Growing Racial Segregation of Latino Children in U.S. Schools from 1998-2010

Educational Researcher, Vol. 48 No. 7, pp. 407 –420
DOI: 10.3102/0013189X19860814
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OCTOBER 2019 407
Racially segregating students of color in certain schools—
separated from White or middle-class peers—often cor-responds
with unfair financing of schools, regressive
allocation of quality teachers, and culturally limited curricula
(e.g., Noguera, Pierce, & Ahram, 2015; Vasquez Heilig, Brown,
& Brown, 2012). But little is known about whether the racial or
economic segregation of young Latino children—as they enter
kindergarten—is easing or growing worse.
We do know that Latino children have enjoyed gains in early
learning and social development during their preschool years
since the 1990s (Bassok, Gibbs, & Latham, 2018; Reardon &
Portilla, 2016). Yet the segregated settings that beset many
Latino children as they enter school likely constrain this
progress
(Owens, 2018). An earlier generation of research detailed how
Black children benefit from integrated schools (for review, see
Cook, 1984). Yet little is known empirically about recent trends
in levels of racial and economic segregation that confront
Latino
children at entry to elementary school.
We contribute to the segregation literature by focusing on
schools that young Latino children enter, matching universe

data
for the nation’s schools and districts with family and child-level
data, 1998 to 2010. This allows us to (a) observe trends in the
isolation of Latino children within certain schools in school
districts nationwide, (b) disaggregate trends for children of
immigrant and native-born parents, and (c) learn how school
ver-
sus neighborhood contexts are changing for Latino children. We
also ask whether patterns of racial and economic segregation
may
move independently over time, as many Latino families spread
across the nation, some enjoying upward mobility (Dondero &
Muller, 2012; Reardon & Bischoff, 2011).
Overall, we find intensifying segregation of Latino children
from White peers among schools in districts that enroll at least
10% Latino pupils; this set against already high levels of racial
isolation. Nor have the nation’s 10 districts serving the poorest
concentrations of students shown discernible progress toward
integrating Latino students among their constituent schools.
Children from low-income families—regardless of race or
Latino
ethnicity—did increasingly attend school with middle-class
peers over the 1998 to 2010 period.
Our more textured child and family-level data verify that
Latino kindergartners experienced declining exposure to White
peers during the period. Those of foreign-born mothers entered
860814EDRXXX10.3102/0013189X19860814Educational
ResearcherEducational Researcher
research-article2019
1University of California, Berkeley, CA
2University of Maryland, College Park, MD

3University of California, Irvine, CA
Worsening School Segregation for Latino Children?
Bruce Fuller1, Yoonjeon Kim1 , Claudia Galindo2, Shruti
Bathia1, Margaret Bridges1,
Greg J. Duncan3, and Isabel García Valdivia1
A half century of research details how segregating racial groups
in separate schools corresponds with disparities in funding
and quality teachers and culturally narrow curricula. But we
know little about whether young Latino children have entered
less or more segregated elementary schools over the past
generation. This article details the growing share of Latino
children from low-income families populating schools, 1998 to
2010. Latinos became more segregated within districts
enrolling at least 10% Latino pupils nationwide, including large
urban districts. Exposure of poor students (of any race)
to middle-class peers improved nationwide. This appears to
stem in part from rising educational attainment of adults in
economically integrated communities populated by Latinos.
Children of native-born Latina mothers benefit more from
economic integration than those of immigrant mothers, who
remain isolated in separate schools. We discuss implications
for local educators and policy makers and suggest future
research to illuminate where and how certain districts have
advanced integration.
Keywords: early childhood; early learning; educational policy;
equity; immigration/immigrants; Latino children;
longitudinal studies; regression analyses; segregation
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408 EDUCATIONAL RESEARCHER
even more sharply segregated schools, compared with Latino
peers of native-born mothers. At the same time, Latino children
more often resided in neighborhoods with higher educational
attainment, and parents’ schooling predicted children’s entry to
economically integrated schools.
We discuss implications for local educators and policy mak-
ers, then sketch future research priorities. Trends in
neighborhood
segregation condition school segregation and improved
exposure
to middle-class peers. But little is known on how education
lead-
ers and policy makers might advance gains at the community
level for Latino children, progressively financing schools and
fairly allocating high-quality teachers. This article does not
revisit the consequences of deep-seated segregation on learning.
We do unpack local variation in the school and neighborhood
contexts of Latino children and how these settings are changing
over time.
Integrating Latino Children—Progress or
Regress?
Schools can act to ease or harden disparities experienced by
chil-
dren of Latino or low-income families. Yet as educators and
policy makers attempt to buoy Latino children—seeking to
advance their early growth and learning—little is known about

whether they are entering less or more segregated schools and
how trends may differ for the offspring of immigrant versus
later-generation parents. The segregated facets of
neighborhoods,
especially housing patterns, contribute to the extent to which
Latino children attend schools with White or middle-class peers.
This article focuses on trends in school segregation, while also
reporting on relevant features of neighborhoods in which Latino
children are raised.
Tracing school and residential segregation has become more
complicated as many Latino families exit urban enclaves (partly
fostered by rising educational attainment), bound for what
demographers term new destinations —suburbs, exurbs, or rural
areas—still mainly White in their demographic composition,
often hosting schools that are ill-equipped to serve diversifying
children and families.
“Migration [within the United States] ostensibly permits resi-
dents to overcome place-linked disadvantages,” as Tienda and
Fuentes argue (2014, p. 505). But “Institutional barriers, eco-
nomic conditions, and housing constraints limit the realization
of social mobility.” And even when Latino parents search out
materially better-off neighborhoods, their children may not
enter more integrated schools. Housing patterns and local dis-
trict policies (or inaction) may limit the likelihood of finding
integrated schools.
Overall, it is not clear whether school segregation for young
Latino children is increasing or decreasing nationwide. Crosnoe
(2005) found that Mexican-heritage children sorted into
schools with greater concentrations of poor and non-White stu-
dents relative to White peers, drawing on a nationally represen-
tative sample. Orfield and Lee (2007) reported that 60% of all
Latino students (K–12) attended high-poverty schools nation-
wide (at least half in poverty), as did less than one-fifth of all

White pupils (18%).
Tracking student composition in 350 metro areas, Stroub and
Richards (2013) found that after peaking in the late 1980s,
mean levels of racial segregation among schools within districts
had fallen modestly by 2009. They also found modest gains in
the integration of Latino students across K–12, in part mirroring
family movement to once predominantly White suburbs (con-
sistent with Fiel, 2013; Iceland & Sharp, 2013). Racial integra-
tion among non-White groups has improved modestly as well,
but not necessarily across economic classes (Reardon & Owens,
2014). That is, the capacity of families to move into middle-
class
neighborhoods (independent of race or ethnicity) may condition
the likelihood of selecting an integrated school.
Turning to residential segregation, Iceland and Sharp (2013)
found that the average Latino resident was less likely to see a
White neighbor in 2010, compared with 1980, after examin-
ing segregation among communities situated in 366 metro
areas. We know that Latinos displayed slightly rising levels of
residential segregation from Whites, 1970 to 2010, across 287
metro areas (Alba & Foner, 2015). And aging suburbs, although
better-off economically compared with immigrant enclaves,
remain quite segregated racially (Lichter, Parisi, Taquino, &
Grice, 2010).
A majority of Latinos by 2010 resided in suburban parts of
metro areas for the first time nationwide, in part stemming from
migration to new destinations in the Midwest and South
(Hirschman & Massey, 2008). Fully one-third of Mexican immi-
grants to the United States, between 1995 and 2000, settled into
nontraditional states (Lichter et al., 2010). Many more left
tradi-
tional immigrant gateways, heading out to diversifying suburbs.

These findings prompt the question of how residential segre-
gation conditions the isolation of Latino children in certain
schools. Both family selection and place-based factors appear to
determine when segregation among schools diminishes or grows
worse. As certain Latino families sort into new destinations, for
instance, this alters the ethnic and economic mix of district
enrollments. Better educated Latino parents may seek middle-
class neighborhoods, while still enrolling their children in pre -
dominantly Latino schools—achieving greater exposure to
middling, but not necessarily White, peers (Reeves & Busette,
2018).
Incumbent residents of neighborhoods also shape evolving lev-
els of segregation via higher fertility rates among some groups,
along with the out-migration of White families. Part of the
“reseg-
regation” of schools stems, not so much from school policy, but
from higher birth rates among Latina mothers, relative to other
groups residing in the same neighborhoods (Logan, 2004).
Yet we still know little about whether young Latino children
are entering schools in which exposure to White or middle-class
peers is improving or diminishing and how these trends vary for
the offspring of immigrant versus native-born Latino parents.
Nor do we know whether children from low-income children
(independent of their race or ethnicity) interact more or less
with
middle-class peers over time. This conditions the experience of
Latino children from poor households. We examine these trends
over the 1998 to 2010 period, an era that witnessed unstable
policies toward English learners, resurging hostility toward
immigrants, and recovery from the Great Recession.
OCTOBER 2019 409

Mapping Segregation—Variation Across Geographies
and Social Classes
Children of Latino heritage, of course, make up a rising share of
school enrollments across the nation. Over one-fifth of all kin-
dergartners were of Latino heritage in 17 states by 2012
(Stepler
& Lopez, 2016). As Latino parents radiate out from urban
enclaves, some do settle in less segregated neighborhoods.1
This
suggests that levels of residential integration may be improving
in many neighborhoods, or at least variability grows wider,
com-
pared with old Latino enclaves in urban centers. This may
condi-
tion trends in school segregation.
To illustrate local variation in residential segregation, Figure 1
displays the share of population, White, for Los Angeles census
tracts in which at least one-fourth of all residents were Latino
(based on kindergarteners in the federal Early Childhood
Longitudinal Study [ECLS], 2010). We see a slight presence of
White neighbors in predominantly Latino tracts downtown
(near the “101” freeway label), with greater integration east and
northwest of the central city.
The L.A. pattern of geographic dispersal backs an optimistic
theoretical position known as spatial assimilation, claiming that
immigrant groups will assimilate into the middle class as they
enjoy gains in education and job status over time (Alba,
Kasinitz,
& Waters, 2011). These advances by individuals accumulate,
according to this account, to lift the economic status and racial
integration of neighborhoods, increasingly populated by second-
and third-generation descendants of immigrant settlers.

This theoretical lens suggests that the isolation of low-status
children in particular schools will ease as residential
segregation
lessens, as experienced with White European immigrants a cen-
tury ago. But whether this allegedly natural drift toward assimi -
lation will be enjoyed by contemporary Latino immigrants,
especially when racialized and stigmatized in many communi -
ties, remains unknown. Nor is it clear that Latinos entering
racial or economically integrated neighborhoods will sort into
integrated schools.
Other scholars counter with place stratification theory, argu-
ing that class and racial markers continue to leave Latinos in
subordinate and isolated positions, even as they move to
promis-
ing economic destinations in which to raise children. “Economic
mobility is no guarantee of residential integration,” as Lichter,
Parisi, and Taquino (2015, p. 36) argue.2 This suggests that
racialized markers will segregate Latinos into separate schools,
even when the larger geographic unit (metro area or school dis -
trict) is becoming more diverse. One troubling case occurs when
immigrant Latinos move into new destinations, where incum-
bent residents remain hostile or school districts are ill prepared,
often assigning newcomers to highly segregated schools.
This theoretical position highlights the pivotal role of educa-
tion leaders, as they allocate Latino students and scarce
resources
FIGURE 1. Varying levels of Latino segregation for sampled
Los Angeles census tracts, 2010.
Source. U.S. Census Bureau (2011) and National Center for
Education Statistics (2001). Cartography by GreenInfo Network,
www.greeninfo.org.

www.greeninfo.org
to particular schools. That is, racial status and local histories
must be explicitly taken into account if school segregation is to
be effectively addressed. And conscious school interventions
are
more likely to make a difference under this theoretical view -
point: Levels of school segregation are not necessarily driven
by
residential or housing patterns alone.
Ecological theory may further explain variation in levels of
segregation observed among schools within districts. Urban
ecologists take a broader look, studying how the movement of
people, jobs, and housing between urban centers and suburbs
comes to racially segment groups among differing schools.3
Patterns of residential segregation, housing prices, and the
city’s
racialized political economy all shape which families populate
differently situated school districts (Reardon & Owens, 2014).
Differential fertility rates for Latinas, tied to maternal educa-
tion levels, then alter the complexion of districts and school
attendance zones over time. Legal histories and district policies
shape efforts to ease or sustain the segregation of non-White
stu-
dents in separate schools as well (Henig, Hula, Orr, &
Pedescleaux, 2001). Whereas the urban ecology frame stems
from older structural views of the city’s political economy, the
school institution may act with some autonomy to ease the
isola-
tion of particular students in certain schools.

The Latino case becomes more complicated by the wide vari -
ation in the class position of this growing population, differing
between the offspring of immigrant versus later-generation
Latinos. Rising school attainment, for instance, spurs exit from
urban enclaves and upward mobility for some Latino parents
(Bean, Brown, & Bachmeier, 2015).
We know that residential segregation is higher in locales host-
ing greater shares of foreign-born, rather than native-born,
Latinos (Iceland & Nelson, 2008). In contrast, native-born
Latinos with children tend to live in higher-income areas and
closer proximity to Whites (Fuller, Bein, Kim, & Rabe-Hesketh,
2015; South, Crowder, & Chavez, 2005).4 Markers of social
class, especially the nativity of parents, may interact with
neigh-
borhood attributes to shape children’s attainment (Brazil, 2016;
Owens, 2010).
But it is unknown whether young Latino children have
entered more or less racially segregated schools in recent
decades.
Recent findings show that American society overall is becoming
more economically segregated, as affluent Americans
increasingly
reside in exclusive enclaves (Gibson-Davis & Percheski, 2018;
Reardon & Bischoff, 2011). Yet for the wide middle class, we
have little understanding of whether Latino children are gaining
greater exposure to middle-class children (economically inte-
grated schools) and how these trends may vary between immi -
grant and later-generation Latino families.
Contexts of School Reception
As Latino families spread to new areas, little is known about the
kinds of schools they enter. Dondero and Muller (2012) found
fewer bilingual teachers and less access to advanced courses in
new-destination schools, compared with schools in older Latino

enclaves. Focusing on the 30 largest “new settlement areas,”
Fry
(2011) found that Latino students in K–12 enjoyed greater
exposure to White and more affluent peers, compared with
enclaves. Other work finds that “the traditional sites … of
Latino
growth – where the knowledge and resources to turn around the
problem are potentially in greater abundance – are no longer the
sites of greatest growth” (Gándara & Mordechay, 2017, p. 151).
Place certainly matters for how schools receive immigrant
and later-generation Latino children, manifest by teachers with
varying cultural competence, those who speak Spanish or reach
out to parents (Perreira, Fuligni & Potochnick, 2010). How dis -
tricts allocate resources among schools often stems from segre-
gated housing and schools, along with local educators’ varying
commitment to racial or economic integration (Orfield & Lee,
2007; Vasquez Heilig, Khalifa, & Tillman, 2014).
Such place-based policies can hold long-term consequences:
Mexican American females raised in Texas, for instance,
display
lower school attainment and higher fertility, compared with
peers in California (Van Hook, Bean, Bachmeier, & Tucker,
2014). And we know that Black-White achievement gaps are
wider in highly segregated districts (Owens, 2017).
Research Questions and Analytic Strategy
In sum, evidence remains mixed on whether Latino students
attend
schools that offer rising or diminishing exposure to White or
mid-
dle-class peers. Nor do know whether children from poor house-
holds (independent of race or Latino ethnicity) attend schools

offering greater interaction with middle-class peers over time.
Even
less is known about segregation trends for young Latino
children as
they enter kindergarten, along with the differing experiences of
immigrant and native-born offspring. And as diverse Latino
fami-
lies spread out to diverse suburbs and exurbs, have they
benefited
from more racially or economically integrated schools?
This article informs these empirical gaps by asking whether
Latino children’s exposure to White peers in elementary school
increased or declined between 1998 and 2010. We also describe
whether exposure of poor to nonpoor children (regardless of
race
or ethnicity) changed in districts enrolling significant shares of
Latino pupils. We report standard measures of racial and eco-
nomic segregation among schools within the nation’s school
dis-
tricts. Then, we draw on representative cohorts of individual
kindergartners over the same period to replicate these patterns
and, going deeper, to examine differences in school and neigh-
borhood contexts.
Racial segregation among schools within districts—
RQ-1A: Did the racial segregation of Latino children within
isolated elementary schools increase or decline in the
nation’s school districts, 1998 to 2010?
RQ-1B: Did the segregation of students of low-income fami-
lies from middle-class peers regardless of race or ethnicity
in isolated elementary schools (economic segregation)
increase or decline, 1998 to 2010?

Racial segregation for Latino kindergartners and subgroups
and explaining variation—
RQ-2A: Did the nation’s average Latino kindergartner enter
an elementary school with rising or declining concentra-
tions of Latino peers (racial segregation)?
OCTOBER 2019 411
RQ-2B: Did the nation’s average Latino kindergartner enter
an elementary school with rising or declining concentra-
tions of peers from low-income families (economic
segregation)?
RQ-2C: Among Latino kindergartners from economically
diverse families, what markers of social class predict higher
or lower levels of racial segregation?
Method
Our analysis builds from two tandem data sets. First, we assem-
bled enrollment data for all public elementary schools and dis -
tricts nationwide, drawn from the Common Core of Data
(CCD) in 1998 and 2010, compiled by the National Center for
Education Statistics (NCES, 2001).5 This allowed us to con-
struct multiple measures of racial and economic segregation
among schools within districts. Then, we replicated observed
patterns for Latino kindergartners at school entry, along with
disaggregating trends for subgroups of Latino children, drawing
on nationally representative samples of kindergartners in the
same years, 1998 and 2010, from the Early Childhood
Longitudinal Study (ECLS-K; NCES, 2001).6
The CCD in 1998 includes enrollment data broken down

by ethnicity and eligibility for free or reduced-price meals
(FRPM) for a universe count of 50,529 elementary schools
nationwide situated in 13,215 school districts. The corre-
sponding counts in 2010 were 53,636 and 13,849, respectively.
The ECLS-K data are drawn from national probability samples
of 7,219 children in 1998 (nested in 442 districts) and 8,627
(in 419 districts) for 2010, after losing cases (a) with missing
nativity data on the mother, (b) absent a match between school
or family to the respective census tract, or (c) when all covari -
ates necessary for regression estimates were not available for
the
final analysis (NCES, 2018; U.S. Census Bureau, 2011). We
weighted all data using the sampling weights provided in the
ECLS-K data set.
Measures
Latino children, families, and subgroups. The CCD reports
enrollment counts of elementary school children identified by
local education authorities as Latino. The ECLS-K data goes
deeper, based on field interviews of the household respondent,
usually the mother. Each self-identified as of Latino origin or
another ethnic heritage and whether they were native or foreign-
born. We only draw on data collected by field staff when the
child was attending kindergarten. Subsequent interviews with
mothers include questions about country of origin, but this
information was not utilized in the present article.7
District and school-level segregation. Multiple indicators of
segregation—the extent to which one group disproportionately
resides in certain units (schools) situated within a larger
geographic
or institutional unit (districts)—are commonly used in the
demog-
raphy and immigration literatures (Reardon & Owens, 2014).
We

describe the conceptual justification for each measure.
For each of the nation’s districts that host at least one elemen-
tary school, we calculated the two-group interaction (exposure)
index, interpretable as the probability that a randomly drawn
Latino student shares a school with a White peer (Massey &
Denton, 1988; Owens, 2017). This measure indicates the extent
to which Latinos are exposed to Whites in elementary schools.
This index ranges higher—indicating strong integration—when
Latino students are evenly distributed among schools within the
district, relative to the distribution of White peers. (The formula
for calculating each index appears in the appendix.)
Given that Latino children may attend schools populated by
multiple ethnic groups, not limited to Whites, we also
calculated
entropy for each school, measuring the evenness of the
represen-
tation of two or more groups (i.e., Black and Asian-heritage
chil-
dren). Finally, we include the dissimilarity index (D), the
absolute value of what percentage of White students would have
to exit a school to reach parity with the Latino share. Shares of
pupils enrolled who are Latino, White, or FRPM-eligible are
reported. Analyses were conducted for all the nation’s
elementary
schools and host districts, then separately for districts enrolling
at least 10% Latino children.
We use the term “middle class” to describe kindergarteners
whose family income exceeded the eligibility threshold for
FRPM.
Change in the percentage of students qualifying for FRPM does
not always track against child poverty rates, one reason that we
report the share of enrollment who are English learners, along
with neighborhood attributes for sampled kindergartners drawn

from the ECLS-K data (Hoffman, 2012; NCES, 2018).8
Neighborhoods. Given interest in how school segregation varies
among types of neighborhoods, we matched each kindergartner
to her or his census tract of residence. This allows us to report
from the ECLS-K data median household income, poverty rates,
and educational attainment of resident adults in 1998 and 2010,
as key indicators of the child’s social context.9 We also
determined
whether the family resided in a new destination or traditional
urban enclave, utilizing Tran and Valdez’s (2015) procedure.
Markers of family social class. We report on attributes of
kinder-
gartners and households, focusing on markers of class that help
to explain variation in segregation among schools. These factors
include household income (adjusted to 2018 dollars); maternal
education as dichotomous indicators of less than high school,
diploma, some college, or bachelor’s degree or more; non-Eng-
lish home language; and female-headed household or not. After
reporting descriptive trends, 1998 to 2010, we estimate the
extent
to which the class position of Latino families contributes to the
level of school segregation experienced by their
kindergartner.10
Findings
Shifting Segregation Levels for Latino Children (RQ1)?
We first replicate earlier work showing that the nation’s schools
serve rising shares of Latino pupils and students from low -
income families regardless of race or ethnicity, over the 1998 to
2010 period. Latino students experienced declining exposure to

White peers over the period in districts with at least 10% Latino
enrollment. At the same time, students from low-income house-
holds (regardless of race) were more likely to attend school
with
a middle-class peer.
We see in column 1 (Table 1) that Latino children’s expo-
sure to White peers across all school districts remained con-
stant on average (row A, index score, .61), 1998-2010; whereas
the likelihood that poor children were exposed to middle-class
peers increased markedly (.33 to .45, p < .001, about two-
fifths SD).
Turning to districts with enrollments at least 10% Latino
(row B), we see the interaction exposure index declining from
.50 to .47 (p < .001) by a small level of magnitude (.11 SD). We
again see a rising likelihood of poor students being exposed to
middle-class students among schools (regardless of race); the
index rising from .31 to .38 (p < .001, .29 SD).
Note that many more districts enrolled at least 10% Latino
children in 2010 (4,277), compared with the count in 1998
(2,321). Trends did not appreciably change when comparing
1998 and 2010 levels only for the original 2,321 districts. This
constant set of districts also displayed declining interaction
between Latino and White children, along with improving inter-
action between children of poor and those of middle-class fami-
lies (again, regardless of race or ethnicity). The share of
students
enrolled, FRPM eligible, climbed from 38% to 61% over the
period. This was partly due to liberalized eligibility for free and
reduced-price meals at school.

We calculated segregation indices for the nation’s 10 poorest
districts (based on FRPM shares) enrolling more than 50,000
pupils and at least 10% Latino, as reported in row C.11 Over all,
we see considerably lower Latino-White interaction scores,
indi-
cating more severe segregation of Latino children in separate
schools, relative to national averages. Schools in these 10
districts
enrolled increasing shares of Latino students, whereas the per-
centage of students, White, declined over the period.
Placing these index values in context, large urban districts
tend to display quite high levels of racial segregation, such as
Los
Angeles or San Antonio, where the interaction index dropped
below .10 in 2010. On the other hand, certain subdistricts of
New York City schools display stronger integration of Latinos,
above .35 on the index.
Patterns are quite similar when moving to the districts from
which ECLS-K kindergartners were sampled (rows D and E),
except that the likelihood of Latino children’s exposure to
White
peers fell from .65 to .51 over the period (p < .001, .40 SD). It
may be that Latino families with kindergarten-age children
reside
in more segregated neighborhoods relative to families with
older
children attending elementary school. Again, we see rising
expo-
sure of poor to middle-class children, a gain of moderate magni-
tude among the ECLS-K school districts (p < .001, .35 SD).
Table 1
Change in Segregation for the Nation’s School Districts and
Elementary Schools and for ECLS-K Sample of

Units Serving Kindergartners, 1998 to 2010
District Segregation School Segregation
N
Latino
Exposure to
Whites
FRPM
Exposure to
Non-FRPM
N
Percent
Enrolled
Latino
Percent
Enrolled
White
Percent
Enrolled
FRPM Dissimilarity
Racial
Entropy
[1] [2] [3] [4] [5] [6] [7]
Universe counts nationwide

A. All districts
1998 13,215 .61 (.38) .33 (.33) 50,529 .14 (.25) .64 (.35) .28
(.30) .65 (.33) .38 (.24)
2010 13,849 .61 (.37) .45 (.25) 53,636 .22 (.28) .53 (.37) .52
(.29) .56 (.32) .46 (.23)
B. All districts with enrollment
>10% Latino
1998 2,321 .50 (.26) .31 (.27) 13,793 .44 (.30) .36 (.28) .38
(.34) .46 (.29) .58 (.19)
2010 4,277 .47 (.27) .38 (.22) 25,568 .43 (.29) .35 (.27) .61
(.27) .45 (.28) .59 (.20)
C. Nation’s 10 poorest districts (FRPM)
>10% Latino enrollment
1998 10 .07 (.05) .16 (.04) 1,097 .58 (.31) .11 (.17) .76 (.23)
.52 (.32) .65 (.36)
2010 10 .05 (.35) .25 (.10) 1,283 .66 (.30) .08 (.16) .68 (.25)
.63 (.31) .59 (.35)
Sampled units hosting ECLS-K kindergartners
D. All sampled districts
1998 442 .65 (.41) .37 (.32) 1,297 .18 (.26) .51 (.37) .37 (.34)
.54 (.34) .40 (.25)
2010 419 .51 (.32) .48 (.25) 1,086 .27 (.28) .44 (.33) .54 (.29)
.49 (.31) .50 (.23)
E. All sampled districts with enrollment > 10% Latino
1998 148 .37 (.39) .34 (.26) 503 .43 (.28) .32 (.27) .47 (.36)
.44 (.27) .56 (.20)
2010 239 .36 (.25) .39 (.21) 668 .42 (.27) .33 (.26) .59 (.27)
.42 (.27) .59 (.20)
Note. FRPM = free or reduced-price meals; ECLS-K = Early
Childhood Longitudinal Study.
OCTOBER 2019 413

Turning to school-level indicators of segregation, we see a
jump in the share of elementary students nationwide of Latino
heritage, rising from 14% in 1998 to 22% in 2010, on average
(row A), but no appreciable change for districts with 10%
Latino
enrollment (row B). The rise in FRPM pupils is larger, climbing
from 38% to 61% among schools in districts with 10% Latino
children or more.
The dissimilarity index fell about one-fourth SD, and entropy
climbed about one-third SD—both measures indicating a more
even racial distribution of students within the nation’s average
elementary school. This is consistent with the rise in integration
among non-White populations among neighborhoods reported
above (Reardon & Owens, 2014). Yet the gains we observed are
not apparent for elementary schools situated in districts with at
least 10% Latino enrollment. Patterns are quite similar for
schools
from which ECLS-K children were sampled (rows D and E).
Differences for Latino Subgroups and
Neighborhoods (RQ2)
Next, we describe school contexts experienced by individual
kin-
dergartners, focusing on Latino subgroups, drawing on the
ECLS-K data. Table 2 reports changing indicators of Latino
chil-
dren’s exposure to White or middle-class peers. We see that the
percentage of students, White, for the mean Latino
kindergartner
declined from 37% to 30% between 1998 and 2010 (p < .05).
We observe a corresponding rise in the share of students identi-
fied as English learners, climbing from 23% to 33% (p < .01).
This confirms that rising concentrations of children from poor
families are not merely artifacts of liberalized FRPM eligibility.

Entropy scores increased over the period for the mean
kindergart-
ner, suggesting a more even distribution among multiple ethnic
groups.
The mean Latino kindergartner experienced deteriorating
neighborhood conditions in terms of falling household income
and rising poverty. Median income fell from $56,291 in 1998 to
$52,348 in 2010 (current dollars), likely due to the post-2007
recession. Yet educational attainment rose for adults in the
mean
Latino child’s tract: 42% of all adults reporting some college in
1998, rising to 47% in 2010. Educational aspirations may oper-
ate somewhat independently of economic shocks, a hopeful
finding for educators and policy makers who endeavor to com-
bat segregation.
Table 3 reveals sharply differing contexts for Latino children,
depending on maternal nativity. The share of peers, White,
dropped from 47% in 1998 to 37% in 2010 for the mean Latino
kindergartner with a native-born mother (p < .05). These shares
equaled 31% and 25%, respectively, for the corresponding child
with a foreign-born mother. Both subgroups of children entered
schools with rising shares of English learners: climbing from
14% to 23% for native-born, and 30% to 39% for foreign-born
over the period (p < .05 in both cases). Children of foreign-born
Table 2
Descriptive Statistics for Census Tracts and Schools in Which
Sampled Families Reside, Split by Ethnicity, for
1998 and 2010 Cohorts (Means and SDs Reported)
1998 2010
All White Latino All White Latino

Schools
Ethnicity and segregation
Percent enrollment, White 0.68
(0.31)
0.80
(0.21)
0.37
(0.32)
0.59
(0.31)
0.73
(0.22)
0.30
(0.29)
Percent enrollment, Latino 0.13
(0.22)
0.07
(0.11)
0.46
(0.32)
0.19
(0.25)
0.11
(0.14)

0.53
(0.33)
Dissimilarity 0.67
(0.30)
0.76
(0.25)
0.53
(0.32)
0.58
(0.30)
0.66
(0.27)
0.56
(0.31)
Entropy 0.38
(0.23)
0.33
(0.21)
0.48
(0.22)
0.46
(0.23)
0.44
(0.22)

0.48
(0.24)
Social class
Percent enrollment, eligible for subsidized meals 0.28
(0.30)
0.21
(0.24)
0.43
(0.35)
0.43
(0.30)
0.35
(0.26)
0.59
(0.33)
Language
Percent enrollment, English learners 0.06
(0.15)
0.02
(0.07)
0.23
(0.27)
0.12
(0.21)
0.06

(0.13)
0.33
(0.29)
Tracts
Median household income ($) 65,887
(27,346)
70,465
(27,060)
56,291
(24,739)
61,760
(27,594)
66,795
(27,608)
52,348
(22,398)
Percent population in poverty 11.7
(10.08)
8.78
(6.88)
17.83
(12.19)
14.38
(11.68)

11.24
(8.98)
20.44
(13.86)
Percent population with some college or more 51.3
(17.96)
54.28
(16.84)
41.82
(19.12)
57.29
(17.37)
60.95
(15.59)
47.23
(18.68)
N of matched families 7,219 4,957 964 8,627 5,372 1,468
mothers were more highly concentrated in urban enclaves and
new destinations, relative to peers with native-born mothers
residing in all other tracts.
Median household income held steady for the average Latino
kindergartner with a native-born mother but fell sharply for the

mean peer with a foreign-born mother (falling by $7,721, p <
.05). School attainment climbed, most markedly in neighbor-
hoods of foreign-born mothers, even in the recession’s wake
(Table 4).
Which Latino Children Sort Into Segregated Schools?
Given the wide diversity of Latino families, we asked whether
certain markers of social class hold explanatory power in
account-
ing for variation in levels of school segregation. Results appear
in
Table 5, when estimating three measures of segregation,
regress-
ing on social-class features of Latino families. Column 1 shows
that home language is a major driver of the share of the aver age
kindergartner’s peers who are Latino. This percentage is 17
points higher for Latino kindergartners of Spanish-speaking par-
ents, compared with those from English-speaking homes.
Family
income, a second marker of class position, is negatively related
to
entering a school with higher concentrations of Latino peers.
Robust results also appear when estimating the share of
enrollment, FRPM eligible (column 2). Beyond household
income and home language effects, Latino children whose par-
ents completed some college entered elementary schools with
lower shares of poor peers. This helps to explain why
integration
of children from poor and middle-class homes improved over
the period. We earlier saw that the average Latino child resided
in a neighborhood with higher educational attainment in 2010,
relative to 1998. The regression finding now shows that Latino
children with better educated parents entered schools with lower
shares of FRPM peers. To the extent that low-income Latino

Table 3
Change Across Cohorts, 1998 to 2010, for Tracts and Schools in
Which Sampled Native or
Foreign-Born Latina Mothers Reside (Means and SDs Reported)
1998 2010 Change Across Cohorta
Variables
Native-Born
Latino
Foreign-Born
Latino
Native-Born
Latino
Foreign-Born
Latino
Native-Born
Latino
Foreign-Born
Latino
Schools
Ethnicity and segregation
Percent enrollment, White 0.47
(0.31)
0.31

(0.30)
0.37
(0.30)
0.25
(0.27)
–0.10*
–1.98
–0.06
–1.48
Percent enrollment, Latino 0.37
(0.30)
0.53
(0.32)
0.45
(0.33)
0.58
(0.31)
0.08
1.52
0.05
1.06
Dissimilarity 0.49
(0.31)
0.55
(0.32)

0.55
(0.30)
0.56
(0.32)
0.06
0.77
0.01
0.22
Entropy 0.49
(0.20)
0.47
(0.24)
0.50
(0.24)
0.47
(0.24)
0.01
0.16
0.00
–0.02
Social class
Percent enrollment, eligible for subsidized
meals
0.35

(0.30)
0.49
(0.36)
0.49
(0.33)
0.66
(0.31)
0.14*
2.55
0.17*
2.5
Language
Percent enrollment, English learners 0.14
(0.22)
0.30
(0.29)
0.23
(0.26)
0.39
(0.29)
0.09*
2.02
0.09*
2.04

Tracts
Median household income ($) 58,677
(26,153)
54,558
(23,531)
57,006
(24,490)
49,581
(20,576)
–1,671
–0.47
–4,977†
–1.74
Percent population in poverty 15.82
(11.48)
19.29
(12.49)
17.95
(13.25)
21.92
(14.01)
2.13
0.99
2.63
1.23

Percent population with some college or more 46.31
(18.78)
38.55
(18.72)
51.61
(19.37)
44.62
(17.77)
5.30†
1.8
6.07*
2.47
Immigrant destinationsb
Traditional destinations 0.31
(0.46)
0.43
(0.50)
0.38
(0.49)
0.43
(0.50)
F(1.55, 834.95) F(1.61, 771.55)
New destinations 0.29

(0.45)
0.41
(0.49)
0.25
(0.44)
0.37
(0.48)
=0.53 =0.52
N of matched families 411 553 564 904
aCross-cohort difference in first rows and t-statistics in second
rows. Significant differences in t-tests for independent samples,
cross cohort.
bTest for independence between immigrant destination and
cohort is conducted. The Pearson χ2 statistic is corrected for
survey design and converted into an F statistic.
†p < .10. *p < .05.
OCTOBER 2019 415
families migrate into middle-class communities, this helps to
explain improving economic integration.
Discussion
A half century of research details the corrosive effects of
segregat-
ing certain groups in separate schools, distant from White or
middle-class peers (e.g., Cook, 1984; Johnson, 2019; Reardon

& Owens, 2014). Our results verify how levels of racial and
eco-
nomic segregation have been slow to move in recent decades for
young Latino children, with notable gains in exposure to mid-
dle-class (often fellow Latino) peers. At the moment these chil-
dren enter school, most face highly segregated settings,
especially
the offspring of immigrant parents.
Equity-minded reformers often assume they can tinker with
the curriculum, the niceties of testing, or performance
standards.
Yet racial segregation, as a deep-seated structural constraint,
mir-
rors disparities in school funding, access to quality teachers,
and
monistic forms of knowledge that remain insensitive to cultural
variety (Vasquez Heilig, Khalifa, & Tillman, 2014). Our results
confirm this deeply institutionalized and racially arranged
social
order.
A pair of contextual dynamics remain key: The share of ele-
mentary pupils of Latino heritage continues to grow in many
districts, both in cities and out in diversifying suburbs. This
means that rising percentages of children from low-income
fami-
lies populate the nation’s schools. Then, we find that Latino
students became more racially segregated over the period—less
likely to interact with White peers in the same schools—for dis-
tricts enrolling at least 10% Latino pupils. The nation’s 10
poor-
est districts, enrolling at least 50,000 students, already quite
racially segregated in 1998, backslid even further by 2010.

The textured child and family-level data show that local gains
in economic integration may be driven in part by rising educa-
tional attainment in neighborhoods that are increasingly settled
by young Latino families. Even as many neighborhoods popu-
lated by children of immigrants felt a sizeable decline in mean
household income during the recession, school attainment of
resident adults continued to climb. And our regression accounts
of variation in school segregation show that Latino kindergart-
ners enter less economically segregated schools when their par -
ents are better educated. We also saw how elementary schools
displayed a more even distribution among multiple racial groups
(entropy) over time. This widening pluralistic blend of popula-
tions may advance economic integration as well.
A less optimistic hypothesis stems from the fact that some
middle-class families in the recession’s wake, at times losing
their
homes, fell into poorer neighborhoods. The net worth of Latino
households fell from $23,600 to $13,700 (42%) between 2007
and 2013, compared with the decline for Whites, from $192,500
to $141,900 (26%; Kochhar & Fry, 2014). Rising economic
integration may have occurred ironically via the downward
mobility of Latino families. Future research is required to learn
whether upward mobility or suburban migration of second and
Table 4
Descriptive Statistics at the Mother and Family Level by
Ethnicity and Nativity Split by Cohort,
1998–2010 (Means and SDs Reported)
1998 2010
Change 1998 to
2010a

Variable All White
Native-
Born
Latino
Foreign-
Born
Latino All White
Native-
Born
Latino
Foreign-
Born
Latino
Native-
Born
Latino
Foreign-
Born
Latino
Social class
Yearly family income ($) 82,263
(77,738)

93,948
(81,687)
66,855
(51,201)
45,425
(54,309)
81,211
(68,618)
95,812
(69,165)
65,403
(60,450)
37,704
(41,236)
–1,452
–0.3
–7,721*
–2.13
Maternal education
Less than high school 0.11
(0.32)
0.06
(0.23)
0.18

(0.38)
0.47
(0.50)
0.11
(0.32)
0.04
(0.21)
0.15
(0.36)
0.46
(0.50)
–0.03
–0.64
–0.01
–0.21
High school diploma 0.31
(0.46)
0.29
(0.46)
0.38
(0.49)
0.29
(0.45)
0.20
(0.40)

0.17
(0.37)
0.27
(0.45)
0.29
(0.46)
–0.11**
–3.46
0.00
0.18
Some college 0.33
(0.47)
0.35
(0.48)
0.34
(0.47)
0.17
(0.38)
0.33
(0.47)
0.34
(0.47)
0.38
(0.48)

0.16
(0.36)
0.04
0.98
–0.01
–0.43
Four-year degree or more 0.25
(0.43)
0.30
(0.46)
0.10
(0.29)
0.08
(0.26)
0.36
(0.48)
0.44
(0.50)
0.20
(0.40)
0.09
(0.29)
0.10**
3.39

0.01
0.73
Language
Non-English home
language
0.09
(0.29)
0.01
(0.10)
0.12
(0.33)
0.76
(0.43)
0.13
(0.34)
0.01
(0.11)
0.10
(0.30)
0.78
(0.42)
–0.02
–0.89
0.02

0.67
Household structures and activity
Single-parent family 0.17
(0.38)
0.12
(0.33)
0.19
(0.40)
0.16
(0.37)
0.19
(0.40)
0.14
(0.35)
0.23
(0.42)
0.18
(0.38)
0.04
1.11
0.02
0.66
aCross-cohort difference in first rows and t-statistics in second
rows. Significant differences in t-tests for independent samples,
cross cohort.

*p < .05. **p < .01.
later-generation Latinos improves the economic integration of
young children.
It is encouraging that class-based integration widened for
elementary students, despite the recession, although this gain
was not observed in the nation’s 10 largest and poor districts.
The mean Latino child resided in a tract with higher educational
attainment in 2010, compared with the corresponding child in
1998. One explanation is that many Latino families exited tradi -
tional urban enclaves over the period. Other studies reveal how
attainment levels climbed for adult Latinos, independent of resi-
dential movement, especially for young women.12 The educa-
tional aspirations of many Latinos seem quite resilient, even
when residing in economically fragile communities.
Our findings mesh with other work showing a significant
postrecession recovery for native-born Latinos, along with sus-
tained upward mobility when compared with first-generation
Latinos (Tran & Valdez, 2015). Median income climbed for
Latino households nationwide from $46,046 in 2006, on the eve
of recession, to $50,486 in 2017 (9.6% gain in 2017 dollars).
This recovery for Whites moved from $63,892 to $68,145
(6.7% gain; U.S. Census Bureau, 2018b). Still, lower and unsta-
ble incomes have persisted for foreign-born Latino parents
(Gennetian, Rodrigues, Hill, & Morris, 2015).
Our fine-grain data on kindergartners detail a similar trend of
increasing segregation as Latino kindergartners enter school.
This remains troubling, as governments invest more heavily in

preschool, aiming to narrow disparities in school readiness. The
average Latino kindergartner entered a school with enrollments,
37% White in 1998, falling to 30% by 2010; the share of enroll -
ment, Latino, climbed from 46% to 53%. The percentage of
FRPM-eligible peers jumped from 43% to 59%, climbing more
than the increment tied to liberalized program eligibility. Future
research should build alternative measures of economic integra-
tion, as the federal definition of FRPM-eligible continues to
shift (Domina et al., 2018).
A pressing question remains of whether and how policy mak-
ers and education leaders can effectively reduce the segregation
of Latino students, independent of demographic and economic
Table 5
Estimating Child Composition, Racial and Class Exposure in
School From Family Socioeconomic Status (SES)
Covariates for Latinos Families With Cross-Cohort Interactions
(Unstandardized Coefficients and SEs Reported)
Variable Percent, Latino
Percent, Free or Reduced-Price
Meal (FRPM) Eligible Percent, English Learners
Yearly family incomea –.0011***
(.0002)
–.0013***
(.0002)
–.0006***
(.0002)
Maternal education

Some college –.0595
(.0329)
–.0804**
(.0303)
–.0307
(.0285)
Four-year degree or more –.0884
(.0629)
–.094*
(.0404)
–.0452
(.0444)
Non-English home language .1754***
(.0276)
.131***
(.0320)
.1644***
(.0263)
Single-parent .0069
(.0293)
–.0174
(.0373)
.0309
(.0288)

Year .065
(.0389)
.1856***
(.0381)
.1084**
(.0390)
Interaction with year
Yearly family income .0003
(.0003)
–.0001
(.0003)
–.0001
(.0002)
Maternal education
Some college .0304
(.0409)
–.0105
(.0371)
–.0205
(.0359)
Four-year degree or more .0078
(.0748)
–.1233*
(.0521)
–.0547

(.0530)
Non-English home language –.0468
(.0351)
–.0411
(.0378)
–.0158
(.0341)
Single-parent .0571
(.0370)
.0595
(.0423)
.0228
(.0360)
Constant .4151***
(.0280)
.4191***
(.0303)
.1674***
(.0316)
F for model F (11, 723) = 15.91 F (11, 723) = 24.48 F (11, 723)
= 17.40
R 2 .15 .23 .18
aFamily income was centered around $36,720, which is close to
the median of family income in year 1998 and 2010, and divided
by $1,000. Thus, a unit increase

corresponds to $1,000 increase in family income.
*p < .05. **p < .01. ***p < .001.
OCTOBER 2019 417
forces. These state and local actors face stiff headwinds: the
steady growth of Latino populations, including poor and immi -
grant families. And many Latino parents continue to exit tradi -
tional urban enclaves, migrating to aging suburbs and exurbs,
where the reception offered by educators and fellow residents
ranges from ill-prepared to downright hostile.
At the same time, an expanding Latino middle class is mov-
ing to economically better-off neighborhoods and schools that
are more integrated, at least along social-class lines. Future
research should further untangle such local variations in the
Latino experience and the extent to which racialized markers
continue to segregate Latino children in certain schools. The
interplay of demographic trends and educational policies—the
incursion of market-oriented reforms, for instance—offers
another ripe area of study (Fiel, 2015).
How do these trends inform contemporary policy efforts and
district-level strategies for lessening the corrosive effects of
segre-
gation? First, the independence of economic integration vis-à-
vis
racial integration offers encouraging news for Latino families in
some locales. We must learn more, however, as to whether mid-
dling Latino parents and children, in turn, benefit from higher
quality schools as they enter less segregated settings. Second,
the
fact that adult educational levels in predominantly Latino neigh-
borhoods continue to climb—despite the recession’s onset—

offers encouraging news as well.
Third, one hopes that upward mobility and school integration
benefit Latino families and young children when the economy
grows. Our findings confirm how children of native-born
parents
do enjoy more integrated schools and materially better-off
neigh-
borhood, compared with immigrant peers. But under what eco-
nomic or schooling conditions do young offspring of foreign-
born
mothers share in these gains? And education leaders—aiming to
serve increasingly diverse Latino children—must discern how
the
conditions of immigrant versus later-generation families can
dif-
fer dramatically, even when attending the same school.
Some education leaders have persevered in their efforts to
racially integrate students among schools within their districts,
for instance by expanding magnet or dual-language schools
(Riel, Parcel, Mickelson, & Smith, 2018). District-managed
choice efforts seek to balance parental preferences with the
com-
mon cause of racial integration, as in Cambridge or San
Francisco. Other district leaders, when direct integration efforts
fail, at least attempt to equalize the allocation of dollars or
qual-
ity teachers among racially segregated schools (Johnson, 2019;
Schwartz, Rubenstein, & Stiefel, 2009; Fuller & Lee, 2018).
Still, our findings highlight how differing fertility rates
among groups, out-migration from old urban enclaves, and
long-term progress in educational attainment will shape whether
Latino parents find better integrated schools in their neighbor -
hoods. Local educators and policy makers must candidly con-

front these deep-seated structural forces that shape varying
degrees of segregation, then look for institutional openings to
better integrate Latino children, widening their opportunities
along lines of race and social class.
ORCID ID
Yoonjeon Kim https://orcid.org/0000-0002-1214-3549
NOTES
This article stems from the Latino Contexts and Early
Development
Project, originally funded by the Packard and Spencer
foundations,
along with Berkeley’s Institute of Human Development. Mr.
Fuller
coordinated this study, and Ms. Kim led the quantitative
analysis. Ms.
Galindo codirects the project. Team members are listed
alphabetically.
Heartfelt thanks to Ann Owens and Sean Reardon for their
guidance
and to Elise Castillo, who compiled much of our data, along
with Gail
Mulligan at the National Center for Education Statistics for her
gra-
cious fielding of endless questions.
1Iceland and Nelson (2008) replicated Massey’s finding, while
showing how Puerto Rican and Black Latinos have not shared
the
upward mobility or integrated settings more commonly achieved
by
later-generation Latinos.

2A third position accents how Latinos increasingly raise their
chil-
dren in multiethnic suburbs or gentrifying urban centers with
Asian,
Black, and White neighbors (e.g., Bean et al., 2015).
3The Los Angeles School of suburban dispersal of families pio-
neered much of this work, in contrast to the Chicago School
(e.g., Soja,
2014). More recently, urban-ecological thinking has been
advanced by
students of Baltimore (Grove, Cadenasso, Pickett, Machlis, &
Burch,
2015).
4White and Sassler (2000) earlier showed how the class position
of Latino families, not surprisingly, predicts the economic and
demo-
graphic features of the neighborhoods in which they settle.
Younger
Latino families appear more likely to migrate to new
destinations, often
finding low-wage jobs (Donato, Tolbert, Nucci, & Kawano
2008).
5NCES defines elementary (or primary) schools as starting at
pre-K or kindergarten and not having grades beyond eighth.
Districts
solely hosting charter schools and high school districts were
excluded.
6Means are nationally representative for all and Latino children
when properly weighted. A nearly identical protocol was
followed
to collect data from families and schools for the tandem cohor ts
(G.

Mulligan, National Center for Education Statistics, personal
commu-
nication providing guidance on representativeness of Latino
subsam-
ples in ECLS-K for 1998 and 2010 cohorts, 2015; Rock &
Pollack,
2002).
7Sampled ECLS-K parents were not asked about nativity until
the
first-grade home visit, resulting in lost cases relative to the
kindergarten
sample.
8The family eligibility cut-point, 185% of the federal poverty
line,
remained constant over the period. Yet Washington moved to
liberal-
ize eligibility and the ease of certifying families (Food and
Nutrition
Service, 2009; Hoffman, 2012). Between 1998 and 2004, the
share
of children deemed eligible for FRPM climbed 3%, while the
child
poverty rate declined a like amount. FRPM eligibility rose from
38% to
48% nationwide, 2000–2010 (NCES, 2018).
9A linguistically isolated household hosts no member, 14 years
or
older, who speaks English fluently, as defined by the census.
10We estimated whether the mother’s Latino ethnicity, as
racialized
marker, further contributed to the intensity of segregated
schools, after

propensity-matching of Latino and White families on social-
class mark-
ers. Results available from the authors.
11These 10 include large urban districts such as Dallas,
Houston,
Los Angeles, Miami, Milwaukee, and San Diego.
12The share of Latina women, age 25–29, who attained a 4-year
college degree nationwide climbed from 66% to 74% between
1998
and 2010. These percentages equaled 60% to 66% for Latino
males
(U.S. Census Bureau, 2018a).
13For tract and neighborhood descriptives, sample weights
C1PW0 (1998) and W1P0 (2010) were used; and for school
descrip-
tives, weights C1CPTW0 (1998) and W1T0 (2010) were
applied. We
https://orcid.org/0000-0002-1214-3549
use stratum and PSU identifiers that correspond to sample
weights to
compute variance estimates based on Taylor series methods.
14Since families in a school possess the same value on the
depen-
dent variable, error terms may be correlated. To correct for this,
we ran
models with cluster-robust standard errors (Crowder & South,
2008).

Because Stata does not provide options for specifying a
stratification
variable under robust-cluster options, we specify sample
weights using
the pweight option.
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AUTHORS
BRUCE FULLER is a professor of education and public policy
at the
Graduate School of Education, University of California,
Berkeley, CA
94720; [email protected] He studies institutions, often the social
and political organization of schooling and processes that
contribute to
the early learning and socialization of Latino children.
YOONJEON KIM is a postdoctoral scholar in the Graduate
School of
Education at the University of California, Berkeley, Center for
the
Study of Child Care Employment, University of California,
Berkeley,
CA 94704; [email protected] Her research examines how macro-
institutional factors shape the social organization of schools and
learn-
ing in the United States and cross-nationally.
CLAUDIA GALINDO is an associate professor of educational
policy
in the College of Education at the University of Maryland,
College
Park, MD 20742; [email protected] Her work focuses on the

school
experiences and achievement of Latino students, and the role of
family
and community supports.
SHRUTI BATHIA is a PhD student in social science methods at
the
Graduate School of Education, University of California,
Berkeley, CA
94720; [email protected] Her research centers on applica-
tions of psychometrics and statistics to study human behavior.
MARGARET BRIDGES is a research scientist at the University
of
California, Berkeley Institute of Human Development,
Berkeley, CA
94720; [email protected] Her work focuses on how families and
preschool contribute to young children’s social-emotional and
cognitive
development.
GREG J. DUNCAN is a distinguished professor in the School of
Education at the University of California, Irvine, CA 92697;
gduncan
@uci.edu. His research focuses on economic mobility and the
effects of
poverty on children’s development.
ISABEL GARCÍA VALDIVIA is a PhD candidate in sociology
at the
University of California, Berkeley, Department of Sociology,
Berkeley,
CA 94720; [email protected] Her research centers on migra-
tion and inequalities faced by Latinx families, including
education and
legal status.

Manuscript received July 10, 2018
Revisions received October 22, 2018; January 8, 2019;
April 28, 2019; May 31, 2019
Accepted June 6, 2019
https://www.rsfjournal.org/doi/full/10.7758/RSF.2017.3.2.03
https://www.rsfjournal.org/doi/full/10.7758/RSF.2017.3.2.03
http://journals.sagepub.com/doi/pdf/10.1177/0038040717741180
http://journals.sagepub.com/doi/pdf/10.1177/0038040717741180
http://journals.sagepub.com/doi/full/10.1177/233285841665734
3
http://journals.sagepub.com/doi/full/10.1177/233285841665734
3
https://www.brookings.edu/podcast-episode/the-changing-
identity-of-americas-middle-class/
https://www.brookings.edu/podcast-episode/the-changing-
identity-of-americas-middle-class/
http://www.census.gov/acs/www/
https://www.census.gov/data/tables/time-
series/demo/educational-attainment/cps-historical-time-
series.html
series.html
series.html
https://www.census.gov/data/tables/2018/demo/income-
poverty/p60-263.html
https://www.census.gov/data/tables/2018/demo/income-
poverty/p60-263.html
mailto:[email protected]

Methods Appendix
Details on Segregation Indices
Interaction index. The interaction (or exposure) index (e.g.,
Latino children’s exposure to Whites) is specified as (Massey &
Denton, 1988; Owens, 2017; Reardon & Bischoff, 2011)
x y
*
i=1
n
P =
x
X
y
s
i i
i
⎡
⎣ ⎢

⎤
⎦ ⎥
⎡
⎣
⎢
⎤
⎦
⎥ ∑ ,
where xi, yi, and si are the counts of Latinos, Whites, and the
total student enrollment in elementary school i, respectively.
X is the total elementary school enrollment of Latinos in the
school district. The interaction index can be interpreted as
the probability that a randomly drawn Latino child goes to
the same school with a White child. Similarly, we calculated
free or reduced-price meal (FRPM)–eligible children’s expo-
sure to non-FRPM peers.
Racial diversity or entropy index. A school’s entropy (E) is
specified as
E Q log
Qrr
R
r
R=
=1
1∑ ,

where R is the number of racial and ethnic groups in each
school.
Qr is the proportion of racial or ethnic group r. School entropy,
which represents the extent of even distribution among the
groups within a school, varies from 0 (when the school contains
only a single group) to 1 (when the racial groups in the school
are evenly proportioned).
Estimating Levels of School Segregation
for Latino Kindergartners
All descriptive statistics are estimated using Stata 13 svy com-
mands specifying stratification, sampling units, and survey
weights.13 After descriptively breaking down differences in the
segregation indices by parental nativity, home language, and
other markers of social class, we estimate their independent
con-
tribution via ordinary least squares (OLS) regression. We
interact
a child-cohort dummy with social-class markers to see if their
contributions are increasing over time, in the form
Y = + Year + X + X Year +j 0 1 ij pij
2
p
pij pij
2
p
pij ij ijβ β β γ ε∑ ∑ .
Here, Yj is the attribute of school j. Dummy Yearij indicates

whether a child i in context j was sampled in 2010. X pij are
family-level attributes of child i in school j. Therefore, β0
represents the mean proportion of students, Latino or in
poverty
(FRPM) in 1998, and β1 represents the change, 1998–2010,
when all family background variables are equal to zero. βpij
indicates the slopes of family variables in 1998, and γpij
indicate
the change in the effects of class markers on school ethnic and
class composition (segregation) between 1998 and 2010.14
Running Head: PROJECT PROPOSAL FOR MICROSOFT
1
PROJECT PROPOSAL FOR MICROSOFT 4
Project Proposal for Microsoft
Shirish Bhatnagar
Colorado Technical University
Digital Forensics
Project Proposal for Microsoft

Digital forensic and incident response plan (DFIR) is a
significant component of an IT business. The philosophy is
supported by technological advancements to provide
comprehensive solutions for the security profession in IT. The
team seeks to offer secure coverage of the internal systems of a
corporation. The following is a DFIR plan for Microsoft
Corporation.
1. Preparation
This is the first phase of the plan and the most significant in
protecting the business. It will entail training the employees on
incident response roles and responsibilities. The training will be
adjusted in response to the data breach, where drills situations
will be developed (Watts, 2020). This process ensures that the
team will be are prepared adequately to minimize eras. Regular
mocks data breaches are critical in evaluating the response plan.
This phase will also examine the funding of the plan in advance.
The management of Microsoft is brought on board to ensure full
support and teamwork. Another significant factor that is
considered in this stage is the identification of the possible
areas of the breach.
Microsoft has crucial information that is protected and,
therefore, its plan will extend beyond the question of the breach
to establish an evaluation response. The internal response team
will guide the company in adhering to the violation of classified
information. It will include risks such as loss of devices,
wrongly sent emails, and information disclosure to a few
employees only. Among the internal team leaders will be the
wireless internet service provider manager, ICT manager,
human resource personnel, a legal officer, and a corporate
communication officer.
2. Containment
The second phase of the plan is containing the spread of a
breach when it occurs. It involves mitigating further damage to
the business. The step will include a procedure for
disconnecting all the affected devices from the internet. The
infected components may be deleted securely, although that will

likely damage the business in the long run. Valuable evidence
may be destroyed, which requires determining the source of the
breach and prevent its occurrence (Lord, 2018). Microsoft team
will have a redundant back-up system to curb this problem and
ensure business operations are restored at the shortest time
possible in case of a breach. The containment measure will
entail a review of remote access protocols, hardening all the
passwords, and changing administrative and user access. The
effort will include quarantine of all malware from the rest of the
environment, multi-factor authentication, and security patches.
3. Action Item Checklist
Microsoft is a multinational corporation with a broad scope of
operations. Its checklist will, therefore, prioritize the
spontaneous response to the slightest data breach. Some of the
components that will be included include:
· The time and date of the incident
· Activation and finalization of both the internal and external
response team towards the breach
· Identification of secure perimeter around the systems and
equipment are suspected to be breach targets
· Drawing the focus of the forensic team to secure the affected
systems
· Initiating the repair efforts while monitoring for incidents of
compromising
4. Eradication
This phase will entail eliminating the root cause of the breach.
All malware will be removed securely, and the system will be
patched and hardened (Lord, 2018). A complete update will then
follow. Valuable data may be lost, and the company's liability
increases if any trace of the malware remains in the system.
Therefore, all the efforts will be directed to re-image the system
and strengthen it than before the breach.
5. Recovery
This phase will be directed towards restoring and returning the
system to normalcy. All the affected devices will be returned to

the business environment of Microsoft after intensive cleaning.
This process will be initiated after establishing that the system
is secure and ready to be operational again.
References
Lord. N. (2018). Cybersecurity incident response planning:
Expert tips, steps, testing & more. Data Insider. Retrieved from
https://digitalguardian.com/blog/incident-response-plan
Watts, S. (2020). Digital forensics and incident response
(DFIR): An introduction. Retrieved from
https://www.bmc.com/blogs/dfir-digital-forensics-incident-
response/
Economic Policy Institute
Presentation | March 6, 2014
MODERN SEGREGATION
B Y R I C H A R D R O T H S T E I N
A presentation to the Atlantic Live Conference, Reinventing the
War on Poverty, March 6, 2014, Washington, D.C.
i.
Education Policy is Housing Policy
We cannot substantially improve the performance of the poorest

African American students – the “truly disadvantaged,”
in William Julius Wilson’s phrase – by school reform alone. It
must be addressed primarily by improving the social and
economic conditions that bring too many children to school
unprepared to take advantage of what schools have to offer.
The conclusion rests on two distinct analyses:
- First, social and economic disadvantage – not only poverty,
but a host of associated conditions – depresses student
performance, and
- Second, concentrating students with these disadvantages in
racially and economically homogenous schools depresses
it further.
The schools that the most disadvantaged black children attend
today are segregated because they are located in segre-
gated neighborhoods far distant from truly middle class
neighborhoods. We cannot desegregate schools without deseg-
regating these neighborhoods, and our ability to desegregate the
neighborhoods in which segregated schools are located
is hobbled by historical ignorance. Too quickly forgetting
twentieth century history, we’ve persuaded ourselves that the
residential isolation of low-income black children is only “de
facto,” the accident of economic circumstance, personal
preference, and private discrimination. But unless we re-learn

how residential segregation is “de jure,” resulting from
E CO N O M I C P O L I C Y I N S T I T U T E • 1 3 3 3 H
S T R E E T, N W • S U I T E 3 0 0 , E A S T TO W E R •
WA S H I N G TO N , D C 2 0 0 0 5 • 2 0 2 . 7 7 5 . 8 8 1 0 •
W W W. E P I . O R G
http://www.epi.org/people/richard-rothstein/
http://www.epi.org/
racially-motivated public policy, we have little hope of
remedying school segregation that flows from this neighborhood
racial isolation.
The individual predictors of low achievement are well
documented:
With less access to routine and preventive health care,
disadvantaged children have greater absenteeism, and they
can’t benefit from good schools if they are not present.
With less literate parents, they are read to less frequently when
young, and are exposed to less complex language at
home.
With less adequate housing, they rarely have quiet places to
study and may move more frequently, changing schools
and teachers.
With fewer opportunities for enriching after-school and summer
activities, their background knowledge and orga-

nizational skills are less developed.
With fewer family resources, their college ambitions are
constrained.
As these and many other disadvantages accumulate, lower social
class children inevitably have lower average achievement
than middle class children, even with the highest quality
instruction.
When a school’s proportion of students at risk of failure grows,
the consequences of disadvantage are exacerbated.
In schools with high proportions of disadvantaged children,
Remediation becomes the norm, and teachers have little time to
challenge those exceptional students who can over-
come personal, family, and community hardships that typically
interfere with learning.
In schools with high student mobility, teachers spend more time
repeating lessons for newcomers, and have fewer
opportunities to adapt instruction to students’ individual
strengths and weaknesses.
When classrooms fill with students who come to school less
ready to learn, teachers must focus more on discipline
and less on learning.
Children in impoverished neighborhoods are surrounded by
more crime and violence and suffer from greater stress

that interferes with learning.
Children with less exposure to mainstream society are less
familiar with the standard English that’s necessary for
their future success.
When few parents have strong educations themselves, schools
cannot benefit from parental pressure for higher qual-
ity curriculum,
Children have few college-educated role models to emulate, and
They have few classroom peers whose own families set higher
academic standards.
Nationwide, low-income black children’s isolation has
increased. It’s a problem not only of poverty but of race.
E C O N O M I C P O L I C Y I N S T I T U T E | M A R C H
6 , 2 0 1 4 PA G E 2
http://www.epi.org/
The share of black students attending schools that are more than
90 percent minority has grown in the last twenty
years from about 34 percent to about 40 percent.
Twenty years ago, black students typically attended schools in
which about 40 percent of their fellow students were
low-income; it is now about 60 percent.

In cities with the most struggling students, the isolation is even
more extreme. The most recent data show, for
example, that in Detroit, the typical black student attends a
school where 2 percent of students are white, and 85
percent are low income.
It is inconceivable that significant gains can be made in the
achievement of black children who are so severely isolated.
As I mentioned, this school segregation mostly reflects
neighborhood segregation. In urban areas, low-income white
students are more likely to be integrated into middle-class
neighborhoods and less likely to attend school predominantly
with other disadvantaged students. Although immigrant low-
income Hispanic students are also concentrated in schools,
by the third generation their families are more likely to settle in
more middle-class neighborhoods.
The racial segregation of schools has been intensifying because
the segregation of neighborhoods has been intensifying.
Analysis of Census data by Rutgers University Professor Paul
Jargowsky has found that in 2011, 7 percent of poor whites
lived in high poverty neighborhoods, where more than 40
percent of the residents are poor, up from 4 percent in 2000;
15 percent of poor Hispanics lived in such high poverty
neighborhoods in 2011, up from 14 percent in 2000; and a

breathtaking 23 percent of poor blacks lived in high poverty
neighborhoods in 2011, up from 19 percent in 2000.
In his 2013 book, Stuck in Place, the New York University
sociologist Patrick Sharkey defines a poor neighborhood as
one where 20 percent of the residents are poor, not 40 percent
as in Paul Jargowsky’s work. A 20-percent-poor neigh-
borhood is still severely disadvantaged. In such a neighborhood,
many, if not most other residents are likely to have very
low incomes, although not so low as to be below the official
poverty line.
Sharkey finds that young African Americans (from 13 to 28
years old) are now ten times as likely to live in poor neigh-
borhoods, defined in this way, as young whites—66 percent of
African Americans, compared to 6 percent of whites.
What’s more, for black families, mobility out of such
neighborhoods is much more limited than for whites. Sharkey
shows that 67 percent of African American families hailing
from the poorest quarter of neighborhoods a generation ago
continue to live in such neighborhoods today. But only 40
percent of white families who lived in the poorest quarter of
neighborhoods a generation ago still do so.
Considering all black families, 48 percent have lived in poor
neighborhoods over at least two generations, compared to
7 percent of white families. If a child grows up in a poor

neighborhood, moving up and out to a middle-class area is
typical for whites but an aberration for blacks. Black
neighborhood poverty is thus more multigenerational, while
white
neighborhood poverty is more episodic.
From the perspective of children, think of it this way: black
children in low-income neighborhoods are more likely to
have parents who also grew up in low-income neighborhoods
than white or Hispanic children in low-income neighbor-
hoods. The implications for children’s chances of success are
dramatic: Sharkey calculates that “living in poor neighbor-
hoods over two consecutive generations reduces children’s
cognitive skills by roughly eight or nine points … roughly
equivalent to missing two to four years of schooling.”
6 , 2 0 1 4 PA G E 3
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And Sharkey has a final finding in this regard that is most
startling of all: Children in poor neighborhoods whose moth-
ers grew up in middle-class neighborhoods score only slightly
below, on average, the average scores of children whose
families lived in middle-class neighborhoods for two
generations. But children who live in middle-class

neighborhoods
yet whose mothers grew up in poor neighborhoods score much
lower. Sharkey concludes that “the parent’s environment
during [her own] childhood may be more important than the
child’s own environment.”
Integrating disadvantaged black students into schools where
more privileged students predominate can narrow the
black-white achievement gap. But the conventional wisdom of
contemporary education policy notwithstanding, segre-
gated schools with poorly performing students cannot be
“turned around” while remaining racially isolated. And the
racial isolation of schools cannot be remedied without undoing
the racial isolation of the neighborhoods in which they
are located.
ii.
The Myth of De Facto Segregation
In 2007, the Supreme Court made integration more difficult
when it prohibited the Louisville and Seattle school dis-
tricts from making racial balance a factor in assigning students
to schools, in cases where applicant numbers exceeded
available seats.
The plurality opinion by Chief Justice John Roberts called
student categorization by race unconstitutional unless

designed to reverse effects of explicit rules that segregated
students by race. Desegregation efforts, he ruled, are imper -
missible if students are racially isolated, not as the result of
government policy but because of societal discrimination,
economic characteristics, or what Justice Clarence Thomas, in
his concurring opinion, termed “any number of innocent
private decisions, including voluntary housing choices.”
In Roberts’ terminology, commonly accepted by policymakers
from across the political spectrum, constitutionally for-
bidden segregation established by federal, state or local
government action is de jure, while racial isolation independent
of state action, as, in Roberts’ view, like that in Louisville and
Seattle, is de facto.
It is generally accepted today, even by sophisticated
policymakers, that black students’ racial isolation is now de
facto,
not only in Louisville and Seattle, but in all metropolitan areas,
North and South.
Even the liberal dissenters in the Louisville-Seattle case, led by
Justice Stephen Breyer, agreed with this characterization.
Breyer argued that school districts should be permitted
voluntarily to address de facto racial homogeneity, even if not
constitutionally required to do so. But he accepted that for the
most part, Louisville and Seattle schools were not segre-

gated by state action and thus not constitutionally required to
desegregate.
This is a dubious proposition. Certainly, Northern schools have
not been segregated by policies assigning blacks to some
schools and whites to others; they are segregated because their
neighborhoods are racially homogenous.
But neighborhoods did not get that way from “innocent private
decisions” or, as the late Justice Potter Stewart once put
it, from “unknown and perhaps unknowable factors such as in-
migration, birth rates, economic changes, or cumulative
acts of private racial fears.”
6 , 2 0 1 4 PA G E 4
http://www.epi.org/
In truth, residential segregation’s causes are both knowable and
known – twentieth century federal, state and local poli-
cies explicitly designed to separate the races and whose effects
endure today. In any meaningful sense, neighborhoods
and in consequence, schools, have been segregated de jure.
Massey and Denton’s American Apartheid is the title of one
book describing only a few of these many public policies.
The title is no exaggeration. The notion of de facto segregation

is a myth, although widely accepted in a national con-
sensus that wants to avoid confronting our racial history.
iii.
De Jure Residential Segregation by Federal, State, and Local
Government
The federal government led in the establishment and
maintenance of residential segregation in metropolitan areas.
From its New Deal inception and especially during and after
World War II, federally funded public housing was
explicitly racially segregated, both by federal and local
governments. Not only in the South, but in the Northeast,
Midwest, and West, projects were officially and publicly
designated either for whites or for blacks. Some projects
were “integrated” with separate buildings designated for whites
or for blacks. Later, as white families left the pro-
jects for the suburbs, public housing became overwhelmingly
black and in most cities was placed only in black
neighborhoods, explicitly so. This policy continued one
originating in the New Deal, when Harold Ickes, Presi-
dent Roosevelt’s first public housing director, established the
“neighborhood composition rule” that public housing
should not disturb the pre-existing racial composition of
neighborhoods where it was placed.

This was de jure segregation.
Once the housing shortage eased and material was freed for
post-World War II civilian purposes, the federal gov-
ernment subsidized relocation of whites to suburbs and
prohibited similar relocation of blacks. Again, this was not
implicit, not mere “disparate impact,” but racially explicit
policy. The Federal Housing and Veterans Administra-
tions recruited a nationwide cadre of mass-production builders
who constructed developments on the East Coast
like the Levittowns in Long Island, Pennsylvania, New Jersey,
and Delaware; on the West Coast like Lakeview and
Panorama City in the Los Angeles area, Westlake (Daly City) in
the San Francisco Bay Area, and several Seattle
suburbs developed by William and Bertha Boeing; and in
numerous other metropolises in between. These builders
received federal loan guarantees on explicit condition that no
sales be made to blacks and that each individual deed
include a prohibition on re-sales to blacks, or to what the FHA
described as an “incompatible racial element.”
In addition to guaranteeing construction loans taken out by mass
production suburban developers, the FHA, as a
matter of explicit policy, also refused to insure individual
mortgages for African Americans in white neighborhoods,

or even to whites in neighborhoods that the FHA considered
subject to possible integration in the future.
Although a 1948 Supreme Court ruling barred courts from
enforcing racial deed restrictions, the restrictions them-
selves were deemed lawful for another 30 years and the FHA
knowingly continued, until the Fair Housing Act was
6 , 2 0 1 4 PA G E 5
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passed in 1968, to finance developers who constructed suburban
developments that were closed to African-Ameri-
cans.
Bank regulators from the Federal Reserve, Comptroller of the
Currency, Office of Thrift Supervision, and other
agencies knowingly approved “redlining” policies by which
banks and savings institutions refused loans to black
families in white suburbs and even, in most cases, to black
families in black neighborhoods – leading to the deteri-
oration and ghettoization of those neighborhoods.

Although specific zoning rules assigning blacks to some
neighborhoods and whites to others were banned by the
Supreme Court in 1917, racial zoning in some cities was
enforced until the 1960s. The Court’s 1917 decision was
not based on equal protection but on the property rights of white
owners to sell to whomever they pleased. Several
large cities interpreted the ruling as inapplicable to their zoning
laws because their laws prohibited only residence
of blacks in white neighborhoods, not ownership. Some cities,
Miami the most conspicuous example, continued to
include racial zones in their master plans and issued
development permits accordingly, even though neighborhoods
themselves were not explicitly zoned for racial groups.
In other cities, following the 1917 Supreme Court decision,
mayors and other public officials took the lead in orga-
nizing homeowners associations for the purpose of enacting
racial deed restrictions. Baltimore is one example where
the mayor organized a municipal Committee on Segregation to
maintain racial zones without an explicit ordinance
that would violate the 1917 decision.

You may recall that in the 1980s, the Internal Revenue Service
revoked the tax-exemption of Bob Jones University
because it prohibited interracial dating. The IRS believed it was
constitutionally required to refuse a tax subsidy to
a university with racist practices. Yet the IRS never challenged
the pervasive use of tax-favoritism by universities,
churches, and other non-profit organizations and institutions to
enforce racial segregation. The IRS extended tax
exemptions not only to churches where such associations were
frequently based and whose clergy were their officers,
but to the associations themselves, although their racial
purposes were explicit and well-known.
This was de jure segregation
Churches were not alone in benefitting from unconstitutional
tax exemptions. Consider this example: Robert
Hutchins, known to educators for reforms elevating the liberal
arts in higher education, was president and chancel-
lor of the tax-exempt University of Chicago from 1929 to 1951.
He directed the University to sponsor neighbor-
hood associations to enforce racially restrictive deeds in its
nearby Hyde Park and Kenwood neighborhoods, and
employed the University’s legal department to evict black
families who moved nearby in defiance of his policy, all

while the University was subsidized by the federal government
by means of its tax-deductible and tax-exempt status.
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Urban renewal programs of the mid-twentieth century often had
similarly undisguised purposes: to force low-
income black residents away from universities, hospital
complexes, or business districts and into new ghettos. Relo-
cation to stable and integrated neighborhoods was not provided;
in most cases, housing quality for those whose
homes were razed was diminished by making public housing
high-rises or overcrowded ghettos the only relocation
option.
Where integrated or mostly-black neighborhoods were too close
to white communities or central business districts,
interstate highways were routed by federal and local officials to
raze those neighborhoods for the explicit purpose of
relocating black populations to more distant ghettos or of
creating barriers between white and black neighborhoods.

Euphemisms were thought less necessary then than today:
according to the director of the American Association
of State Highway Officials whose lobbying heavily influenced
the interstate program, “some city officials expressed
the view in the mid-1950′s that the urban Interstates would give
them a good opportunity to get rid of the local
‘niggertown.’”
State policy contributed in other ways.
Real estate is a highly regulated industry. State governments
require brokers to take courses in ethics and exams
to keep their licenses. State commissions suspend or even li ft
licenses for professional and personal infractions –
from mishandling escrow accounts to failing to pay personal
child support. But although real estate agents openly
enforced segregation, state authorities did not punish brokers
for racial discrimination, and rarely do so even today
when racial steering and discriminatory practices remain.
This misuse of regulatory authority was, and is, de jure
segregation.
Local officials have played roles as well.
Public police and prosecutorial power was used nationwide to
enforce racial boundaries. Illustrations are legion.

Growing Racial Segregation of Latino Children in U.S. Schools from 1998-2010

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