486289
research-article2013
EUSXXX10.1177/0013124513486289Education and Urban SocietyVasquez Heilig and Holme
Article
Nearly 50 Years PostJim Crow: Persisting
and Expansive School
Segregation for African
American, Latina/o, and
ELL Students in Texas
Education and Urban Society
XX(X) 1­–24
© The Author(s) 2013
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DOI: 10.1177/0013124513486289
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Julian Vasquez Heilig1 and
Jennifer Jellison Holme1
Abstract
This study addresses the segregation of English language learner (ELL)
students in schools across Texas. We descriptively analyze levels of racial,
economic, and linguistic isolation experienced by ELL students across the
state of Texas. We also examine the association between segregation by
race/ethnicity, economic disadvantage, and language proficiency with highstakes accountability ratings. Despite nearly two decades of accountability
policies that have promised equality, our statistical analyses show that a
majority of ELL students in Texas still attend high-poverty and high-minority
schools, and we find that segregation by socioeconomic status (SES) and
race and ethnicity is highly significant for predicting whether schools will be
low performing relative to high performing.
Keywords
English language learners, minority students, segregation, accountability
1The
University of Texas at Austin, Austin, TX, USA
Corresponding Author:
Jennifer Jellison Holme, PhD, Assistant Professor of Educational Policy and Planning,
Department of Education Administration, The University of Texas at Austin, George I.
Sanchez Building (SZB) 374D, 1 University Station D5400, Austin, TX 78712-0374, USA.
Email: [email protected]
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Education and Urban Society XX(X)
Although U.S. schools are more racially diverse than ever before, they are
growing increasingly segregated, with African American and Latina/o students attending more segregated schools than at any time in the past 20 years
(Orfield, 2009). Although current levels of school segregation are reminiscent
of the pre-Brown era, the demographics of students in U.S. schools have
shifted dramatically since that time. One of the most notable shifts has been
the growth of the English language learner (ELL) student population, a population that has more than doubled in the past 25 years, with high growth
expected to continue (National Center for Education Statistics [NCES], 2011).
Although the ELL population is growing, the extent to which such students are affected by segregation by race, poverty, and language proficiency
is not well understood. This study will first examine the segregation of ELL
students in schools across Texas, the state with the second largest population
of ELL students in the United States (NCES, 2010), by using school-level
data from the Public Education Information Management System (PEIMS)
data system. We will begin by considering how federal and state legal decisions and policies have directly and indirectly affected levels of school segregation for ELL students in the state. We then descriptively examine levels
of racial, economic, and linguistic isolation experienced by students across
the state of Texas. Finally, we conduct an inferential statistical analysis to
understand the association between segregation by race/ethnicity, economic
disadvantage, and language proficiency with high-stakes accountability
ratings.
Background
Texas school districts have a long history of using native language as a rationale for segregating students. In the following discussion, we first detail the
legal battles against segregation of ELL students into different school buildings, a type of isolation that has been termed “first-generation” segregation
(Mickleson, 2001). We then examine challenges to the assignment of ELL
students to separate classes within school, also known as “second generation”
segregation (Mickleson, 2001). We then focus our discussion and analysis on
the rise of a new type of segregation, which we call “third generation” segregation, which is the growing isolation of Latina/o students by race, language,
and poverty.
First-Generation Segregation
In Texas, the issues of native language and segregation have been closely
intertwined throughout the state’s history. Prior to Brown, many school
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Vasquez Heilig and Holme
3
districts segregated Mexican American students into separate schools, using
their home language as a rationale for such practices (Valencia, 2008), even
though the state constitution did not technically permit such segregation (as
it did for African Americans). The practices of segregating students increased
significantly as the state’s immigrant population from Mexico grew, especially in the 1920s (Valencia, 1991). By one estimate, by 1930, fully 90% of
the schools in Texas were segregated (Gonzales, 1990; Valencia, 1991). The
school segregation paralleled increasingly rigid residential segregation for
Mexican migrants (Valencia, 1991).
The first suit to challenge this type of first-generation segregation was the
case of Independent School District v. Salvatierra in 1930, which targeted
Del Rio ISD’s practice of segregating Mexican American students into separate schools (Salinas, 1971; Valencia, 2008). Del Rio ISD justified its segregation of Mexican Americans on the grounds that segregation better served
the needs of the children of migrant workers, even though Anglo migrant
children were not subject to the same practices (Salinas, 1971). The district
also argued that segregation was justifiable because the practice helped them
to better meet the needs of ELL students. Although the parents lost in the
lower court, the Texas State Court of Civil Appeals ruled that the district’s
existing practice of segregating Mexican American students was not permitted because “the rules for the separation are arbitrary [and] applied indiscriminately to all Mexican pupils . . . without apparent regard to their
individual aptitudes . . . while relieving children of other White races from
the operation of the rule” (Independent School District v. Salvatierra, 1930).
The court did, however, rule that the “children’s language deficiencies warranted their separate schooling” (Salinas, 1971, p. 15).
Although the judge in Salvatierra admonished districts against the
“indiscriminate” segregation of Mexican American students, many school
districts continued to segregate Latina/o students regardless of the “acceptable” rationale of language ability (Salinas, 1971). Such practices were
again challenged in Texas in the Delgado v. Bastrop ISD case, filed in
1948. The case was filed after the 1947 decision in Westminster v. Mendez,
in California, in which the Ninth Circuit Court of Appeals had ruled that
segregation of Mexican American students in California was illegal, not
because racial or ethnic segregation was illegal but because the California
“Jim Crow” statutes did not include Mexican Americans (Westminster v.
Mendez, 1947). Because the case was decided in the Ninth Circuit and
Texas was in the Fifth Circuit, the case had no bearing on Texas law
(Wilson, 2003). Lawyers in the Delgado case challenged the segregation
in Bastrop ISD on the same grounds (Salinas, 1971; Valencia, 2008;
Wilson, 2003). The court ruled in favor of the parents, deciding that while
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4
Education and Urban Society XX(X)
linguistic segregation was permissible, the “arbitrary” linguistic segregation as practiced by Bastrop ISD, in which all Mexican American students
were assumed to be ELLs and segregated into separate schools on that
presumption, was not. Segregation by language ability within schools,
however, was deemed permissible as long as the district used objective
standards (i.e., standardized tests or other assessments) to determine students’ levels of language proficiency before assigning students to separate
classes (Salinas, 1971; Wilson, 2003; Valencia, 1991). However, many
districts ignored the Delgado decision (Salinas, 1971; Wilson, 2003). As
Wilson (2003) noted, “Most districts either ignored the mandate, or set
standards that made it extremely easy for school administrators to prevent
any Mexican Americans from sharing public classrooms” (p. 9).
After these rulings, many districts also enacted policies to resist integration orders, by instituting “freedom of choice” plans where Mexican American
students were offered a “choice” between the formerly all Mexican school
and the district’s other-all White school(s). As Gonzales (1990) writes,
“Rarely did school districts exchange students as to integrate both schools.
Usually these districts achieved integration only if Mexican parents sent their
children to the old Anglo school” (p. 156). Little integration occurred through
these choice plans, and these evasive practices were eventually struck down
by the U.S. Supreme Court in Green v. New Kent County (1968).
It should be noted that the pre-Brown cases of Salvatierra and Delgado in
Texas, and the Mendez case in California rested on the peculiar legal status of
Latina/os, who were until that point considered legally “White”—or more
specifically belonged to an “other White” category. Lawyers challenging the
school segregation of Latina/os argued that because Latina/os were “other
White,” that state Jim Crow laws (which permitted African American segregation, as well as often the segregation of students of American Indian and
Asian descent) did not apply. Thus, the strategy of relying on the “other
White” category as a basis for challenging segregation of Latina/os, as
Valencia noted, came back to haunt the civil rights attorneys, as school boards
began to argue that because Latina/os were “White” they had no grounds for
a Fourteenth Amendment challenge:
Brown, the controlling authority in desegregation cases, could not be applied to
Mexican Americans, the argument went, because in the absence of state laws
allowing segregation, school boards could not be found culpable of intent, or de
jure segregation. Furthermore, given that the law considered Mexican Americans
as legally White, the CCISD (and other districts) desegregated their schools by
pairing African American and Mexican American plaintiffs needed to develop an
equal protection argument so as to be protected under Brown. (2008, p. 82)
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Vasquez Heilig and Holme
5
The practice of integrating Mexican Americans (“Whites”) with African
Americans for the purposes of desegregation, also found to occur in other
districts, including Houston ISD (Valencia, 2008) was challenged in a 1970
case in Texas in Cisneros v. Corpus Christi ISD. Plaintiffs in this case challenged the segregation of Mexican Americans in CCISD, arguing that the
Fourteenth Amendment of the U.S. Constitution did, in fact, apply to them.
The federal district court ruled that Mexican Americans were entitled to the
same Fourteenth Amendment protections extended by Brown (Cisneros v.
Corpus Christi ISD, 1970). As Salinas (1971) noted of the case, “Cisneros is
unique in that it is the first case in which a court officially recognized Mexican
Americans as an identifiable ethnic minority group for the purposes of public
school desegregation” (p. 3). The recognition of Latina/os as an identifiable
minority group for desegregation lawsuits was affirmed by the U.S. Supreme
Court in Keyes v. Denver School District No. 1, in 1973. In this case, the U.S.
Supreme Court reasoned that Chicanos were “in fact recognized as an identifiable minority group and thus entitled to special services in desegregated
settings” (Valencia, 1991, p. 39).
Second-Generation Segregation: Within-School Isolation for
ELLS
Although the first-generation cases helped to dismantle the dual systems
established by Texas for ELL students and Latina/o students, the issue of
within-school segregation has been thornier for ELL students who have
often been separated within schools into bilingual classrooms. As Valencia
(1991) observes, after first-generation segregation was resolved, “a new
form of school segregation began to emerge in American public schools—
that is, language segregation within desegregated schools, a new form of
resegregation” (p. 41).
One such form of segregation was the placement of students into “low
ability” classes: As Gonzales (1990) notes, after court victories, particularly
in the 1940s and 1950s, “schooling for Mexican children continued to come
under the significant influence of pseudo-scientific intelligence testing, with
its heavy tracking into slow learner, vocational, and EMR (educationally
mentally retarded) classes” (p. 156).
Another tension arose around the issue of bilingual education—as many
districts accused of segregating students on the basis of language were also
accused of failing to provide appropriate language instruction for students to
access the general curriculum (Vasquez Heilig, Dietz, & Volonnino, 2011).
As the first-generation cases were resolved, the friction between bilingual
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6
Education and Urban Society XX(X)
education and desegregation became more apparent, as courts and districts
sought to balance the need, on the one hand, to offer linguistically appropriate
instruction for subgroups of students who do not yet speak English, and the
danger, on the other hand, that such practices could result in racial and linguistic isolation of those students. As Gifford and Valdes (2006) write of the
tension between those advocating for desegregation and those advocating for
bilingual education,
For those concerned about segregation, bilingual education appeared to be a
language policy that masked exclusion. For those concerned about the futility of
educating students in a language that they did not understand, bilingual education
was a compensatory education policy that focused on language, the condition that
prevented students from accessing the curriculum. (p. 131)
Indeed, according to Valencia (1991), there were grounds for concern that
bilingual education was used to discriminate against ELL students, as “many
recalcitrant school systems circumvented the implementation of bilingual
education programs by scattering Limited English Proficiency (LEP) children throughout their districts; others used bilingual education as an opportunity to segregate Chicano LEP children, thus separating them from White
children” (p. 42).
Although courts began, in the 1970s, to recognize the rights of ELL students to integrated school settings, not all desegregation remedies addressed
their linguistic needs (Arias, 2007; Valencia, 1991). This was because, as
Arias (2007) notes, there was general wariness of any program that “might
entail an aspect of ‘separate but equal’” (para 9). As a result, whereas some
desegregation plans included exemptions for programs serving ELL students,
others pushed for integrating students into schools regardless of whether or
not there were programs available to meet their needs (Arias, 2007).
There has also been a concern around “tracking” of ELL students not only
into bilingual classes, but also into lower or remedial academic tracks that offer
little access to a college preparatory curriculum. Indeed, after many of the
desegregation cases for Latina/os were won, other cases were brought challenging the use of standardized testing that often placed non-English speakers
in classes for “educationally mentally retarded” students. Yet, as many scholars
have observed, ELL students often remain in “dead-end” academic tracks
(Suarez-Orozco, Suarez-Orozco, & Tordova, 2008). As Gandara and Orfield
(2010) wrote, “Linguistic segregation at the classroom level for much of the
day intensifies all the negative impacts of school segregation. For this reason,
it is especially crucial to organize instruction in ways that can mitigate, not
exacerbate, this segregation for students who are learning English” (p. 4).
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Vasquez Heilig and Holme
7
Third-Generation Resegregation: Demographic Shifts and
“Triple Segregation”
Struggles about how best to serve ELL students within integrated schools
have become, over the past several decades, less relevant, as demographic
shifts have left many ELLs concentrated into the same neighborhoods and the
same schools. According to an analysis by Orfield (2009), levels of school
segregation for Latina/os, who comprise 91% of the ELL student population
in Texas, have increased substantially over the past 30 years: In 2006-2007,
40% of Latina/o students attended “intensely segregated” schools, up from
approximately one third in 1988. Furthermore, the average Latina/o student
that year, attended a school that was 57% low income (Orfield, 2009).
This rise in school segregation for Latina/os, as Orfield (2009) observes,
reflects increases in residential segregation—as opposed to the termination of
court ordered school desegregation—because an increasing number of
Latina/os reside in suburban districts that were never under court ordered
integration plans. Overall, the percentage of minority students enrolled in
suburban schools has increased from 28% to 41% between 1993-1994 and
2006-2007 (Fry, 2009). The enrollment growth of Latina/os in suburban districts outpaced the growth of all other minority groups: The growth rate in
that 15-year period was 296% (Fry, 2009). In some metro areas, however, the
increase in minority population in the suburbs is much higher: In 2006-2007,
the percentage of Latina/o students enrolled in large suburban districts was
nearly equal to the percentage of White students in those same districts in the
25 largest Metropolitan Statistical Areas (Tefera, Frankenberg, SiegelHawley, & Chirichingo, 2011). Analyses of the Census 2010 found that 59%
of Latina/os now reside in suburban neighborhoods (Frey, 2011).
As the proportion of Latina/os has increased in suburban districts, they
have become increasingly isolated into the same schools (Fry, 2009; Reardon
& Yun, 2001). In 2006-2007, according to Fry, more than two thirds of nonWhite students in the suburbs attended a majority minority school, and such
schools educated more than 73% of suburban Latina/o students, as compared
with 68% of suburban Blacks, and just 13% of suburban Whites (Fry, 2009).
In 2006-2007, Tefera et al. (2011) found that “nearly 30 percent of African
American and Latina/o suburban students are in hyper-segregated suburban
schools with 0-10 percent White students” (p. 4).
As a subgroup of Latina/os, it is ELLs who are the most likely to experience high levels of school and residential segregation because they often live
in more segregated neighborhoods, and attend more segregated schools than
their U.S.-born peers (Iceland & Scopolliti, 2008; Suarez-Orozco et al.,
2008). In their study of immigrant students in Boston and San Francisco, for
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Education and Urban Society XX(X)
example, Suarez-Orozco et al. found that the Latina/o students in their sample (Dominicans, Central Americans, and Mexicans) were “much more likely
than either Haitians or Chinese students to attend ‘intensely’ segregated
schools where more than 90 percent of the students were of color” (p. 92).
Suarez-Orozco et al. (2008) term the uniquely high levels of school segregation experienced by ELLs as “triple segregation”—isolation by poverty,
color, and language. In their study, they found that intensely segregated
school settings provided a “separate and not equal educational environment”
for ELL students (p. 92). They found that schooling environments that students experienced—the level of segregation and poverty—were correlated
with students’ academic trajectories, with ELLs more likely to decline academically at the most segregated, high-poverty schools.
In the following section, we examine levels of school segregation by race
and ethnicity and for ELLs in Texas, a state with majority “minority” student
population and the second highest proportion of ELL students in the United
States (second to California) in 2009-2010 (Vasquez Heilig, 2011b). In 20072008, Texas served 13.2% of all ELL students in the United States (Batalova
& McHugh, 2010). In 2007-2008, the state served 775,000 ELL students in
pre-K-12, an increase of 40% since 2000 (Vasquez Heilig, Rodriguez, &
Somers, 2011). By 2011, ELLs comprised 17% of the state’s student population (Vasquez Heilig, 2011b). Little research, however, has examined the
extent to which ELL students are isolated by race, poverty status, or language
proficiency. As a result, the study seeks to ask the following questions: What
is the current state of segregation by race/ethnicity, SES, and ELL status in
the state of Texas? Are segregated majorities by race/ethnicity, SES, and ELL
status associated with high-stakes accountability ratings?
Method
Descriptive Analyses
The study begins by conducting descriptive analyses of publicly available
2011 school-level PEIMS data. The PEIMS was created in 1983 for the Texas
Education Agency (TEA) to provide a uniform accounting system to collect
all information about public education, including student demographics, academic performance, personnel, and school finances. The PEIMS lies at the
heart of the Texas student accountability system, and the wealth of information gathered from school districts offers the opportunity to examine segregation statewide.
We began by recoding PEIMS variables representing the school-level proportions of African American, Latina/o, economically disadvantaged, and ELL
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Vasquez Heilig and Holme
9
students in each school into dummy variables denoting school-level majority
and nonmajority for each demographic variable. We also created a variable by
combining the proportion of African Americans and Latina/os in each school to
denote which Texas schools were majority African American and Latina/o. A
locality variable (which we obtained directly from TEA) was matched to the
data set and then recoded into three localities (urban/central city, suburban, and
rural). A school-level variable (high school, middle, elementary, and multilevel) was also used. Descriptive cross-tab analyses were then undertaken
using SPSS to consider segregation by each of these variables.
Multivariate Logistic Regression
The second set of analyses examined the association between segregation of
students in Texas schools and TEA accountability ratings.1 We used the
school-level 2011 PEIMS data for all noncharter public schools that received
low performing or exemplary accountability ratings (N = 1599) in the state of
Texas to conduct a multivariate logistic regression. This method is based on
the logit transformation of the probability of achieving the exemplary
accountability rating relative to low performing based on a set independent
segregation variables. The basic logit model is
log (P / 1 − P) = α + ∑ βi χi
The following variables were included as independent variables in the multivariate logistic regression: race/ethnicity, economic disadvantage, locality,
ELLs, and school level.
Findings: Persisting Segregation in the State of
Texas
In the following analysis, we describe the level of segregation of ELL students in Texas. We illustrate that, consistent with national trends, ELL students are highly isolated in both urban and suburban schools. We further
illustrate that ELL students in Texas experiencing “triple segregation” by
race/ethnicity, language, and poverty.
Race and Ethnicity
Our first set of analyses of 2011 Texas education data examined racial isolation by examining the proportion of schools that had a simple majority (50%
or more) of any racial and ethnic group and schools that had a “vast majority”
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10
Education and Urban Society XX(X)
(90% or more) of any racial and ethnic group. We examined levels of segregation of almost 8,000 noncharter public schools in the state of Texas.
Overall, we found that most Texas schools have a majority of one racial or
ethnic group and that 43% of all schools in the state of Texas are majority
Latina/o/a; 34% are majority White, 17% have no racial or ethnic majority,
and 5% are majority African American (see Table 1). We found further that the
Texas schools that served a “vast majority” of a single racial/ethnic group
tended to be Latina/o/a: We found that 15.4% of schools in the state are “vast
majority” (90% or greater) Latina/o, whereas just 2% are vast majority White,
and 0.4% of schools are “vast majority” African American (results not shown).
Segregation differs, we found, by the grade level of schools, with Latina/
o/a students attending elementary schools in Texas experiencing the highest
levels of segregation. Because elementary schools tend to more closely track
patterns of residential segregation, this finding is consistent with the research
on growing levels of Latina/o/a residential segregation. Our analysis found
that 48% of elementary schools in Texas are majority Latina/o, whereas
17.5% of elementary schools in Texas are intensely segregated (90% or more)
Latina/o schools. Latina/os are also segregated to a slightly lower degree at
the middle school level: 39% of middle schools are majority Latina/o, with
13.8% being intensely segregated Latina/o/a schools (results not shown).
Levels of segregation are slightly lower for African Americans: 4% of elementary schools in the state are majority African American, and just 0.5% are
vast majority African American (results not shown).
Table 2 shows the demographics of public schools in Texas when African
American and Latina/o proportions are combined. As much as 51% of all
schools in Texas are majority African American and Latina/o. As a result, the
majority of schools in Texas are now “majority-minority.” As with the data
on majority one-race/ethnicity schools discussed previously, the highest levels of racial isolation in terms of “majority-minority” status are at the lower
grades: Our data show that 57% of elementary schools are majority nonWhite, and 55% of middle schools are majority non-White, compared with
38% of high schools and 19% of multilevel schools.
Analyzing the proportion of schools that are intensely segregated, serving
90% or greater populations of African Americans and Latina/os combined,
reveals similar patterns. Our analysis shows that nearly a quarter (24.1%) of
schools in Texas are intensely segregated (90% or greater African American/
Latina/o combined); 68% of these intensely segregated schools are elementary schools (30.1% of elementary schools overall, 23% of middle schools,
and 14% of high schools).
Our data also show that double segregation by race/ethnicity and economic disadvantage is still an issue in Texas (see Table 3). Of schools that are
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Elementary
Count
% within school level
% within majority R/E
% of total
Middle
Count
% within school level
% within majority R/E
% of total
High school
Count
% within school level
% within majority R/E
% of total
Multilevel
Count
% within school level
% within majority R/E
% of total
Total
Count
% within school level
% within majority R/E
% of total
2,070
48.10%
61.00%
26.40%
627
39.10%
18.50%
8.00%
586
36.80%
17.30%
7.50%
113
33.70%
3.30%
1.40%
3,396
43.40%
100.00%
43.40%
316
19.70%
23.40%
4.00%
249
15.60%
18.40%
3.20%
56
16.70%
4.10%
0.70%
1,353
17.30%
100.00%
17.30%
Majority
Latina/o
732
17.00%
54.10%
9.30%
No racial/
ethnic
majority
2,696
34.40%
100.00%
34.40%
147
43.90%
5.50%
1.90%
666
41.80%
24.70%
8.50%
585
36.50%
21.70%
7.50%
1,298
30.20%
48.10%
16.60%
Majority
White
364
4.60%
100.00%
4.60%
19
5.70%
5.20%
0.20%
87
5.50%
23.90%
1.10%
69
4.30%
19.00%
0.90%
189
4.40%
51.90%
2.40%
Majority
African
American
Table 1. Texas Public Schools by School Level and Majority Race/Ethnicity (R/E).
19
0.20%
100.00%
0.20%
0
0.00%
0.00%
0.00%
4
0.30%
21.10%
0.10%
3
0.20%
15.80%
0.00%
12
0.30%
63.20%
0.20%
Majority
Asian
American
3
0.00%
100.00%
0.00%
0
0.00%
0.00%
0.00%
1
0.10%
33.30%
0.00%
2
0.10%
66.70%
0.00%
0
0.00%
0.00%
0.00%
Majority
Native
American
7,831
100.00%
100.00%
100.00%
335
100.00%
4.30%
4.30%
1,593
100.00%
20.30%
20.30%
1,602
100.00%
20.50%
20.50%
4,301
100.00%
54.90%
54.90%
Total
12
Education and Urban Society XX(X)
Table 2. Texas Public Schools by Level and Majority African American (AA) and
Latina/o.
Elementary
Count
% within school level
% within majority AA & Latina/o
% of total
Middle
Count
% within school level
% within majority AA & Latina/o
% of total
High school
Count
% within school level
% within majority AA & Latina/o
% of total
Multilevel
Count
% within school level
% within majority AA & Latina/o
% of total
Total
Count
% within school level
% within majority AA & Latina/o
% of total
Not majority
AA and
Latina/o
Majority
AA and
Latina/o
Total
1,835
42.70%
48.10%
23.40%
2,466
57.30%
61.40%
31.50%
4,301
100.00%
54.90%
54.90%
723
45.10%
18.90%
9.20%
879
54.90%
21.90%
11.20%
1,602
100.00%
20.50%
20.50%
985
61.80%
25.80%
12.60%
608
38.20%
15.10%
7.80%
1,593
100.00%
20.30%
20.30%
273
81.50%
7.20%
3.50%
62
18.50%
1.50%
0.80%
335
100.00%
4.30%
4.30%
3,816
48.70%
100.00%
48.70%
4,015
51.30%
100.00%
51.30%
7,831
100.00%
100.00%
100.00%
majority economically disadvantaged in the state of Texas, 93% (3,857) of
them are also majority African American and Latina/o, whereas 45% are
intensely segregated—90% or greater African American and Latina/o (results
not shown). The stark difference in the socioeconomic status (SES) demographics of Texas schools that African Americans and Latina/os attend is
readily apparent.
We next examined segregation by race/ethnicity and locality. In urban and
central city areas, the vast majority of schools were majority Latina/o (63%)
followed by no racial or ethnic majority (16%), majority White (14%) and
majority African American (8%). Consistent with data on suburban
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Vasquez Heilig and Holme
Table 3. Doubly Segregated: Texas Public Schools by Majority African American
(AA) and Latina/o and Majority Economically Disadvantaged (ED).
Not majority ED
Count
% within AA & Latina/o
% within majority ED
% of total
Majority ED
Count
% within AA & Latina/o
% within majority ED
% of total
Total
Count
% within AA & Latina/o
% within majority ED
% of total
Not majority
AA and
Latina/o
Majority
American and
Latina/o
Total
3,506
95.70%
91.90%
44.80%
158
4.30%
3.90%
2.00%
3,664
100.00%
46.80%
46.80%
310
7.40%
8.10%
4.00%
3,857
92.60%
96.10%
49.30%
4,167
100.00%
53.20%
53.20%
3,816
48.70%
100.00%
48.70%
4,015
51.30%
100.00%
51.30%
7,831
100.00%
100.00%
100.00%
diversification, it appears that there are high levels of diversity in suburban
districts in Texas as well as high levels of school segregation. Our data show
that suburban districts also had the largest proportion of majority Latina/o
schools at 38%, with majority White schools close behind at 34%. In suburban areas, about 23% of schools had no racial or ethnic majority whereas
about 4% were majority African American. In rural areas, 55% of schools
were still majority White, 31% were majority Latina/o, 20% had no racial or
ethnic majority and 3% were majority African American (see Table 4).
Table 5 shows the demographics of public schools by locality in Texas
when African American and Latina/o proportions are combined. As noted
above, 51% of all schools in Texas are now majority African Americana and
Latina/o. Our data show high levels of segregation in urban core districts:
Driven by rapid growth in the Latina/o population, in urban and central city
areas in Texas, 72% of schools are majority African American and Latina/o
combined; with 46% of urban schools being “intensely segregated” (90% or
more African American and Latina/o/a student population combined).
We also find high concentrations of non-Whites in suburban districts. In
suburban districts, 47% of schools are also now majority African American
and Latina/o, with one fifth (20.2%) of suburban schools being “intensely
segregated” (90% or greater African American and Latina/o/a combined).
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Education and Urban Society XX(X)
Table 4. All Texas Public Schools by Locality and Majority Race/Ethnicity (R/E).
No racial/
Majority Majority Majority
ethnic Majority Majority African
Asian
Native
majority Latina/o White American American American
Urban/central city
Count
% within locality
% within majority
R/E
% of total
Suburban
Count
% within locality
% within majority
R/E
% of total
Rural/Ind. town
Count
% within locality
% within majority
R/E
% of total
Total
Count
% within locality
% within majority
R/E
% of total
Total
364
15.50%
26.90%
1,477
62.80%
43.50%
317
13.50%
11.80%
190
8.10%
52.20%
4
0.20%
21.10%
4.60%
18.90%
4.00%
2.40%
0.10%
708
23.20%
52.30%
1,168
38.30%
34.40%
1,041
34.20%
38.60%
113
3.70%
31.00%
15
0.50%
78.90%
9.00%
14.90%
13.30%
1.40%
0.20%
0.00%
281
11.60%
20.80%
751
30.90%
22.10%
1,338
55.00%
49.60%
61
2.50%
16.80%
0
0.00%
0.00%
0
2,431
0.00% 100.00%
0.00% 31.00%
3.60%
9.60%
17.10%
0.80%
0.00%
0.00%
1,353
3,396
2,696
17.30% 43.40% 34.40%
100.00% 100.00% 100.00%
17.30%
43.40%
34.40%
364
19
4.60%
0.20%
100.00% 100.00%
4.60%
0.20%
0
2,352
0.00% 100.00%
0.00% 30.00%
0.00%
30.00%
3
3,048
0.10% 100.00%
100.00% 38.90%
38.90%
31.00%
3
7,831
0.00% 100.00%
100.00% 100.00%
0.00% 100.00%
Historically, Whites in Texas have been the majority in rural areas overall
across the state, but as of 2011, 36% of schools in rural areas are now majority African American and Latina/o.
ELLs
As stated previously, descriptive statistical analyses of the segregation of
ELLs in schools in the state of Texas to date have been rare. Table 6 shows
that about 9% of all schools in Texas are majority ELL. Examining the segregation of ELLs by grade levels, we find that the vast majority of schools
(645) in the state of Texas that are majority ELLs are elementary—about 8%
of all schools in Texas. There are very few schools in the state at the middle
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Vasquez Heilig and Holme
Table 5. All Texas Public Schools by Locality and Majority African American (AA)
and Latina/o.
Not majority
AA and
Latina/o
Urban/central city
Count
% within locality
% within majority AA & Latina/o
% of total
Suburban
Count
% within locality
% within majority AA & Latina/o
% of total
Rural/Ind. town
Count
% within locality
% within majority AA & Latina/o
% of total
Total
Count
% within locality
% within majority AA & Latina/o
% of total
Majority AA
and Latina/o
Total
653
27.80%
17.10%
8.30%
1,699
72.20%
42.30%
21.70%
2,352
100.00%
30.00%
30.00%
1,602
52.60%
42.00%
20.50%
1,446
47.40%
36.00%
18.50%
3,048
100.00%
38.90%
38.90%
1,561
64.20%
40.90%
19.90%
870
35.80%
21.70%
11.10%
2,431
100.00%
31.00%
31.00%
3,816
48.70%
100.00%
48.70%
4,015
51.30%
100.00%
51.30%
7,831
100.00%
100.00%
100.00%
(16), high school levels (11), and multilevel (3) that are majority ELL. This is
because many ELL students are reclassified by the end of elementary school
(Gandara & Rumberger, 2009). In Texas in 2011-2012, the proportion of students classified as LEP fell from 28% to 16% between first and fifth grade, to
8% by eighth grade (Texas Education Agency, 2012). Nevertheless, although
they are not the majority in middle and high school, considering that almost
17% of all students in the state of Texas are ELLs (Vasquez Heilig, 2011b),
the next question is whether majority-ELL schools are dispersed broadly by
locality if not by school level.
Table 7 shows ELL segregation by locality, and the findings illustrate that
most (55%) of the schools with a majority of ELL students are located in
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Education and Urban Society XX(X)
Table 6. Texas Public Schools by School Level and Majority English Language
Learner (ELL).
Elementary
Count
% within school level
% within majority ELL
% of total
Middle
Count
% within school level
% within majority ELL
% of total
High school
Count
% within school level
% within majority ELL
% of total
Multilevel
Count
% within school level
% within majority ELL
% of total
Total
Count
% within school level
% within majority ELL
% of total
Not majority ELL
Majority ELL
Total
3,656
85.00%
51.10%
46.70%
645
15.00%
95.60%
8.20%
4,301
100.00%
54.90%
54.90%
1,586
99.00%
22.20%
20.30%
16
1.00%
2.40%
0.20%
1,602
100.00%
20.50%
20.50%
1,582
99.30%
22.10%
20.20%
11
0.70%
1.60%
0.10%
1,593
100.00%
20.30%
20.30%
332
99.10%
4.60%
4.20%
3
0.90%
0.40%
0.00%
335
100.00%
4.30%
4.30%
7,156
91.40%
100.00%
91.40%
675
8.60%
100.00%
8.60%
7,831
100.00%
100.00%
100.00%
urban and central city districts (representing 16% of all urban schools),
whereas a significant proportion (38%) are in suburban areas (representing
8% of suburban schools) and 6% are located in rural areas (representing 2%
of rural schools overall).
We also find that ELL students tend to experience double segregation by
language proficiency and poverty. We find specifically that 7% of all schools
in the state of Texas are majority ELL and majority economically disadvantaged. We found that 15% of all schools that are majority economically disadvantaged are also majority ELL. Of majority-ELL schools, we found that
89% of them are also majority economically disadvantaged (see Table 8).
Notably, we find that two thirds (66%) of the schools that are intensely
poor—“vast majority” economically disadvantaged—are also majority ELL
(results not shown).
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Vasquez Heilig and Holme
Table 7. Texas Public Schools by Locality and Majority English Language
Learner (ELL).
Not majority ELL
Urban/central city
Count
% within locality
% within majority ELL
% of total
Suburban
Count
% within locality
% within majority ELL
% of total
Rural/Ind. town
Count
% within locality
% within majority ELL
% of total
Total
Count
% within locality
% within majority ELL
% of total
Majority ELL
Total
1,975
84.00%
27.60%
25.20%
377
16.00%
55.90%
4.80%
2,352
100.00%
30.00%
30.00%
2,788
91.50%
39.00%
35.60%
260
8.50%
38.50%
3.30%
3,048
100.00%
38.90%
38.90%
2,393
98.40%
33.40%
30.60%
38
1.60%
5.60%
0.50%
2,431
100.00%
31.00%
31.00%
7,156
91.40%
100.00%
91.40%
675
8.60%
100.00%
8.60%
7,831
100.00%
100.00%
100.00%
Table 8. Doubly Segregated: Texas Public Schools by Majority English Language
Learner (ELL) and Majority Economically Disadvantaged (ED).
Not majority ELL
Not majority ED
Count
% within majority ED
% within majority ELL
% of total
Majority ED
Count
% within majority ED
% within majority ELL
% of total
Total
Count
% within majority ED
% within majority ELL
% of total
Majority ELL
Total
3,592
98.00%
50.20%
45.90%
72
2.00%
10.70%
0.90%
3,664
100.00%
46.80%
46.80%
3,564
85.50%
49.80%
45.50%
603
14.50%
89.30%
7.70%
4,167
100.00%
53.20%
53.20%
7,156
91.40%
100.00%
91.40%
675
8.60%
100.00%
8.60%
7,831
100.00%
100.00%
100.00%
We also find that ELLs experience “double” segregation by language proficiency and race. Table 9 shows that 8% of all schools in Texas are majority
African American and ELL. Of schools that are majority African American
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Education and Urban Society XX(X)
Table 9. Doubly Segregated: Texas Public Schools by Majority English Language
Learner (ELL) and Majority African American (AA) and Latina/o.
Not majority ELL
Not majority AA & Latina/o
Count
% within majority AA & Latina/o
% within majority ELL
% of total
Majority AA & Latina/o
Count
% within majority AA & Latina/o
% within majority ELL
% of total
Total
Count
% within majority AA & Latina/o
% within majority ELL
% of total
Majority ELL
Total
3,744
98.10%
52.30%
47.80%
72
1.90%
10.70%
0.90%
3,816
100.00%
48.70%
48.70%
3,412
85.00%
47.70%
43.60%
603
15.00%
89.30%
7.70%
4,015
100.00%
51.30%
51.30%
7,156
91.40%
100.00%
91.40%
675
8.60%
100.00%
8.60%
7,831
100.00%
100.00%
100.00%
and Latina/o, 15% are majority ELL. Of those schools that are majority ELL,
89% of them are also majority African American and Latina/o, and a striking
81% of vast majority African American and Latina/o (90% or greater) schools
are also majority-ELL schools (results not shown).
Our data also illustrates the problem of “triple segregation” for ELL students in Texas. Table 10 shows that about 15% of all schools in the state are
triple segregated by majority ELL, majority economically disadvantaged and
majority African American and Latina/o. Although triple segregation is negligible in middle schools (1.2%) and high schools (0%), about 24% of Texas
elementary schools are triply segregated with majorities of African American
and Latina/o, economically disadvantaged, and ELL students.
Inferential Statistical Analyses: Association Between Segregation
and School Success
From Table 11 it can be seen that all of the school-level demographic variables
considered in the descriptive cross-tab analysis are highly significant predictors
of whether a school will be exemplary. Elementary schools were the referent
group and are the most likely to be exemplary in Texas. Other schools levels are
significantly less so as middle schools show a 91% (–2.454 log odds = e.086;
Table 11), high schools a 95% (–2.983 log odds = e.051; Table 11) and multilevel
schools also show a 76% (–1.413 log odds = e.243; Table 11) decrease in the odds
of being exemplary relative to elementary schools. Both majority economically
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19
Vasquez Heilig and Holme
Table 10. Triply Segregated Texas Public Schools: Majority Economically
Disadvantaged, Majority African American and Latina/o, and Majority English
Language Learner (ELL) by School Level.
Not majority ELL
Elementary
Count
% within school level
% within majority ELL
% of total
Middle
Count
% within school level
% within majority ELL
% of total
High school
Count
% within school level
% within majority ELL
% of total
Multilevel
Count
% within school level
% within majority ELL
% of total
Total
Count
% within school level
% within majority ELL
% of total
Majority ELL
Total
1,852
75.70%
56.90%
48.00%
593
24.30%
98.30%
15.40%
2,445
100.00%
63.40%
63.40%
836
98.80%
25.70%
21.70%
10
1.20%
1.70%
0.30%
846
100.00%
21.90%
21.90%
504
100.00%
15.50%
13.10%
0
0.00%
0.00%
0.00%
504
100.00%
13.10%
13.10%
62
100.00%
1.90%
1.60%
0
0.00%
0.00%
0.00%
62
100.00%
1.60%
1.60%
3,254
84.40%
100.00%
84.40%
603
15.60%
100.00%
15.60%
3,857
100.00%
100.00%
100.00%
disadvantaged (–1.645 log odds = e.193; Table 11) and African American and
Latina/o (–1.008 log odds = e.365; Table 11) schools exhibit decreases in the
odds (81% and 64%, respectively) for being exemplary relative to low performing. Locality is also a significant predictor of being exemplary as rural schools
odds are 87% (2.048 log odds = e.129; Table 11) less likely to be exemplary relative to urban schools with aforementioned demographics held constant.
In our analysis, we also examined the association between ELL segregation and school performance as measured by the likelihood of being rated
“exemplary” by the state in 2011. Table 12 examines whether triple segregation of ELLs in majority African American and Latina/o and economically
disadvantaged schools can predict whether schools will be exemplary relative to low performing. The odds ratios for economically disadvantaged
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20
Education and Urban Society XX(X)
Table 11. Logistic Regression Analysis of Race/Ethnicity School Segregation and
Exemplary Accountability Rating.
Predictor
Elementary
Middle
High
Multilevel
Majority economically
disadvantaged
Majority African
American and Latina/o
Urban/central city
Suburban
Rural
Constant
β
SE β
Wald’s χ2
df
Significant
eβ
–2.454
–2.983
–1.413
–1.645
.200
.222
.443
.322
258.485
149.816
180.033
10.149
26.036
3
1
1
1
1
.000
.000
.000
.001
.000
0.086
0.051
0.243
0.193
–1.008
.331
9.258
1
.002
0.365
0.227
–2.048
4.208
.198
.216
.249
130.905
1.319
89.687
285.425
2
1
1
1
.000
.251
.000
.000
1.255
0.129
67.207
Model goodness of fit: Nagelkerke pseudo R2 = .587.
Table 12. Logistic Regression Analysis of English Language Learner (ELL) School
Segregation and Exemplary Accountability Rating.
Predictor
Majority economically
disadvantaged
Majority African
American and
Latina/o
Majority ELL
Constant
β
SE β
Wald’s χ2
df
Significant
eβ
–1.610
.261
38.183
1
.000
0.200
–0.662
.255
6.746
1
.009
0.516
1.417
2.248
.282
.119
25.340
354.809
1
1
.000
.000
4.125
9.473
Note: Model goodness of fit: Nagelkerke pseudo R2 = .258.
schools are associated with an 80% (1.610 log odds = e.200; Table 12)
decrease in the odds of being exemplary. In triple segregated schools, majority African American and Latina/o schools are 48% (.662 log odds = e.516;
Table 12) less likely to be exemplary. Surprisingly, controlling for triple
segregation, majority-ELL schools are 1.5 times (2.248 log odds = e.4.125;
Table 12) more likely to be exemplary. However, as noted in the descriptive
analyses there are very few ELL majority middle and high schools. As a
result, this positive coefficient is due to the fact that there were 72 exemplary and 15 low performing majority-ELL elementary schools in the state
of Texas (results not shown). The state should be applauded for these numbers. However, there were no exemplary majority-ELL middle schools (0 of 2)
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Vasquez Heilig and Holme
21
and there were no majority-ELL high schools that were rated exemplary or
low performing in 2011.
Discussion and Conclusion
Our analyses of Texas data indicate that ELL students in Texas experience
high levels of segregation in schools by race, poverty, and language status.
The reasons for the growing segregation are less clear, and merit further
research; but there are a number of potential causes indicated within the literature. One such cause indicated within the research literature is the growing
residential segregation by race, language proficiency, and poverty—segregation that has increasingly been found, as our data show, in suburban school
systems. It is also possible that educational policies contribute to high levels
of triple segregation as well. Some policies that have been adopted with the
intent of improving language acquisition, as in the past, have the effect of
increasing linguistic isolation: for example, research has found that school
systems that are racially diverse often adopt “clustered bilingual” programs
in an effort to best serve the linguistic needs of ELL students. As in the past,
a linguistic rationale used by school districts in terms of meeting the needs of
ELL has the effect (intentionally or unintentionally) of increasing isolation of
ELL students and reducing exposure to native speakers during the school day.
Another policy that can have the indirect effect of worsening ELL segregation is school choice: Many school districts in the state of Texas have
adopted “open enrollment” policies that allow students to transfer between
schools within the same district. These policies, as research has shown, tend
to advantage more well-resourced students (particularly because transportation is not provided with most such policies). Due to differences in cultural
and social capital, it is likely that students whose home language is not
English are less likely to take advantage of choice (Vasquez Heilig, 2011a)
due to lack of familiarity with the application process.
One of the most significant contributions to segregation in schools, however,
is housing. ELL students, who are often Latina/o, are increasingly residentially
isolated in urban and, increasingly, suburban neighborhoods. As Gandara and
Contreras (2009) observed, “Housing segregation has particularly onerous
effects on Latina/o students learning English. When students’ lack appropriate
language models and individuals with whom to interact in English, their acquisition of academic English is delayed” (p. 74). This lack of opportunity is exacerbated when students residing in high-poverty and linguistically isolated
neighborhoods attend schools isolated by race/ethnicity, poverty, and language.
In conclusion, nearly 50 years since Jim Crow, the intensity of segregation
in Texas schools is still largely problematic. Our statistical analyses show that
a majority of ELL students in Texas attend high-poverty and high-minority
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Education and Urban Society XX(X)
schools. One positive note is that elementary schools serving ELL students
are more likely to be high performing than low performing schools. However,
this finding is tempered by the fact that as ELL students progress in the education pipeline in Texas, they are more likely to attend low performing middle schools and high schools (results not shown). Furthermore, ELLs enrolled
in secondary schools ultimately have the highest dropout rates and lowest
tests scores and graduation rates in Texas (Vasquez Heilig, 2011a).
Surprisingly, after almost two decades of Texas-style accountability, the
overall finding that segregation by SES and race and ethnicity is still highly
significant for predicting whether schools will be low performing relative to
high performing suggests that high-stakes testing and accountability as systemic reforms have still not delivered as a cure-all in Texas.
Authors’ Note
Both authors contributed equally to the content of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Note
1.
There are four typical accountability ratings for traditional public schools in Texas:
exemplary, recognized, acceptable, and low performing. This analysis focuses specifically on the highest and lowest ratings in the system. For more information
on the complex formulas used to calculate the ratings in the Texas accountability
system see http://www.tea.state.tx.us/perfreport/account/2011/manual/
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Author Biographies
Julian Vasquez Heilig is an award-winning researcher and teacher. He is currently an
associate professor of Educational Policy and Planning and African and African
Diaspora Studies (by courtesy) at the University of Texas at Austin. His primary work
considers equity and social justice in relation to various educational policies. He blogs
at Cloaking Inequity.
Jennifer Jellison Holme is an assistant professor of educational policy and planning
in the Department of Educational Administration at the University of Texas at Austin.
Her research examines the politics and implementation of educational policy, with a
particular interest in the relationship among school reform, equity, and diversity in
schools.
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