoods were
not significantly different in mean levels of disadvantage from neighborhoods that
transitioned over the two decades, as seen in column 1. This suggests that
racially/ethnically stable White-Black and White-Latino neighborhoods had no higher or
lower levels of disadvantage than all types of unstable neighborhoods.
Several other patterns are important to highlight in Table 5.2. First, the
coefficients in column 2 are all significant and positive, indicating that all neighborhoods
have significantly higher levels of disadvantage in 2000 than long-term White areas.
Additionally, the size of the effects mirror the racialized hierarchical patterns revealed in
the descriptive Figures and Tables preceding this analysis. Specifically, neighborhoods
with only small numbers of Whites, such as Latino, Black, and Latino-Black areas, have
higher levels of disadvantage than the integrated areas with a large representation of
Whites. Finally, also in line with the descriptive analyses, Latino-Black neighborhoods
121
have significantly higher levels of disadvantage compared to all other neighborhoods, net
of the controls.
The coefficients for neighborhood controls in Table 5.3 are predominantly
significant and in the expected direction. Neighborhoods have higher levels of
concentrated disadvantage if they are in the central city, have fewer immigrants, are
smaller, have more overall population growth, lower median income, less growth in the
housing market, fewer home owners, and more recent movers. The coefficients for
metropolitan controls indicated that neighborhoods in metropolitan areas in the West
(compared to the South and Midwest), characterized by less population growth, more
immigrants, and more Black-White and Latino-Black segregation have higher levels of
concentrated disadvantage.
What do these results mean? Figure 5.2 displays a bar chart which visually
displays the results presented in Table 5.2 net of the controls; the hierarchical, racialized
relationship between racial/ethnic neighborhood stability/change and concentrated
disadvantage. The chart provides predicted levels of concentrated disadvantage in 2000.
Predicted values stem from a hypothetical scenario that assumes all the neighborhoods
have characteristics identical with the average characteristics for the sample as a whole.
By a wide margin, stable White neighborhoods have the lowest mean predicted level of
disadvantage, followed by White-Latino, White-Black, and unstable neighborhoods. In
contrast, Latino-Black, Black, and Latino neighborhoods (in that order), have the highest
predicted levels of disadvantage. The results in Table 5.2 show that the unstable, longterm White-Black, and long-term White-Latino neighborhoods are not significantly
different from each other, as well as the stable Black and Latino areas. However, this
122
does not affect interpretation of the larger pattern of lower levels of disadvantage
associated with the presence of a large number of Whites whether in a homogenous or
integrated context.
5.3 Descriptive Patterns of Black, White, and Latino Advantage in Stable and
Transitioning Neighborhoods
The findings above are mixed regarding the validity of the claim that long-term
integrated neighborhoods reap social and economic benefits for minorities relative to
other homogenous and unstable alternatives. It is clear that stable White-Black and
White-Latino neighborhoods are significantly less disadvantaged compared to long-term
Black and Latino communities. However, Latino-Black neighborhoods are significantly
more disadvantaged than long-term Black and Latino areas.
However, conclusions from the analyses above must be cautiously interpreted, as
they do not actually differentiate how group-members themselves fare in the long-term
integrated versus homogenous communities. Though the long-term White-Black and
White-Latino areas are less disadvantaged than the stable Black and Latino areas, are
Blacks and Latinos residing in these integrated neighborhoods meaningfully more
advantaged than those situated in the stable, predominantly minority communities? A
more precise method to answer this question is to examine race-specific advantage levels
within stable integrated neighborhoods compared to homogenous and transitioning
alternatives. As discussed in the introduction of this chapter, data limitations prevent the
use of a race-specific disadvantage index congruent with the one used in the
neighborhood-level analysis. As such, the outcome for the remainder of the analysis
shifts to a race-specific index of advantage for Whites, Blacks, and Latinos.
123
How do Whites, Blacks, and Latinos fare in mean levels of advantage in 2000 in
the communities where they were most likely to reside between 1980 and 2000? Figures
5.3 through 5.5 present charts displaying patterns in levels of White (Figure 5.3), Black
(Figure 5.4), and Latino (Figure 5.5) advantage in the respective kinds of neighborhoods
where the majority of group members resided in the two decades (as revealed in Chapter
4). It is important to note that the horizontal axis in all three charts represents a
standardized mean level of advantage for Whites, Blacks, and Latinos, allowing for
comparison of absolute levels of advantage across the different groups.4 It is also
important to note that the category “Transitioned” in the figures refers to the
neighborhoods in 1980 (represented in the particular figure), that transitioned to some
other type of community over the two decades. For example, for Figure 5.3, Transitioned
neighborhoods represented in the first bar in the chart are neighborhoods that were White,
White-Latino, or White-Black in 1980 but differentially classified in 2000 as a result of
significant change in the racial or ethnic makeup of the neighborhood over the two
decades.5
Several important patterns emerge when examining patterns first within and then
across the groups. When examining patterns for White advantage in 2000 in Figure 5.3,
it is striking that average levels of White advantage are well above the mean, regardless
of the particular type of context. Second, mean White advantage is substantially higher
for group members that resided in long-term White neighborhoods, with an advantage
4
See Chapter 3 for a more detailed explanation of the method employed to produce these calculations.
Transitioned neighborhoods included in Figure 5.3 had to be White, White-Latino, or White-Black in
1980 (the three neighborhood types represented in the Figure), and to have transitioned to some other
context in 2000 (one of fourteen possible trajectories as defined in the typology constructed in Chapter 3).
The same logic applies to the transitioned classification in Figures5.4, 5.5, and the multivariate analysis.
5
124
index score of .533. Interestingly, average levels for residents in Transitioning, WhiteLatino, and White-Black neighborhoods were very similar (.27, .31, and .27
respectively).6
Patterns for Blacks contrast sharply with those for Whites. Figure 5.4 shows that,
aside from those residing in predominantly White areas in 2000, mean levels of Black
advantage in all other contexts were below the mean. The lowest levels of Black
advantage in 2000 were in stable Latino-Black and Black areas, with index scores of 1.074 and -.884, respectively. Average levels of Black advantage were surprisingly only
slightly lower in stable White-Black areas (index score of -.682) compared to the average
in stable predominantly Black areas (index score of -.884). This is somewhat surprising
given the large disparity in neighborhood levels of concentrated disadvantage when
comparing racially stable White-Black and Black neighborhoods in 2000; long-term
Black neighborhoods in 2000 had significantly higher levels of concentrated
disadvantage than White-Black neighborhoods (see Figure 5.1). Finally, neighborhoods
in flux between 1980 and 200 with a large representation of Blacks, represented in the
first bar in Figure 5.4, have a mean 2000 advantage index score of -.37, which is much
lower than the scores for the stable neighborhoods (aside from the stable White context).7
6
Though not presented here, I also examined mean levels of White advantage across the varying
transitioning contexts between 1980 and 2000. Not surprisingly, neighborhoods that became more White
had higher average levels of White advantage than those that transitioned from White to integrated
contexts. In fact, areas that transitioned from White-Latino to White and Black to White-Black had higher
average levels of White advantage than the average for those in long-term predominantly White
neighborhoods. Conversely, areas with the lowest levels of White-advantage (though all still above the
mean for all groups) were those that transitioned from integrated to predominantly minority (such as WhiteLatino areas that became mostly Latino, and White-Black areas that became mostly Black).
7
Though not presented here, I also examined mean levels of Black advantage across the varying
transitioning contexts between 1980 and 2000. Neighborhoods with a large share of Blacks in 1980 that
transitioned to or from a Latino-Black area had significantly lower levels of Black advantage than other
transitioning contexts. However, there were not that many Latino-Black neighborhoods in both 1980 and
2000, which explains why the average for transitioning neighborhoods as a whole presented in Figure 5.4
125
Similar to the patterns for Blacks, those for Latinos, presented in Figure 5.5, show
that only Latinos in stable predominantly White areas in 2000 had a higher average index
score of Latino advantage compared to the mean. Additionally, Latinos in long-term
Latino-Black neighborhoods had the lowest levels of advantage compared to group
members in other stable and transitioning contexts, with a score of -1.215. Finally,
Latino advantage in 2000 appeared to be much higher in long-term integrated WhiteLatino neighborhoods (-.582) and Transitioning neighborhoods (-.45) compared to stable
Latino neighborhoods (-.99).8
When comparing the relationship between racial/ethnic neighborhood stability
and race-specific advantage across the groups, as presented in Figures 5.3-5.5, several
patterns are important to note. First, Whites are the only group to have average White
advantage index scores above the average for all groups regardless of the specific type of
context (even those areas with large White representation in 1980 that ultimately became
Latino or Black in 2000). Second, Latinos appear to be more negatively impacted in
terms of average advantage scores, compared to Blacks, when they do not reside in
neighborhoods with a large proportion of Whites. Specifically, Latinos had a lower mean
level of advantage in stable Latino communities (an index score of -.998) in 2000
compared to the average for Blacks residing in stable Black communities (index score of
would not be heavily impacted by the extremely low scores for areas that transitioned to or from LatinoBlack. Areas that transferred to or from White or White-Black neighborhoods had much higher average
levels of Black advantage in 2000 compared to the other areas that transitioned. Regardless of the type of
transition though, all average scores for Black advantage were significantly below the mean for all groups.
8
Though not presented here, I also examined mean levels of Latino advantage across the varying
transitioning contexts between 1980 and 2000. Compared to other transitioning contexts, the highest scores
for Latino advantage were in neighborhoods that transitioned from White-Latino to White, by a wide
margin. Any transition involving Latino-Black contexts, whether to or from, had significantly lower index
scores, approaching the level for stable Latino-Black areas. Finally, those areas that transitioned from
White-Latino to Latino or Latino to White-Latino had much lower average levels of Latino advantage
compared to those areas that transitioned from White to White-Latino or White-Latino to White.
126
-.884). Similarly, Latinos in stable Latino-Black areas had a lower mean advantage score
compared to Blacks in stable Latino-Black areas (-1.22 compared to -1.074). However,
while Latinos may experience greater consequences in terms of group-level advantage
when not residing with Whites compared to Blacks, they also appear to benefit slightly
more than Black in average advantage scores when they reside in long-term integrated
neighborhoods with Whites. Specifically, in Figure 5.5 we see that the Latino advantage
index score in 2000 in long term White-Latino neighborhoods was -.58; slightly higher
than the average index score in Figure 5.4 for Blacks residing in long term White-Black
neighborhoods, -.68.
The final important pattern to note when examining collectively the results in
Figures 5.3-5.5 is that when comparing mean levels of advantage for the groups
represented in integrated contexts with Whites, Whites always have significantly higher
index scores compared to Black or Latino average scores in the same stable contexts (see
Figure 5.9 in the Additional Tables section at the conclusion of the chapter for a chart
which displays the patterns and associated scores). Though not presented here, the same
pattern holds for all types of transitioning integrated contexts involving a large proportion
of Whites, regardless of the type of transition.
5.4 Modeling Black, White, and Latino Advantage in Stable and Transitioning
Neighborhoods
The descriptive patterns presented above provide an initial answer to the larger
question driving the analyses in this section of the chapter; are Blacks and Latinos
residing in integrated neighborhoods meaningfully more advantaged than those situated
in stable, predominantly minority communities? It appears that mean levels of Latino
127
advantage in stable White-Latino neighborhoods are in fact substantially higher in 2000
than levels for those residing in stable Latino neighborhoods. Mean levels of Black
advantage in 2000 in stable White-Black communities are slightly higher than levels for
those residing in stable Black communities. However, do these relationships hold when
important metropolitan and neighborhood demographic, housing, and social factors are
taken into account?
Tables 5.4-5.6 present results from multilevel multivariate models which
separately predict 2000 advantage for Whites (Table 5.4), Blacks (Table 5.5), and Latinos
(Table 5.6). The sample for each model includes the neighborhoods where the groups are
represented in large proportions. The key independent variables are the racial/ethnic
stability dummies in the first set of rows in each table (with only the relevant dummies
included for each of the separate models). As with the neighborhood-level analysis
predicting concentrated disadvantage levels in the first section of this chapter, I run
separate models with each racial/ethnic trajectory serving as the omitted reference
category. This is necessary in order to test the significance of the difference in the effects
with each other in predicting mean levels of advantage for Whites, Blacks, and Latinos.
However, I only include the coefficients in each of the tables in which the stable
homogenous neighborhood for the group in which advantage levels are predicted serves
as the omitted reference category. This makes theoretical sense given the larger purpose
of the analysis; assessing if minorities in long-term integrated neighborhoods have
meaningfully higher levels of advantage compared to those in long-term homogenous
contexts. The coefficients estimated for all of the other models for each group are
presented in the Additional Tables section at the end of the chapter, in Table 5.7 for
128
White advantage, Table 5.8 for Black advantage, and Table 5.9 for Latino advantage.
However, the results of these tests are incorporated into the interpretation and discussion
of results in Tables 5.4-5.6. Interpretation of the key independent variables in each of the
models, the neighborhood trajectory dummies, is similar in logic to that employed for the
multivariate analysis in the first section of the chapter.
Statistical significance for any of the dummy variables, net of the neighborhood
and metropolitan controls, would indicate a significant relationship (positive or negative
depending on the sign) between the particular racial/ethnic neighborhood outcome
between 1980 and 2000, and its associated 2000 mean level of race-specific advantage.
To support the assertions made in the segregation literature about the advantages of long
term neighborhood integration for minorities (as opposed to residence in unstable or
segregated contexts), the coefficients for integrated neighborhoods should be significant
and positive for the Black and Latino models. This would indicate that Blacks and
Latinos in long term integrated neighborhoods have higher levels of advantage in 2000
than group members residing in homogenous Black or Latino neighborhoods.
Table 5.4 presents the findings for the hierarchical linear model predicting White
advantage in 2000 in stable and transitioning neighborhoods with a large representation
of Whites and with long-term White areas serving as the omitted reference category for
the neighborhood trajectory dummy variables. In contrast to the patterns in the
descriptive Figure5.3, White advantage was significantly higher in long-term WhiteBlack areas than in stable predominantly White neighborhoods. Furthermore, White
advantage was significantly lower in both Transitioning and stable White-Latino contexts
compared to stable White contexts. However, White-Latino and Transitioning
129
neighborhoods were not significantly different from each other in mean levels of White
advantage in 2000.
Results for the neighborhood controls show that White advantage was higher in
2000 in neighborhoods located in the central city, with more immigrants, smaller
population change, higher and increasing median income, fewer homeowners, and more
recent movers. For the metropolitan controls, the results indicate that White advantage
was higher in neighborhoods located in metropolitan areas in the South compared to the
West, with a burgeoning population, and less Black-White segregation.
Table 5.5 presents results for the hierarchical linear model predicting Black
advantage in 2000 in stable and transitioning neighborhoods with a large portion of
Blacks and with stable majority Black neighborhoods as the excluded reference category.
The most important finding in the table is the significant and negative coefficients for the
White-Black and Latino-Black dummies. These coefficients indicate that, net of the
controls, Black advantage in 2000 was significantly lower in these integrated contexts
compared to stable Black contexts. The slightly higher mean level of Black advantage in
White-Black neighborhoods compared to Black neighborhoods in the descriptive Figure
5.4 does not hold once important neighborhood and metropolitan factors are accounted
for. Interestingly, there appears to be no significant difference in mean levels of Black
advantage in neighborhoods that transitioned and neighborhoods that were stable and
mostly White, compared to long-term Black areas.
The full set of models run in the Additional Tables section at the end of the chapter, in
Table 5.8, show that stable Black and White neighborhoods were not significantly
130
different from each other, as well as stable Black and Transitioning areas and long-term
White-Black and transitioning neighborhoods.
The neighborhood level controls for the Black advantage model indicate that
Black advantage is higher in neighborhoods located outside of the central city, with more
immigrants, higher and growing median income, more homeowners, and more recent
movers. At the metropolitan level, Black advantage was lower in 2000 in neighborhoods
that were located in the South compared to those in the West.
Finally, Table 5.6 presents results for the hierarchical linear model predicting
Latino advantage in 2000 in stable and transitioning neighborhoods with a large portion
of Latinos and with stable majority Latino neighborhoods as the omitted reference
category. In contrast to Blacks, Latinos residing in stable integrated neighborhoods with
a large share of Whites had significantly higher levels of advantage compared to those in
long-term Latino neighborhoods; the coefficient for Remained White-Latino is positive
and significant. However, similar to the patterns for Blacks, Latino advantage in stable
Latino-Black neighborhoods is significantly lower than for those in long-term
predominantly Latino neighborhoods. Finally, Latino advantage was also higher in both
Transitioning and stable predominantly White areas compared to long-term Latino
communities. All neighborhoods were significantly different from each other according
to the results for the full set of models as reported in the Additional Tables section in
Table. 5.9.
For the neighborhood controls, Latino advantage was higher in 2000 in
communities located in the central city, with more immigrants, declining population size,
higher and growing median income, growth in the housing market, and more
131
homeowners and less renters. At the metropolitan level, Latino advantage was higher in
neighborhoods located in the South compared to the West, with an expanding population,
and less Black-White segregation.
Figures 5.6 through 5.8 provide a clear visual depiction of the dominant patterns
revealed in the multivariate analyses predicting advantage for Whites, Blacks, and
Latinos. The figures present bar charts displaying predicted levels of advantage for each
of the groups. As such, predicted levels of advantage, particularly for Blacks and
Latinos, will be significantly higher than observed values given the use of averages for
the neighborhood and metropolitan controls of all neighborhoods.
Figure 5.6 shows a clear pattern in which predicted White advantage is highest in
stable White-Black communities, followed by long-term majority White areas. White
advantage in Transitioning and long-term White-Latino areas was lower (though not
significantly different from each other). Figure 5.7, presenting predicted values for Black
advantage, shows Black advantage was highest in stable majority White areas.
Interestingly, Black advantage was slightly higher in stable Black communities compared
to transitioning and stable White-Black areas (and the models in Table 5.8 in the
Additional Tables show that Black advantage in stable White compared to stable WhiteBlack, and stable Black compared to stable White-Black neighborhoods, was
significantly different from each other). Finally, predicted levels of Latino advantage
presented in Figure 5.8 show a clear pattern in which advantage is predicted to be highest
for Latinos in stable White areas, followed by transitioning areas. Predicted levels of
advantage in long-term Latino and White-Latino areas were slightly lower and similar to
132
each other. Finally, as with Black advantage in Latino-Black areas, predicted Latino
advantage in stable Latino-Black communities was the lowest of all the contexts.
5.5 Conclusion
The results in this chapter cast serious doubt over presumed benefits, particularly
for Blacks, of residence in long-term racially/ethnically integrated neighborhoods. The
central finding of the chapter is that while racially stable White-Black neighborhoods are
significantly less disadvantaged than racially stable Black areas, the average level of
Black advantage in stable White-Black neighborhoods was significantly less than the
average level for those in long-term Black neighborhoods. In contrast, Latinos do appear
to have higher levels of advantage in racially stable White-Latino neighborhoods
compared to those in stable majority Latino neighborhoods (and stable White-Latino
contexts as a whole have less disadvantage than long-term Latino communities).
This differential pattern for Latinos and Blacks is important for several reasons.
First, for the case of Blacks specifically, the finding is a direct challenge to views that
espouse that long-term integration between Whites and Blacks will result in improved
social and economic outcomes for Blacks (compared to those in segregated Black areas).
Second, the differential findings for the case of Black advantage compared to Latino
advantage highlights a dominant theme to emerge from all of the analysis in the chapter;
the patterning of neighborhood and group-level advantage for racially stable contexts
follows a clear racialized hierarchical privileging of Whites as most advantaged, Blacks
as least advantaged, and Latinos as being somewhere in between. Across all the
analyses, communities with a large proportion of Whites and the White residents in them
133
were found to be significantly more advantaged than those for Latinos and Blacks. In
turn, stable neighborhoods shared by Latinos and Whites and Whites and Blacks were
significantly more advantaged than neighborhoods with very few Whites.
The case of Latino-Black neighborhoods, in particular, further problematizes the
framing of long-term racial/ethnic integration as a beneficial outcome for minorities.
Specifically, Latino-Black neighborhoods are the most likely to remain stable over time
(almost as likely as predominantly White neighborhoods). However, across all the
analyses examining the socioeconomic character of Latino-Black neighborhoods relative
to other integrated and homogenous contexts, Latino-Black communities were the most
disadvantaged of all other areas. An integrated context with mostly Blacks and Latinos,
that is incredibly disadvantaged and likely to remain as such over time, contrasts sharply
with the conceptual frame of neighborhood integration as positive for minorities. In
essence, the findings in this chapter coupled with those in Chapter 4, indicate that LatinoBlack contexts may actually be no different, or even potentially worse off, than the longterm segregated and extremely disadvantaged segregated Black communities that receive
much attention in the segregation literature. This form of integration in particular would
serve as a poor “poster child” for a campaign aiming to highlight the benefits of longterm integration for minorities.
The distinct findings for long-term White-Black, White-Latino, and Latino-Black
communities highlight the necessity to avoid making generalizations about integrated
neighborhoods as a whole. The results show that the racial and ethnic composition of the
neighborhood plays a significant role in the social and economic character of the
neighborhood. This is not a new idea in itself, as decades of social science research have
134
demonstrated the link between neighborhood racial composition and various indicators of
neighborhood quality. However, when referring specifically to segregation and the need
to push for integration, academics quite often refer to integration in a generalized manner,
without differentiating the specific form, groups involved, and who will specifically (or
not) benefit.
Though the findings in this chapter call into question the assertions by some
policy makers and academics that long term integration is beneficial for Blacks and
Latinos, it is important to note the limitations of the analysis and findings. First, only one
outcome has been assessed for one point in time – concentrated disadvantage for
neighborhoods in 2000 and advantage for group members in 2000 (though the key
independent variables and controls span a two-decade period). We know that
neighborhood quality or desirability includes many other concrete components beyond
those related to the socioeconomic status of residents. These may include crime and
safety, the quality of schools and educational resources, employment opportunities, social
networks, policing and access to the equitable administration of justice, infrastructure and
development, the number and types of organizations available to residents, transportation,
political connections and power, social capital, and so on. All of these components of
neighborhoods must be considered, and across multiple and longer periods of time, in the
larger assessment of the potential benefits of integration for minorities. It is possible that
while a positive relationship between long term integration with Whites and
socioeconomic advantage cannot be identified for Blacks in this analysis, perhaps there
are other meaningful benefits for Blacks residing in long term integrated contexts beyond
those examined in this dissertation.
135
A second important limitation is that I am not able to disaggregate the group-level
data to identify which group members in 2000 were also residents of the neighborhood in
1980. This is a potentially serious problem, given my analytical focus on predicting how
group members benefitted (or not), at a later point in time (2000), when residing in
neighborhoods that were stable over the preceding two decades. Though I do control for
residential instability in the neighborhoods, there is no way to verify the degree to which
the specific group members represented in the advantage indices were residents in the
neighborhood in 1980 and/or 1990. If a large proportion of the residents were not living
in the neighborhood for much of the two decades, the models lose significant validity in
testing the relationship between racial/ethnic stability and group-level advantage. Recent
scholarship evaluating the Moving To Opportunity (MTO) experiment is one example of
the types of studies which may help address this issue (Sampson 2008).
Finally, an additional potentially significant limitation of the analyses relates to
the common concern of any scholarship examining individual or group-level outcomes in
geographic locales - selection bias. It is often difficult to identify whether outcomes
examined are the result of specific features of the geographic locale, or rather whether
some kind of sorting process occurs in which individuals with particular kinds of
characteristics end up in specific kinds of neighborhoods. In this particular study, I can
make no claims about the potential significance processes of selection bias may play in
determining where Whites, Blacks, and Latinos reside. However, my analytical intention
is not to make causal claims about the relationship between integration and racial/ethnic
inequality. Rather, I seek to document patterns for Whites, Latinos and Blacks in the
metropolitan residential landscape, as they play out in what I contend to be a larger
136
society characterized by a system of White supremacy that impacts housing and all other
institutions. As such, the potential role of selection bias for my study is less of concern
because I do not address the issue of why particular residents end up where they do, and
this is not consequential for the interpretation of my findings. Whatever the particular set
of processes that collectively shape patterns of where people live, I seek to uncover and
understand the outcomes associated with these patterns to better inform academic and
public policy framing of racial residential integration as it actually occurs in metropolitan
America.
137
2.5
2.1111
2
1.6725
1.5
1.2501
1
0.5
0.4549
0.3346
0.2846
0
Transitioned
-0.5
Remained
White
-0.4329
Remained
Black
Remained Remained Remained Remained
Latino
White-Latino White-Black Latino-Black
-1
Figure 5.1 Levels of 2000 Concentrated Disadvantage for Racially Stable and Transitioning
Neighborhoods Between 1980 and 2000
138
Table 5.1 Socioeconomic Stability and Change for Racially Durable Neighborhoods between 1980 and 2000
Remained or Became
Remained or Became Advantaged
Disadvantaged
139……
Stable –
Advantaged
(1)
Declined –
Still
Advantaged
(2)
Improved –
Now
Advantaged
(3)
Stable –
Disadvantaged
(4)
Declined –
Now
Disadvantaged
(5)
White
86.8%
4.4%
7.7%
.6%
.6%
Black
11.9%
.1%
5.2%
76.3%
6.5%
Latino
16.9%
.0%
8.6%
55.2%
19.3%
White-Latino
73.3%
2.3%
9.8%
6.8%
7.7%
White-Black
60.3%
.7%
12.7%
17.0%
9.3%
Latino-Black
2.1%
.0%
2.1%
89.8%
6.0%
Racially Stable 1980-2000
Table 5.2 Coefficients and Standard Errors for Key Independent Variables from Hierarchical Linear Models Predicting 2000 Concentrated
Disadvantage for 1980 White, Black, Latino, White-Black, White-Latino, and Latino-Black Neighborhoods ⁿτ±
Models With Varying Neighborhood Trajectories Serving As Omitted Reference Group
Neighborhood
Trajectory
Transitioned
(1)
Remained
White
(2)
Remained
Black
(3)
Remained
Latino
(4)
Remained
White-Black
(5)
Remained
White-Latino
(6)
Remained
Latino-Black
(7)
Transitioned
140……
τ
Remained White
-0.43**
(0.02)
Remained Black
0.86**
(0.08)
1.29**
(0.08)
Remained Latino
0.67**
(0.12)
1.09**
(0.13)
-0.19
(0.18)
Remained White-Black
0.01
(0.03)
0.44**
(0.03)
-0.85**
(0.08)
-0.66**
(0.14)
Remained White-Latino
-0.05
(0.03)
0.38**
(0.03)
-0.91**
(0.10)
-0.72**
(0.11)
-0.06
(0.04)
Remained Latino-Black
1.19**
(0.09)
1.62**
(0.09)
0.33*
(0.15)
0.53**
(0.06)
1.18**
(0.10)
Source: Neighborhood Change Data Base
1.24**
(0.07)
*p<.05 **p<.01 (two-tailed)
ⁿResults are net of metropolitan and neighborhood level controls presented in Table 5.3. Results for controls remain the same regardless of which neighborhood
trajectory is omitted as the reference group for the key independent variables.
standard errors are in parenthesis below the coefficients in each cell in the table
±
Table 5.3 Independent Controls and Intercepts for Hierarchical Linear Models Predicting
2000 Concentrated Disadvantage for 1980 White, Black, Latino, White-Black, White-Latino,
and Latino-Black Neighborhoods ⁿτ
Coeff.
Std. Err.
.001
-.008
-.000
.001
.0001**
.003**
.000*
.0001**
-.00003
-.008
.000001**
.0003**
-.001
-.001
-.001
.0001**
.0005*
.0004**
-.061
-.148
-.103
.033
.027**
.029**
-.001
.012
-.0001
.004
.0003**
.002**
.0001
.027**
Neighborhood Controls
Demographic
Central city
Proportion foreign born
Tract population
Tract population change 1980 to 2000
Socioeconomic
Median Income
Change in Median Income 1980 to 2000 - adjusted to 2000 dollars
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
Metropolitan Controls
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White dissimilarity index
White-Latino dissimilarity index
Latino-Black dissimilarity index
Intercept – (Transitioned as reference)
Source: Neighborhood Change Data Base
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
τ
Neighborhood level N=39150; Metropolitan level N=325
141
.001
.001
-.002
.001*
.177
.027**
*p<.05 **p<.01 (two-tailed)
ⁿτ
Levels are predicted holding constant the neighborhood and metropolitan character of the neighborhoods at the
mean levels for all neighborhoods.
Figure 5.2 Predicted Levels of 2000 Concentrated Disadvantage for Racially Stable and
Transitioning Neighborhoods between 1980 and 2000ⁿτ
142
White Advantage
0.75
0.533
0.2695
0.309
0.269
Remained White-Latino
Remained White-Black
0.25
Transitioned
Remained White
‐0.25
‐0.75
‐1.25
Figure 5.3 Levels of 2000 White Advantage in Racially Stable and Transitioning Neighborhoods
Between 1980 and 2000
143
Black Advantage
0.75
0.25
0.05
Transitioned
Remained White
Remained Black
‐0.25
Remained
White-Black
Remained
Latino-Black
-0.3736
‐0.75
-0.682
-0.884
-1.074
‐1.25
Figure 5.4 Levels of 2000 Black Advantage in Racially Stable and Transitioning Neighborhoods
Between 1980 and 2000
144
Latino Advantage
0.75
0.25
0.051
Transitioned
Remained White
Remained Latino
‐0.25
Remained
White-Latino
Remained
Latino-Black
-0.4517
-0.582
‐0.75
-0.998
‐1.25
-1.215
Figure 5.5 Levels of 2000 Latino Advantage in Racially Stable and Transitioning Neighborhoods
Between 1980 and 2000
145
Table 5.4 Hierarchical Linear Models Predicting 2000 White Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ⁿ
2000 White Advantage
Coeff.
Std. Err.
-0.101
0.001**
0.0618
0.015**
-0.092
0.0140**
.117
.003
.00000
-.0002
.010**
.001**
.00000
.0001**
.00003
.008
.000001**
.0002**
.0003
-.006
.001
.0001**
.0003**
.0003**
-.002
.072
-.006
.024
.024**
.026
.001
.0005
-.00002
-.002
.0003*
.002
.0001
.001**
White-Latino dissimilarity index
Latino-Black dissimilarity index
.0001
.001
.001
.001
Intercept
.423
35702
315
.019**
Neighborhood Racial/Ethnic Stability 1980-2000
Transitioned
Remained White-Black
Remained White-Latino
(Remained White –reference)
τ
Neighborhood Controls
Demographic
Central city
Proportion foreign born
Tract population
Tract population change 1980 to 2000
Socioeconomic
Median Income
Change in Median Income 1980 to 2000
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
Metropolitan Controls
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White dissimilarity index
Neighborhood level N
Metropolitan level N
Source: Neighborhood Change Data Base
*p<.05 **p<.01 (two-tailed)
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
146
Table 5.5 Hierarchical Linear Models Predicting 2000 Black Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ⁿ
2000 Black Advantage
Neighborhood Racial/Ethnic Stability 1980-2000
Transitioned
Remained White
Remained White-Black
Remained Latino-Black
(Remained Black-reference)
Neighborhood Controls
Demographic
Central city
Proportion foreign born
Tract population
Tract population change 1980 to 2000
Socioeconomic
Median Income
Change in Median Income 1980 to 2000
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
Metropolitan Controls
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White dissimilarity index
White-Latino dissimilarity index
Latino-Black dissimilarity index
Intercept
Neighborhood level N
Metropolitan level N
Coeff.
Std. Err.
-0.061
0.036
0.035
0.040
-0.072
0.035*
-0.284
0.038**
-.067
.008
-.00001
.0001
.013**
.001**
.000003
.0001
.00003
.007
.000001**
.001**
.0002
.003
.003
.0001
.0004**
.001**
.064
-.083
-.067
.038
.035*
.042
-.0002
.003
.0002
.0003
.001
.003
.0001
.001
.001
.001
.0003
.001
-.127
31647
313
.050
Source: Neighborhood Change Data Base
*p<.05 **p<.01 (two-tailed)
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
147
Table 5.6 Hierarchical Linear Models Predicting 2000 Latino Advantage in
Stable Homogenous and Integrated Neighborhoods between 1980-2000 ⁿ
2000 Latino Advantage
Coeff.
Std. Err.
0.171
0.046**
0.353
0.054**
0.109
0.036**
-0.102
0.043**
.008
.002
-.000001
-.00003
.015**
.001**
.000003
.0001**
.00003
.008
.000001**
.001**
.0002
.001
-.001
.0001**
.0004**
.0005**
.077
.111
.072
.039
.027**
.035
.0001
-.001
-.0005
-.003
.0004
.002
.0001
.001**
White-Latino dissimilarity index
Latino-Black dissimilarity index
-.0002
.001
.001
.001
Intercept
-.500
31547
315
.056**
Neighborhood Racial/Ethnic Stability 1980-2000
Transitioned
Remained White
Remained White-Latino
Remained Latino-Black
(Remained Latino-reference)
Neighborhood Controls
Demographic
Central city
Proportion foreign born
Tract population
Tract population change 1980 to 2000
Socioeconomic
Median Income
Change in Median Income 1980 to 2000
Housing
Growth in housing units 1980 to 2000
Proportion Owner Occupied
Proportion Recent Mover
Metropolitan Controls
Region – Northeast
Region – South
Region – Midwest
(West - omitted category)
1980-2000 Population Growth
Proportion Foreign Born
Change in Proportion Foreign Born 1980-2000
Black-White dissimilarity index
Neighborhood level N
Metropolitan level N
*p<.05 **p<.01 (two-tailed)
Source: Neighborhood Change Data Base
ⁿ Unless otherwise noted, all variables represent 1980 characteristics
148
Figure 5.6 Predicted Levels of 2000 White Advantage in Racially Stable and Transitioning
Neighborhoods Between 1980 and 2000
149
Figure 5.7 Predicted Levels of 2000 Black Advantage in Racially Stable and Transitioning
Neighborhoods Between 1980 and 2000
150
Figure 5.8 Predicted Levels of 2000 Latino Advantage in Racially Stable and
Transitioning Neighborhoods Between 1980 and 2000
151
ADDITIONAL TABLES
Table 5.7 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups - Predicting 2000 White Advantage
Omitted Reference Group
Independent Variable
Unstable
Remained
White
Remained
White-Black
Unstable
Remained White
0.10
Remained White-Black
0.16
0.06
Remained White-Latino
0.01
-0.09
**Bolded Coefficients are significant at p<.05
*net of other metropolitan and neighborhood level controls
152
-0.15
Remained
White-Latino
Table 5.8 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups – Predicting 2000 Black Advantage
Omitted Reference Group
Independent Variable
Unstable
Remained
White
Remained
Black
Remained
White-Black
Unstable
Remained White
0.10
Remianed Black
0.06
-0.03
Remained White-Black
-0.01
-0.11
-0.07
Remained Latino-Black
-0.22
-0.32
-0.28
**Bolded Coefficients are significant at p<.05
*net of other metropolitan and neighborhood level controls
153
-0.21
Remained
Latino-Black
Table 5.9 Coefficients Estimated for Hierarchical Linear Models with Varying
Reference Groups - Predicting 2000 Latino Advantage
Omitted Reference Group
Independent Variable
Unstable
Remained
White
Remained
Latino
Remained
White-Latino
Unstable
Remained White
0.18
Remained Latino
-0.17
-0.35
Remained White-Latino
-0.06
-0.24
0.11
Remained Latino-Black
-0.27
-0.45
-0.10
**Bolded Coefficients are significant at p<.05
*net of other metropolitan and neighborhood level controls
154
-0.21
Remained
Latino-Black
Chapter 6
Conclusion
First, as scholars who study ethnicity and race, especially as they relate to modes
of state power, we should contribute to a richer theoretical and historically
grounded understanding of diversity. Instead of just celebrating diversity, we
must theorize it, interrogate it, and actively seek the parallels and connections
between people of various communities. Instead of talking about race, we should
popularize the public’s understanding of the social processes of “racialization,”
that is, how certain groups in U.S. society have been relegated to an oppressed
status by the weight of the law, social policy, and economic exploitation.
-Manning Marable 2004:227
6.1 Introduction
In 2004, race scholars Maria Krysan and Amanda E. Lewis published an
important edited volume, The Changing Terrain of Race and Ethnicity, dedicated to
W.E.B. DuBois “for setting the standard for careful and engaged work on racial dynamics
in the United States.” The volume aims to remind academics that changing racial
dynamics are not necessarily equated with racial progress. Krysan and Lewis frame their
book as setting the stage for a new agenda of race scholarship that accounts for “shifting
demographics and meanings” while studying “progress on some fronts and retrenchment
on others” (2004:8). The theoretical insights in this volume serve as an impetus for the
formulation of my dissertation project.
155
I have sought to problematize the sociological study of racial and ethnic
neighborhood integration by examining how patterns and consequences associated with
neighborhood integration may be conditioned by the larger racialized social structure in
which they occur. I see this project as a direct response to Marable’s charge, presented in
the opening quote to this chapter, to “theorize” and “interrogate” diversity as opposed to
simply celebrating it. I argue for a need to problematize the study of neighborhood
integration. I contend that a careful analysis of the patterns and consequences associated
with integration may result in findings that suggest skepticism that recently reported
declines in segregation at the metropolitan level are translating into long-term integrated
neighborhoods that are serving to significantly diminish racial and ethnic inequality. My
rationale, as explicated in Chapter 2, is that sources and outcomes for observed patterns
in the residential landscape of the United States are situated in a societal context where
structures and systems are in place to protect White privilege and maintain Black
disadvantage (Mills 2004; Bonilla-Silva 2004). The structures, systems, and processes
may shift dramatically over time, yet they continue to ensure advantage for Whites, often
at the cost of Blacks, Latinos, and other subordinated group members. Whether
intentional or inadvertent, the presumption that cases of long-term neighborhood
integration are automatic success stories may be misguided. As social scientists work to
provide greater clarity about the mechanisms that create and maintain stratification,
neglecting the racialized context in which these processes are embedded may result in
inappropriate research questions and methods of analysis.
In my dissertation, I have sought to extend a small but burgeoning neighborhood
integration literature by addressing some of the theoretical and empirical gaps in existent
156
work. First, I provided a detailed national portrait of basic patterns of neighborhood
integration between 1980 and 2000; these showed the prevalence and durability of
integration across the two decades, what happened to integrated and homogenous
neighborhoods over time, and the relationship between advantage and the likelihood that
neighborhoods become integrated or homogenous. Here, I attempted to add greater
nuance to our current understanding of patterns given limitations of the few existing
national studies, as outlined in Chapter 2. I also worked to explicitly interpret patterns
within the context of the actual distribution of racial and ethnic group members across
neighborhood types. Second, I examined the contention that long-term integrated
neighborhoods are more advantaged contexts for Blacks and Latinos compared to
homogenous or unstable communities. Most importantly, I assessed group-specific levels
of advantage in cases of long-term integration, to assess whether Blacks and Latinos in
stable integrated neighborhoods are significantly more advantaged than those in other
types of contexts.
In this chapter, I summarize the key findings from the analyses. I also provide
further discussion for some of the most important results as they pertain to the larger
question of whether or not integrated neighborhoods are more beneficial contexts for
historically subordinated group members than other kinds of communities. I offer
specific implications for sociology and public policy, and discuss limitations and
suggestions for future research. Finally, I conclude by placing my study and the results
within the broader context of race and residence in metropolitan America.
6.2 Summary of Key Findings
157
Below, I summarize the most important findings for the three research questions
comprising the larger project. First, regarding the question of basic patterns of
prevalence and stability, I find that predominantly White, Black, and Latino
neighborhoods remained the norm across the two decades. The number and proportion of
Black and Latino neighborhoods increased somewhat, while those with predominantly
Whites decreased. This decline in majority White neighborhoods largely drove and
increase in the share of two-group neighborhoods. They increased substantially from
17.3% to 29.2% across the two decades (in particular, White-Black, White-Latino, and
Latino-Black neighborhoods). These patterns were characterized by several important
details. Whites remained concentrated in White neighborhoods despite the substantial
decline in the proportion of predominantly White neighborhoods between 1980 and 2000.
Blacks and Latinos resided in a wider range of neighborhood types than Whites. And,
across all racial neighborhood types, whether stable or undergoing transition, substantial
flux in the population composition was apparent.
I also found that homogenous neighborhoods were substantially more stable than
integrated neighborhoods, with the exception of Latino-Black neighborhoods (which
were nearly as likely to remain Latino-Black as White neighborhoods were likely to
remain White). Approximately half of 1980 Black-White and Latino-White
neighborhoods remained integrated in 2000. In contrast, more than 80% of White, Black,
and Latino neighborhoods in 1980 remained homogenous in 2000.
The analysis of the relationship between disadvantage and neighborhood change
revealed a striking pattern in which, in all cases, lower levels of disadvantage were
associated with neighborhoods becoming White, and higher levels of disadvantage were
158
associated with neighborhoods becoming Black or Latino (compared to remaining
integrated). This suggests that higher levels of advantage in integrated neighborhoods
may actually undermine integration in the long term.
In assessing the degree to which long-term integrated neighborhoods across the
two decades were more advantaged than homogenous and transitioning contexts, I found
that racially stable integrated neighborhoods with a large share of Whites (White-Black
and White-Latino areas) were significantly less disadvantaged relative to predominantly
Black and predominantly Latino areas. In line with expectations from the segregation
literature, long-term White-Black neighborhoods and White-Latino neighborhoods are
significantly more advantaged contexts compared to racially stable Black and Latino
neighborhoods. In contrast, racially stable Black-Latino neighborhoods were the most
disadvantaged form of integration. These communities also had higher average levels of
disadvantage than predominantly Black and majority Latino areas. Long-term majority
White areas were significantly less disadvantaged compared to all other contexts,
whether homogenous, integrated, stable, or unstable.
In the final portion of the analysis, I examined whether historically subordinated
group members in durable integrated neighborhoods had higher average levels of
advantage than members in homogenous and transitioning contexts. Net of the controls
in the models estimated, the average level of Black advantage in durable White-Black
neighborhoods was significantly less than the average for those in long-term Black
neighborhoods. In contrast, net of the controls in the models, Latinos had significantly
higher levels of advantage in stable White-Latino neighborhoods compared to those in
stable Latino neighborhoods. I also found that average levels of advantage for both
159
Latinos and Blacks residing in long-term Latino-Black neighborhoods were significantly
lower compared to those in all other contexts. Finally, the analysis showed that average
levels of White advantage were significantly higher in long-term White-Black than stable
White contexts.
6.3 Discussion
Several of the findings highlighted above warrant further discussion. First,
the most obvious and pressing question from the results pertains to the finding that mean
levels of Black advantage in stable White-Black neighborhoods are significantly lower
than those in long-term predominantly Black neighborhoods; they are actually
significantly lower net of the controls. This is surprising in light of the central findings of
decades of residential segregation scholarship. Indeed, considerable research
demonstrates that segregated Black contexts are highly disadvantaged as evident in high
concentrations of poverty, poor schools, negative role models, high crime, and a lack of
economic development (e.g.,Wilson 1987; Massey and Denton 1993; Krivo et. al. 1998).
This finding raises concern over the presumed benefit, for Blacks, of residing in
long-term integrated contexts with Whites (though average levels of Black advantage
were higher for group members residing in stable, predominantly White areas). In
contrast, Whites had higher average levels of advantage in stable White-Black
neighborhoods than even stable White areas. This suggests, but certainly cannot prove,
that regardless of how the urban residential landscape shifts over time in form and makeup, what will remain consistent is the advantaging of Whites over Blacks across
differential neighborhood contexts.
160
I would contend an important related point that should not to be overlooked
pertains to the tremendous inequity in both neighborhood and group-level
disadvantage/advantage between the stable White neighborhoods compared to all other
neighborhoods with large shares of Blacks and Latinos. For the large share of Whites,
and the small overall proportion of Blacks and Latinos, residing in these long-term White
communities, there is a clear socioeconomic advantage. The neighborhoods themselves
are significantly more advantaged than all others, and the group members in them
(whether White, Black, or Latino), are significantly more advantaged than their
counterparts in other communities. This is not surprising overall. However, when placed
within the context of the other findings from my analyses, it challenges how we think
about the push for integration as a solution to racial and ethnic inequality between
Whites, Blacks, and Latinos. Specifically, the findings show that Blacks are only
significantly more advantaged in “integrated” contexts for which we know they are least
comfortable – neighborhoods with only a small proportion of other Blacks (Krysan 2000;
Charles 2006).
Additionally, how do these findings fit with our understanding of the negative
consequences associated segregated Black neighborhoods (Massey and Denton 1993;
Wilson 1987)? It is important to be clear that I am not arguing that the deleterious
characteristics associated with segregated Black neighborhoods are not important, or that
we should stop work that addresses the sources and consequences of these features.
Rather, this research highlights the importance of taking a contextualized approach to the
study of race and residence which accounts for shifting demographic patterns and the
racialized societal context in which they occur. It is evident that Blacks and Latinos are
161
increasingly residing in a greater array of neighborhood types, and the number residing in
predominantly same-group neighborhoods is declining. Racialized, inequitable patterns
associated with all of the areas in which Blacks and Latinos reside need to be considered,
including but not solely, segregated Black and segregated Latino neighborhoods. In other
words, my central argument is that the findings suggest scholars should dedicate equal
attention to the raciazlized consequences for Blacks and Latinos residing in integrated
communities, as is currently given to the consequences associated with residence in
segregated Black and Latino neighborhoods. This is a more holistic approach to the
study of race, residence, and inequality, because it considers all of the contexts in which
Blacks and Latinos reside (and how this shifts over time).
A final important point to discuss pertains to the overwhelming conclusion, from
the results, that framing neighborhood integration as a singular construct is inaccurate
and problematic. It is clear that the urban residential landscape is marked by divergent
forms of integration with differential consequences for the neighborhoods and the groups
involved. The differential patterns in neighborhood advantage and group level advantage
are an important part of the story to emerge, and support theoretical arguments about a
shifting hierarchical racial order given shifts in the demographic urban landscape in
recent decades (Bonilla-Silva and Glover 2004). While this study is a first step in
establishing baseline knowledge of the socioeconomic consequences associated with
integration, the striking differential patterns found for Whites, Blacks, and Latinos and
the integrated neighborhoods where they reside, highlights the necessity to further
theoretically and empirically incorporate this into our discussion and examination of
neighborhood integration.
162
6.4 Implications for Sociology and Public Policy
What do these findings collectively mean for our understanding of race,
residence, and inequality? What are the implications of the complicated story to emerge
from my research? What do these results mean for how we think about segregation and
its consequences? Do these results imply that we should avoid a push for more racial and
ethnic integration in neighborhoods? I discuss these questions below, with a central aim
to “interrogate,” as Marable (2004) encourages, the conceptualization of stable
neighborhood integration as a significant mechanism to reduce racial and ethnic
inequality associated with segregated contexts (Marable 2004:227).
Sociology
The central sociological implication stemming from my research pertains to the
question of what this approach and the results imply for how sociologists currently
conceptualize racial residential segregation and inequality. As I have highlighted
elsewhere, to date, the majority of work on this topic is characterized by a focus on the
patterns, sources, and consequences of living in segregated Black neighborhoods. This is
not surprising given the view that racial residential segregation is the “structural
lynchpin” that maintains racial and ethnic inequality (Charles 2006; Bobo 1994).
However, I argue that macro measures of racial residential segregation (i.e., the
Index of Dissimilarity) are not a comprehensive litmus test for the state of race,
residence, and inequality in metropolitan areas in the United States. The racialized
patterns of outcomes and consequences associated with segregation and integration are
potentially better indicators than levels of segregation and integration alone. If larger
163
systems and structures remain in place to protect White privilege, patterns of racial and
ethnic inequality may persist regardless of the particular structuring of groups in
neighborhoods. It is likely that the patterns of inequality will continue to reflect
expectations stemming from the current tri-racial order, with Whites the most
advantaged, Blacks the most disadvantaged, and Asians and Latinos and Others
somewhere in between.
The sociological implication is to move away from a singular focus on one aspect
of race and residence, such as the negative consequences associated with segregated
Black neighborhoods. Rather, I contend we should work to simultaneously study the
consequences for historically subordinated group members across all the residential
contexts in which they reside. This is a more theoretically sound approach as it accounts
for the racialized patterning, and associated consequences, of groups across all types of
neighborhoods, including all the different types of integrated, segregated, or transitioning
contexts. Patterns and outcomes associated with both integration and segregation are
directly shaped by the larger racialized social structure, and this should be integrated into
our scholarship to move forward our understanding of the link between race, residence,
and inequality.
Public Policy
Several important policy implications emerge from my research, which I briefly
summarize below. It should be clear from the discussion above that I would not advocate
for a simple policy initiative that rests on the assumption that long-term cases of racial
and ethnic integration are always beneficial contexts for Blacks and Latinos. I would
argue, the negative consequences associated with residential segregation, and the
164
racialized patterning of mean levels of advantage/disadvantage in both homogenous and
integrated neighborhoods, are unacceptable. Similarly deplorable is the perpetual, and
highly color-coded inequitable distribution of resources (socioeconomic, transportation,
education, policing, justice,etc.) available to neighborhoods (which are the root of the
deleterious consequences associated with segregation). Also, the significant, on-going
role of discriminatory practices in the rental and housing markets despite decades-old
legislation in place to ensure equal opportunity in housing (Yinger 1995; Ross and Turner
2005; Massey 2005; Galster 1998), which yield segregation, is also highly problematic.
It is evident that Blacks and Latinos do not share the same privilege as Whites in selfsorting into neighborhoods based on desire and economic constraints.
For policy considerations, the central point my findings suggest is that the
consequences associated with integration for Blacks and Latinos are more important
considerations than a singular focus on arbitrary determinations of ideal racial quotas in
neighborhoods. As such, I offer the following policy suggestions in light of the
conclusions from my research:

Avoid policies that seek to achieve or maintain a specific racial quota in
neighborhoods for the sake of integration in and of itself.

Dedicate resources to improving conditions associated with the most
disadvantaged neighborhoods, whether they are integrated or homogenous. My
research demonstrates these are likely contexts where few Whites reside, such as
Black-Latino, predominantly Black, and predominantly Latino communities.
6.5 Limitations and Directions for Future Research
165
To conclude, I address some of the limitations of my research, and highlight
potential directions for future research. I will discuss limitations here not already
mentioned in the discussion in Chapters 4 and 5 pertaining to the analysis or results in
those chapters.
First, a significant concern with the approach I have taken is the issue of flux in
neighborhoods. My research indicates substantial population flux in neighborhoods that
are characterized as stable according to the typology I employ. This is especially
problematic in my assessment of outcomes in 2000 for neighborhoods that remained
racially stable in the preceding two decades. It is clear that many of the residents in these
neighborhoods were not likely residents across the two decades. Further, it is impossible
to decipher the degree to which this is the case. However, while this is a serious problem,
some assurance can be found in the work of Sharkey (2008) and Sampson and Sharkey
(2008), who find that by and large, the spatial attainment for racial and ethnic group
members moving neighborhoods replicates the existent stratified urban landscape. So
even if a substantial degree of the residents in the integrated neighborhoods moved across
the two decades, they likely moved to a neighborhood very similar in racial and class
composition to the neighborhood from which they departed. However, more importantly,
this limitation can be better addressed in studies with data similar to that which Sharkey
and Sampson (2008) analyze in their work on neighborhoods and the reproduction of
racial inequality. Specifically, these data include information about the character of
patterns of residential mobility for individuals, groups, and neighborhoods that can be
aggregated or disaggregated.
166
A second significant limitation pertains to the use of an absolute typology to
define integration. While I contend this typology is an improvement from those currently
employed in the literature, significant limitations remain. First, the typology relies on
thresholds that may be criticized as inappropriate. It is very difficult to make theoretical
claims that requiring 20% representation, as opposed to 15% or 25%, to be considered
integrated is the unquestionably best decision. A worthwhile endeavor to understand the
extent to which divergent thresholds impacts the results would be to replicate the
analyses with the use of divergent threshold level requirements (within some reasonable,
theoretically informed boundary, such as 10% to 30%).
An additional limitation with the typology employed is that it relies on a panethnic approach, failing to differentiate between diverse Latino and Asian groups. This is
particularly important in light of theoretical arguments by Bonilla-Silva and Glover
(2004) that Latinos and Asians may be found across all three of the tri-racial categories in
the current racial order. The patterns revealed in the current analysis for integrated and
homogenous neighborhoods with large shares of Latinos may mask important differences
that would be revealed if Latino diversity was accounted for in the typology. This would
allow for work to actually test Bonilla-Silva and Glovers theory (something I cannot do
here), as the results would indicate if the neighborhoods with Latinos considered Whites
or Honorary Whites were in fact more advantaged than those considered part of the
Collective Black.
A final concern with the typology and the definition of long-term integration
pertains to the decision to define as stable, neighborhoods that remained similarly racially
classified across two decades. It is difficult to know if this is an appropriate length of
167
time in conceptualizing long-term integration. Is there some other source, theoretical or
empirical, to draw from that could inform an appropriate definition of stability? It may
be important to obtain information about the degree to which this is a serious problem or
not by examining the consequences of divergent definitions of stability for the results.
Another limitation pertains to the characteristics of neighborhoods and what
makes them desirable contexts to reside. What about other concrete features associated
with the conceptualization of neighborhood quality not included in these analyses,
beyond levels of neighborhood advantage/disadvantage? Do the patterns hold when
examining outcomes such as crime and safety, collective efficacy, school quality, labor,
transportation, and health. Future research should examine these outcomes to further test
the implications and arguments stemming from my theoretical orientation and research.
When we conceptualize important qualities in neighborhoods, mean levels of
advantage/disadvantage are one, but certainly not the only, important factor to consider.
Though the relationship between residence in stable White-Black neighborhoods
and Black advantage is negative, there are a host of other concrete features of
neighborhoods that may be beneficial for Blacks residing in integrated as opposed to
same-group neighborhoods (particularly highly disadvantaged segregated Black areas).
We know that areas with large proportions of Whites have more resources, infrastructure,
less crime, and better schools. I do not examine here the possibility that Black residents
in long-term White-Black neighborhoods may in fact benefit, over time, from exposure to
potential features associated with White-Black neighborhoods compared to segregated
Black communities. Of course, examining this question will also require assessing how
Whites and Blacks may differentially benefit from the same resources in shared
168
neighborhoods. It is problematic, from a theoretical perspective, to assume that group
members experience the same benefits from the contexts in which they simultaneously
operate (Zuberi and Bonilla-Silva 2008). Consideration of the interactional mechanisms
of inequality production may play a significant role when examining this question. My
research is a starting point, and these are questions that need to be addressed as scholars
continue to explore the connection among race, residence, and inequality.
Finally, I do not account for the potentially significant influence of surrounding
areas in impacting the outcomes I examine. Recent theoretical developments in
criminology as well as the study of neighborhood change emphasize the role that
characteristics of adjacent neighborhoods play in shaping outcomes (e.g., Krivo and
Peterson 2009; Crowder and South 2008). Future work should incorporate these
sophisticated spatial methods to better account for the relationship between integration
and disadvantage. This is especially important given the problems associated with
reliance on the census tract as a proxy for neighborhoods.
In conclusion, my research challenges the promise of neighborhood integration as
a solution for the problems associated with racial residential segregation. The results do
not support the conceptualization of long-term integrated neighborhoods as significantly
impacting mean levels of advantage for Blacks compared to those in long-term primarily
Black neighborhoods. The findings for Latinos are more promising. Nonetheless, while
causal claims are not possible, I hope the theoretical orientation and ensuing analysis and
results which characterize this project, serve to inspire other researchers to “interrogate”
some of the implications of my findings.
169
Here, I have focused specifically on racial and ethnic neighborhood integration
and its associated consequences for Whites, Blacks, and Latinos. However, the larger
approach I adopt, which considers how processes and outcomes are conditioned by larger
racialized systems and structures, is not limited to the examination of race and residence
exclusively. I would argue, following Zuberi and Bonilla-Silva (2008), that all
examinations of inequality should consider the role of the larger system of White
supremacy in shaping outcomes; regardless of the form of inequality or the level of
analysis. Progress remains limited by the questions we ask (or not) and the methods we
employ to answer these questions; the difficulty is identifying what is most appropriate
and relevant for both endeavors.
170
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