Special education was borne out of, and owes a debt to, the civil
rights movement. That is, the inspiration for, and the strategies used
by, advocates whose efforts resulted in the first national special
education legislation emerged from the struggles of the civil rights
movement (Smith & Kozleski, 2005). Concerns about racial inequity
were central to litigation (e.g., Mills v. Board of Education, 1972)
that led to the promulgation of the first special education legislation
(Individuals With Disabilities Education Act, IDEA, Public Law No.
94-142, 1975). Thus, it is highly ironic that racial disparities in
rates of special education service remain one of the key indicators of
inequity in our nation's educational system.
The disproportionate representation of minority students is among
the most critical and enduring problems in the field of special
education. Despite court challenges (Larry P. v. Riles,
1972/1974/1979/1984; PASE v. Hannan, 1980); federal reports (Donovan
& Cross, 2002; Heller, Holtzman, & Messick, 1982); and abundant
research on the issue (e.g., Chinn & Hughes, 1987; Harry &
Klingner, 2006; Hosp & Reschly, 2003; Losen & Orfield, 2002;
Oswald, Coutinho, Best, & Singh, 1999), the problem of
disproportionate representation of minority students in special
education has persisted. Indeed, although consistently documented, it is
fair to say that the full complexity of minority disproportionality has
not yet been understood, nor has a clear or comprehensive picture
emerged concerning the causes of disproportionality (Donovan &
Cross; Harry & Klingner). To address the issue of disproportionate
minority placement, the 1997 reanthorization of the Individuals With
Disabilities Education Act (IDEA 97, Public Law No. 105-17) stressed the
importance of efforts to "prevent the intensification of problems
connected with mislabeling and high dropout rates among minority
children with disabilities" (p. 5) and that effort has been further
amplified in the Individuals With Disabilities Education Improvement Act
(IDEA 2004, Public Law No. 108-446).
This article provides a status report on minority
disproportionality in special education. What is the historical context
for current problems of racial/ethnic disparity? What are the current
levels of disproportionality and how are those measured? What are the
possible causes and conditions that create or maintain
disproportionality? What interventions have been suggested? Finally, the
history and current status of the field suggests that any comprehensive
strategy for addressing disproportionality must attend to three aspects
of the issue: (a) examination of current data, (b) comprehensive
hypothesis formulation and interpretation, and (c) culturally responsive
intervention and evaluation.
HISTORY: A BRIEF SYNOPSIS OF A VERY OLD PROBLEM
The initial identification of the problem of disproportionate
representation of some groups, most notably African American students,
in special education is often traced back to Dunn's (1968) classic
critique of the field. Yet the problem itself has its roots far deeper,
in the problems of oppression and discrimination that have characterized
race relations throughout American history (Smedley, 2007). In 1853,
Margaret Douglas was sentenced to 1 month in jail for her attempts to
teach the children of freed slaves to read and write (Blaustein &
Zangrando, 1968). In 1896, Plessy v. Ferguson legitimated the doctrine
of separate but equal, even though segregated education in the Jim Crow
period was by no means equal (Jackson & Weidman, 2006). In the late
19th century and early 20th century, attacks on Black communities during
race riots included the burning of Black schools (Harmer, 2001). Early
20th century mental testing was grounded in the premise of American
eugenics that races other than those of northern European stock were
intellectually inferior, and that the purity of the superior races
should be preserved by vigorously segregating the
"feeble-minded" (Terman, 1916). From Reconstruction until the
1950s, the dominant view of African American education was that it was
intended not to educate for equal citizenship, but rather for the lower
ranked positions that it was assumed African Americans would occupy
It is not surprising then that leaders in the emerging field of
special education documented racially-based disparities in service in
the 1960s and 1970s. In his classic critique of special education, Dunn
(1968) suggested that the overrepresentation of ethnic and language
minority students in self-contained special education classrooms raised
significant civil rights and educational concerns. Mercer (1973),
highlighting ethnic differences in rates of special education service as
part of her critique of the "6-hour" or situationally retarded
child, found that public schools tended to identify more children as
mentally retarded than any other child service setting.
In the wake of Brown v. Board of Education (1954) and legislative
action to provide equal access to education, institutional structures,
such as ability grouping and significantly separate special education
classrooms, continued to keep minority students segregated from their
White peers (Losen & Welner, 2001). Addressing violations of the
Equal Protection Clause of the Constitution and Title VI of the Civil
Rights Act of 1964, de facto segregation was challenged in the
Washington, DC public school system in the case of Hobson v. Hansen
(1967). Continued challenges were brought in court under Title VI of the
Civil Rights Act of 1964, the Rehabilitation Act of 1973, and the
Education for All Handicapped Children Act of 1975, addressing the role
of standardized testing and the reduced educational opportunity afforded
by the racial isolation of minorities in special education programs
(Diana v. California State Board of Education, 1970; Guadalupe
Organization v. Temple Elementary School District #3, 1972; Larry P. v.
Riles, 1972/1974/1979/1984; PASE v. Hannon, 1980). Although the earliest
of these cases were highly influential in the generation of state and
federal statutes establishing special education in the early to
mid-1970s, the outcomes of the cases were by no means uniform (Bersoff,
1981; Reschly, 1996). Nevertheless, concerns about bias in testing led
to a profusion of research in the 1970s and early 1980s examining that
In the 1980s, examination of the U.S. Department of Education
Office for Civil Rights survey data began to produce estimates of the
extent and distribution of disproportionality, which have been
consistent over time (Chinn & Hughes, 1987; Donovan & Cross,
2002; Finn, 1982). Yet this research did not, in and of itself, provide
any understanding of the mechanisms that contribute to racial and ethnic
disparities in special education. Recent disproportionatity research has
seen a sharper focus on the forces that shape and maintain
disproportionate representation (e.g., Artiles, 2003; Harry &
Klingner, 2006; Hosp & Reschly, 2003; Skiba et al., 2006a).
Policy pressure to remediate disproportionality in special
education at the state and local levels increased significantly with the
inclusion of provisions concerning disproportionality in IDEA 1997 and
especially with the expansion of provisions in the reauthorization of
IDEA in 2004 (see Figure 1). Under the provisions of IDEA 2004, states
must monitor disproportionate representation by race or ethnicity in
disability categories and special education placements and require the
review of local policies, practices, and procedures when
disproportionate representation is found. One of the most significant
new requirements under IDEA 2004 is that local educational agencies
(LEAs) determined to have significant disproportionality must devote the
maximum amount of Part B funds allowable (15%) to early intervening
programs. Early intervening services are distinguished from early
intervention services for infants and toddlers with disabilities in that
they identify and target "children who are struggling to learn ...
and quickly intervening to provide support" (Williams, 2007, p.
28). Significant disproportionality is not defined in IDEA 2004 nor its
implementing regulations, and discretion is left to the states to
develop the quantifiable indicators of disproportionality used for
MEASUREMENT ISSUES IN DISPROPORTIONALITY
Disproportionality may be defined as the representation of a group
in a category that exceeds our expectations for that group, or differs
substantially from the representation of others in that category.
Although concerns have historically tended to focus on issues of
overrepresentation in special education or specific disability
categories, groups may also be underrepresented in a category or setting
(e.g., underrepresentation in general education settings, gifted
education, or visual impairment). Although the concept of
disproportionate representation seems relatively straightforward,
measurement of disproportionality can be quite complex. In measuring
disproportionality, one may assess (a) the extent to which a group is
over- or underrepresented in a category compared to its proportion in
the broader population (composition index) or (b) the extent to which a
group is found eligible for service at a rate differing from that of
other groups (risk index and risk ratio).
The most intuitive method of measurement of disproportionality, the
composition index (CI; Donovan & Cross, 2002), compares the
proportion of those served in special education represented by a given
ethnic group with the proportion that group represents in the population
or in school enrollment; that is, it provides a measure of
representation in the target phenomenon compared to our expectations for
that group. At the national level, African American students account for
33% of students identified as mentally retarded, clearly discrepant from
their representation in the school-age population of 17% (Donovan &
Although the CI is a clear cut measure, there are some difficulties
with its use. First, there is no criterion for determining when a
discrepancy in composition indices is meaningful or significant
(Coutinho & Oswald, 2004). Chinn and Hughes (1987) suggested setting
a confidence level of 10% around the population enrollment percentage of
the group in question (e.g., for an overall African American enrollment
of 17%, disproportionality would be expressed by special education
enrollment rates outside of a range of 17% +/- 1.7%, that is, 15.3% to
18.7%). The CI is also beset by scaling problems: discrepancies at the
extremes of the scale may not have the same meaning as those in the
middle. Finally, the CI diminishes in usefulness as groups become more
homogeneous (Westat, 2003, 2005). In several urban settings, African
American enrollment exceeds 92%, making it impossible to find
overrepresentation (e.g., 92% + 9.2% = 101.2% using Chinn &
RISK INDEX AND RELATIVE RISK RATIO
An alternative approach to describing disproportionality is to
measure a group's representation in special education compared to
other groups. The risk index (RI) is the proportion of a given group
served in a given category and represents the best estimate of the risk
for that outcome for that group. Donovan and Cross (2002) reported, for
example, that, at the national level, 2.64% of all African American
students enrolled in the public schools are identified as having mental
retardation (MR). By itself, however, the RI is not particularly
meaningful. In order to interpret the RI, a ratio of the risk of the
target group to one or more groups may be constructed, termed a risk
ratio (RR; Hosp & Reschly, 2003; Parrish, 2002). A ratio of 1.0
indicates exact proportionality, whereas ratios above or below 1.0
indicate over-and underrepresentation, respectively. Comparing African
American risk for MR identification (2.64%) with the risk index of 1.18%
of White students for that disability category yields a risk ratio of
2.24 (2.64/1.18), suggesting that African Americans are more than two
times more likely to be served in the category mental retardation than
White students. The same data can also be used to compute an odds ratio,
representing both the probability of being in special education and the
probability of not being in special education for both groups (Finn,
1982). In contrast to the RR, the odds ratios assess both occurrence and
There are also limitations and issues of interpretation with the
RR. Although less sensitive to changes in relative proportions of
population, the RR may become unstable with small n's (Hosp &
Reschly, 2004). Risk ratios may also provide an incomplete picture of
racial and ethnic disparities; although both 30% of Blacks versus 15% of
Whites in a category will provide the same RR (2.0) as 2% of Blacks and
1% of Whites in that category, the meaning of those discrepancies varies
greatly. Finally, there is no consensus in the field on the appropriate
group against which to compare a target group's RI. A case can be
made that, being the largest and historically dominant group, White
enrollment represents the appropriate criterion against which to compare
other racial/ethnic group representation and may be a more appropriate
measure for assessing Latino disproportionality. Using White as the
index group precludes the calculation of a RR for that group, however,
making estimation of White underrepresentation in special education
impossible (Westat, 2004). The U.S. Department of Education, Office of
Special Education Programs recommends using all others as the
denominator in the calculation of disproportionality (Westat, 2005), but
the use of either Whites and All Others as the index group appears to be
acceptable in the research literature (Skiba, Poloni-Staudinger,
Simmons, Feggins, & Chung, 2005).
In order to aid states in the reporting of disproportionality data,
the U.S. Department of Education, Office of Special Education Programs
and Westat convened a national panel to consider methodologies for
monitoring disproportionality. The guidance developed as a result of
that panel (a) recommends the use of a RR approach to measure
disproportionality; (b) provides instruction on the calculation of those
measures; and (c) recommends an alternative "weighted" RR when
there are fewer than 10 students from a target group in a given school
district, or to compare RRs across districts (Westat, 2004, 2005).
Again, absolute criteria for significant disproportionality are left
Although there has been progress in recent years in standardizing
the measurement of disproportionality, significant areas of confusion
remain. Although different measures such as RRs and odds ratios are
sometimes equated or confused in the literature (see e.g., Donovan &
Cross, 2002), they provide similar data only under certain conditions
(Davies, Crombie, & Tavakoli, 1998). Further, the issue of a
definitive criteria in determining disproportionality is complex. The
framers of IDEA 2004 may have deliberately intended to avoid cutoffs
identifying significant disproportionality in order to allow
responsiveness to regional and local variation; rigidly defined criteria
might also encourage local districts to meet those criteria by simply
cutting minority referrals. Yet, the absence of criteria for defining
significant disproportionality may perpetuate confusion by failing to
provide sufficient guidance to those at the state and local level who
may be unfamiliar with statistical analysis.
STATUS OF DISPROPORTIONALITY
PATTERNS OF DISPROPORTIONALITY
Analyses of data from the U.S. Department of Education, Office for
Civil Rights (OCR; e.g., Chinn & Hughes, 1987; Donovan & Cross,
2002; Finn, 1982) have revealed consistent patterns of
disproportionality. African American students are typically found to be
overrepresented in overall special education service and in the
categories of mental retardation (MR) and emotional disturbance (ED),
whereas American Indian/Alaska Native students have been overrepresented
in the category of learning disabilities (LD). Data from the 26th Annual
Report to Congress on the Implementation of the Individuals With
Disabilities Education Act (U.S. Department of Education, 2006; see
Table 1) indicates that American Indian/Alaska Native students received
services under the category developmental delay at a higher rate than
other groups, Asian/Pacific Islander students received special education
for hearing impairments and autism at a somewhat higher rate than other
students, and Latino students were somewhat more likely to receive
services in the category of hearing impairment. Parrish (2002) reported
that African American students are the most overrepresented group in
special education programs in nearly every state.
A number of characteristics of disproportionality have been noted.
Disproportionate representation is greater in the judgmental or
"soft" disability categories of MR, ED, or LD than in the
nonjudgmental or "hard" disability categories, such as hearing
impairment, visual impairment, or orthopedic impairment (Donovan &
Cross, 2002; Parrish, 2002). Parrish reported that rates of
overrepresentation tend to increase as a minority group constitutes a
relatively high percentage of their states' population. Finn (1982)
reported a complex relationship between school district size and
percentage of minority enrollment--for smaller districts,
disproportionality was greatest in districts with the highest minority
enrollment, whereas for larger districts (30,000 or more students),
disproportionality was greatest when minority enrollment was 30% or
less. Finally, states may show evidence of disproportionality in
categories that appear proportionate at the national level, and local
school districts may show evidence of disproportionality in a category
not disproportionate at the state level (Harry & Klingner, 2006).
In contrast to the relative stability of African American
disproportionality over time, there have been inconsistencies in
estimates of the degree and direction of Latino disproportionality. Some
state- and district-based studies, primarily based on data from
California or New York, have tended to show Latino overrepresentation in
special education (Artiles, Rueda, Salazar & Higareda, 2002; Wright
& Santa Cruz, 1983). National data, however, show that the most
common finding is the underrepresentation of Latino students in overall
special education service and in most disability categories (Chinn &
Hughes, 1987; National Center on Culturally Responsive Educational
Systems, NCCRESt, 2006). Examination of Table 1 suggests Hispanic
overrepresentation in Hearing Impairments and perhaps LD;
underrepresentation is a much more common finding across a number of
Discrepancies between findings of overrepresentation for African
American students and underrepresentation for Latino students may be due
in part to the tendency for overrepresentation to become more pronounced
as minority students represent a larger proportion of the population. In
contrast to the case of African American students, where
overrepresentation in certain categories has been found to be relatively
consistent across time and locale, overrepresentation of Latino students
appears to be concentrated in those areas in which Latino students
represent a relatively higher proportion of enrollment (Parrish, 2002).
Formal studies to evaluate these discrepancies have been limited
(Klingner, Artiles, & Mendez Barletta, 2006). The difficulty in
accurately distinguishing between language acquisition difficulties for
English Language Learners and a language disability also complicates
identification and assessment issues for Latino students (Barrera, 2006;
DISPROPORTIONALITY IN EDUCATIONAL SETTINGS
Although less well researched, available data demonstrates that
students of color, especially African Americans, are overrepresented in
more restrictive educational environments and underrepresented in less
restrictive settings (Fierros & Conroy, 2002; Skiba,
Poloni-Staudinger, Gallini, Simmons, & Feggins-Azziz, 2006b). Given
the conceptual importance of inclusion and the dramatic increases in
recent years in general education placements for students with
disabilities (McLeskey, Henry, & Axelrod, 1999), it could be argued
that disproportionality with respect to access to less restrictive
educational environments may be more important conceptually than
disparities in disability category (Skiba et al., 2006b).
Different interpretations might well be applied to findings of
racial disparities in educational settings. It might be presumed, for
example, that "differences in placement by race/ethnicity may
reflect the disproportional representation of some minority groups in
disability categories that are predominately served in more restrictive
settings" (U.S. Department of Education, 2002, p. III-45). Yet
failure to find such a pattern may suggest that disproportionality in
special education settings is driven, to some extent, by systemic
responses, such as educators who may mistake cultural differences for
cognitive or behavioral disabilities (Harry, 2008; Oswald et al., 1999;
Trent, Kea, & Oh, 2008).
To test that hypothesis, Skiba et al. (2006b) explored the extent
to which African American students were proportionately placed in more
and less restrictive settings within five disability categories in one
state's data for a single year. In four of the five disability
categories, African American children were more likely than their peers
with the same disability to be overrepresented in more restrictive
settings, or underrepresented in the general education setting. Further,
disproportionality in placement increased as the severity of the
disability decreased: African American students with disabilities were
much more likely than peers with the same disability label to be served
in a separate class setting in milder, more judgmental categories such
as learning disabilities (RR = 3.20) or speech and language (RR = 7.66).
Such results do not support the hypothesis that minority
disproportionality in educational environments is simply a function of
disproportionality in disability category. That is, the overuse of more
restrictive placements for African American students with disabilities
is likely due to factors other than severity of disability; further
research is critically needed to identify what those factors might be.
CAUSES OF DISPROPORTIONATE SPECIAL EDUCATION REPRESENTATION
A fairly extensive database has consistently documented African
American disproportionality in special education service and across
educational environments, although findings regarding Latino
disproportionality are less extensive and less consistent. Describing
the extent of the problem is merely the first step in understanding the
causes and conditions that create and maintain racial disparities in
special education. A number of possible conditions or causes related to
special education disproportionality have been explored, beginning in
the 1970s with test bias.
PSYCHOMETRIC TEST BIAS
In the 1970s, the issue of psychometric test bias played a central
role in court cases concerning minority disproportionality, specifically
overrepresentation. These cases appeared to be based on the presumption
that tests that yielded group racial differences in results must, of
necessity, be biased (Mercer, 1973). Although the presiding judge in
Larry P. v. Riles (1972/1974/1979/1984) appeared to agree with this
assessment, other courts failed to find evidence that bias in assessment
has yielded misclassification (Bersoff, 1981). The possibility of bias
against minorities in standardized tests of intelligence and achievement
was examined fairly extensively in the 1970s and 1980s, although there
has been less research on the topic in recent years (Valencia &
Suzuki, 2000), focusing mainly on the impact of high-stakes testing
(Madaus & Clarke, 2001). Extensive reviews of that literature have
reached somewhat different conclusions.
Perhaps the most influential review of cultural bias in
psychometric tests was conducted by Jensen (1980). That review and
others (Brown, Reynolds, & Whitaker, 1999; Cole, 1981) concluded
that data from a number of converging sources indicates little or no
evidence of bias against minority students in intelligence tests. First,
a similar factor structure for intelligence tests for Black and White
students suggests that the major constructs underlying those tests are
comparable across ethnic groups (Brown et al.). Second, although it has
been argued that undersampling of minority populations will lead to
tests that are biased against minority populations (Harrington, 1975),
tests of the hypotheses with human samples have not yielded such results
(Hickman & Reynolds, 1987). Finally, comparisons of African American
and White performance on a wide range of tests have generally failed to
find a significant bias at the item level (Brown et al.). For these
reasons, it has been argued that the case against test bias has been
conclusively made (Jensen) and some have expressed frustration about the
failure of the field to fully accept such findings (Reynolds, 2000).
Other equally extensive reviews of the same literature have not
always reached the same conclusions, however. Valencia and Suzuki (2000)
noted that, because the majority of studies on test bias were conducted
in the 1970s and 1980s, almost all of what we know regarding test bias
is based on the WISC and WISC-R intelligence tests, neither of which is
currently in use. Further, the literature on test bias has
underrepresented students in special education and some minority groups.
Nor are the results of available research entirely consistent. Of 32
investigations of content and predictive bias reviewed by Valencia and
Suzuki, 50% yielded findings concerning bias that were at least mixed;
in the area of predictive validity, 6 out of 18 investigations
(involving primarily Mexican Americans, but also African Americans and
Asian Americans) showed evidence for bias in predictive validity.
In particular, recent research has pointed to possible sources of
item bias. Shepard (1987), arguing that analysis at the individual item
level may be insufficient for exploring test bias, suggested that more
sophisticated methodologies, such as item response theory, have yielded
patterns of bias that explain a small but significant portion of the
variance in Black-White test score discrepancies. In particular,
concerns have been raised in regard to item selection processes on
commercially available standardized tests that may be weighted
differentially against minority test takers (Freedle, 2003; Kidder &
Rosner, 2002). Examining the test construction process for the SAT,
Kidder and Rosner found that questions more frequently answered
correctly by African American students than White students are rejected
at a higher frequency for inclusion, because such items do not correlate
with a total score that is higher for White than Black test takers.
Further research is necessary to determine to what extent such processes
may apply in the construction of standardized tests of intelligence or
achievement used in special education assessment.
Finally, language differences and examiner effects may also
contribute to bias in testing. Abedi (2004) demonstrated that tests
normed for native English speakers have lower reliability and validity
for English Language Learners and noted that tests standardized on
native English speakers may inadvertently function as English language
proficiency tests. The examiner may also represent a source of bias. In
a meta analysis of the effects of examiner familiarity on test
performance, Fuchs and Fuchs (1986) reported that examiner
unfamiliarity, defined in part as membership in a different group from
the examinee, had a significant impact on standardized test performance.
In particular, the examinees of low socioeconomic status (SES) were more
significantly affected than examinees of higher SES.
An extensive literature exploring psychometric test bias has, in
general, tended not to identify a level of cultural bias in standardized
tests of intelligence sufficient to account for the inappropriate
classification of students as disabled. Yet, given the failure to
include relevant populations in some areas of study, a literature base
that is, for the most part, more than 20 years old, and inconsistent
evidence in certain areas (e.g., item bias, examiner bias), the
assertion that test bias has been conclusively ruled out as a possible
source of minority disproportionality in special education is at best
Even a demonstration that standardized tests of cognition were
completely free of psychometric bias would not in and of itself identify
the source of the Black-White test score gap; in particular, findings
that tests are unbiased does not mean that racial differences in IQ
scores are inherent or genetic. Tests that are technically unbiased may
still provide an index that is essentially still unfair to certain
groups if interpreted uncritically. Wide and consistent disparities have
been identified in the quantity and quality of educational resources
available to White and African American students in American education
(Donovan & Cross, 2002; Kozol, 2005). While depressed minority test
scores are an indicator of current performance, they are also a product
that accurately reflects the impact of economic and educational
disadvantage. Tests that are unbiased may provide an accurate estimate
of current individual aptitude; yet they also provide an unbiased and
accurate record of the effects of unequal educational opportunity.
Indeed, at this point in history, tests that failed to reflect some form
of disadvantage for victims of racial or socioeconomic bias might be
said to lack concurrent and predictive validity with respect to the
conditions of bias present in our educational and social systems (Skiba,
Bush & Knesting, 2002).
SOCIO-DEMOGRAPHIC FACTORS: THE INFLUENCE OF POVERTY
A second factor that might contribute to a disproportionate rate of
representation in special education among students of color are
sociodemographic factors associated with economic disadvantage. One
might expect that because minority students are more likely to be
exposed to poverty in American society (U.S. Census Bureau, 2001), the
risk factors associated with poverty will result in increased academic
underachievement and emotional/behavioral problems among minority
students, thus increasing the risk of minority referral to special
A number of demographic factors related to geographical location
and SES have been shown to be associated with student educational
achievement or early cognitive development. These include neighborhood
and housing stability (Ainsworth, 2002); the student's home
environment (Caldas & Bankston, 1999); family health care (Kramer,
Allen, & Gergen, 1995); and geographic location (Huebner, 1985).
McLloyd (1998) reported that the effects of poverty on early cognitive
development, school achievement, and socio-emotional functioning are
dependent on the duration, timing, and neighborhood context of poverty;
deep and persistent poverty consistently predicts more deleterious
effects. The 2002 National Research Council panel exploring
disproportionality in special education (Donovan & Cross, 2002)
affirmed that biological and social/environmental factors that
disproportionately affect minority students have been found to
contribute to poor cognitive and behavioral outcomes, and they
recommended a national commitment to early intervention to offset
socioeconomic risk factors.
The consistent overlap of race and poverty in this country has led
some to suggest that race is simply a "proxy" for poverty
(Hodgkinson, 1995). MacMillan and Reschly (1998) argued that the
correlation of ethnicity and social class suggests that class may
explain more variance than race in predicting service in high-incidence
disabilities. That view is also widely shared among school personnel
(see e.g., Harry, Klingner, Sturges, & Moore, 2002; Skiba et al.,
Yet showing that poverty influences academic achievement is not the
same thing as demonstrating that poverty causes minority
disproportionality in special education, Skiba et al. (2005) noted that
developing a link between poverty and minority disproportionality
requires a series of logical connections, not all of which are
well-documented in the literature. Although there is a fairly strongly
documented connection between minority status and poverty (U.S. Census
Bureau, 2001), direct links between poverty and academic and behavioral
outcomes are not as impressive (Brooks-Gunn & Duncan, 1997). Nor do
academic or social/behavioral problems necessarily predict special
education eligibility, because the specific disability definitions of
IDEA are intended to ensure that not all students with academic or
emotional/behavioral problems are found eligible for special education.
Thus, to demonstrate that poverty contributes significantly to special
education disproportionality, it Would be necessary to show that
economic disadvantage increases the risk, not merely of
underachievement, but of the specific types of learning and behavior
problems defined by IDEA as disability.
Given this complexity, it is not surprising that investigations of
the association of poverty and special education disproportionality have
yielded inconsistent results that sometimes contradict the race-poverty
hypothesis. Some have found that poverty indeed creates higher rates of
minority placement in the disability categories of LD (Coutinho, Oswald,
& Best, 2002); MR (Finn, 1982); and ED (Oswald, Coutinho, &
Best, 2002). Others, however, have reported an opposite direction of
effect, finding that as levels of poverty decrease, minority students
are at greater risk for referral as LD (Zhang & Katsiyannis, 2002);
MR (Oswald, Coutinho, Best, & Nguyen, 2001); and ED (Oswald et al.,
In order to directly assess the contribution of poverty to the
disproportionate representation of African American students in special
education, Skiba et al. (2005) studied the relationship of special
education enrollment, race, socioeconomic and demographic factors, and
test score outcomes in a sample of 295 school districts in a midwestern
state. Across ordinary least squares and logistic regression equations,
poverty made a weak, inconsistent, and often counter-intuitive
contribution to the prediction of disproportionality across a number of
disability categories. Where poverty made any contribution above and
beyond race in predicting disability identification, its primary effect
was to magnify existing racial disparity.
Generalizations about the effects of poverty on parenting may also
yield unwarranted assumptions about families from groups overrepresented
in special education. Although poverty has been shown to be associated
with more negative parenting styles (McLloyd, 1998), there is no
evidence that African American or Latino families are, on average, more
dysfunctional than other families. Yet, in their recent ethnographic
study of racial disproportionality in special education, Harry and
Klingner (2006; Harry, Klingner, & Hart, 2005) found negative
beliefs about African American families to be pervasive among educators.
Families of African American students were described as neglectful,
incompetent, and dysfunctional, often absent any firsthand knowledge of
those families' actual circumstances. Such descriptions also ignore
significant cultural strengths in African American and Latino
communities, such as the involvement and expertise of extrafamilial
adults, who may act as protective factors despite economic disadvantage
(Harry & Klingner, 2006; King, 2005).
In summary, a variety of poverty-associated risk factors have been
shown to predict academic and behavioral gaps that might be expected to
lead to special education referral, suggesting that economic
disadvantage makes some contribution to minority disproportionality in
special education. Yet the path from initial referral to eligibility
determination is complex and governed by policy regulations that are by
no means strictly linear. It is not surprising, then, that research to
this point has not supported the hypothesis that poverty is the sole or
even primary cause of racial and ethnic disparities in special
education. In particular, although poverty creates conditions that
reduce parenting efficacy, assumptions made about the general quality of
African American or Latino families and their contributions to disparate
rates of special education referral are unwarranted given the extent of
Finally, regardless of the relationship among poverty, academic
achievement, and racial disparities, mechanisms for the negative effects
of poverty remain unclear. It is often presumed that economic
disadvantage affects educational readiness by increasing biological or
family-based risk prior to school entry. Yet students placed at risk for
the biological or social effects of poverty are also more likely to
attend schools with reduced educational resources and fewer
opportunities for quality instruction (McLloyd, 1998; Peske &
Haycock, 2006). In an educational system in which poor students of color
routinely receive an inferior education, the possible contributions of
the schooling itself to disparities in special education service must
also be considered.
UNEQUAL OPPORTUNITY IN GENERAL EDUCATION
One of the most consistent findings in educational research is that
students achieve in direct proportion to their opportunity to learn
(Wang, Haertel, & Walberg, 1997). It might well be expected that
students whose educational opportunities are limited will be more likely
to be referred for special education services (Artiles & Trent,
1994; Harry, 1994). Differential access to educational resources has
been consistently demonstrated for some minority groups in a number of
areas (Kozol, 2005; Peske & Haycock, 2006).
Of the possible links between general education practices and
special education disproportionality, however, only the proportion of
culturally consonant teachers in the teaching force has been directly
investigated. Serwatka, Deering, and Grant (1995) found that as the
percentage of African American teachers increased, overrepresentation of
African American students in the emotionally disturbed category
decreased. Similarly, in a cross-state comparison, Ladner and Hammons
(2001) found that the discrepancy of African American and White rates of
eligibility for special education rose in direct proportion to the
percentage of the teaching force that was White, especially in districts
with a White percentage of more than 60%.
More generally, however, inequity in the quality and quantity of
educational resources has been extensively documented. Curricula and
instructional presentation appear to disfavor working-class students or
students of color (Ferri & Connor, 2005, Sleeter & Grant, 1991).
Serious deficiencies in physical facilities and resources in urban
schools have been documented (Kozol, 1991, 2005; Oakes, Ormseth, Bell,
& Camp, 1990). Such resource disparities may have their origin in
inequitable school funding formulas (Rebell, 1999) or in historical
patterns of segregation and re-segregation (Katznelson, 2005; Orfield
& Eaton, 1996). Finally, a number of factors ranging from inadequate
teacher preparation (Barton, 2003); to teacher inexperience (Peske &
Haycock, 2006); to teacher reticence to teach in what are perceived to
be challenging areas may limit the access of students in high poverty,
high minority districts to quality teaching (Darling-Hammond, 2004).
Students from poverty backgrounds and students of color are also more
likely to be taught by teachers with less experience and expertise, in
more poorly funded schools that have difficulty recruiting and
maintaining both teachers of color in particular and a sufficient
teaching force in general (Barton; Donovan & Cross, 2002; Peske
These inequities have a demonstrable effect on the educational
opportunity and school achievement of low SES children. In a multiyear
observational study, Greenwood, Hart, Walker, and Risley (1994) reported
that inferior instruction in low SES schools resulted in students in
those schools receiving an equivalent of 57 weeks less academic
engagement than students in high SES schools by the sixth grade; as a
result, an achievement gap equal to 0.3 of a grade level at school entry
grew to a gap of 3.5 grade levels by Grade 6. These data make a strong
case that students of color in low SES communities are at greater risk
for poor quality educational experiences that undermine their academic
It is reasonable to presume that factors that limit educational
opportunity will impact educational achievement, thereby increasing the
risk for special education referral (Skiba, Bush, & Knesting, 2002).
Although suggestions that equity in special education services might
best be achieved by ensuring that quality educational services for all
students are longstanding (Heller et al., 1982), the influence of
general educational quality on special education referral is still
remarkably understudied. Although the link between teacher demographics
and special education disproportionality has been explored to some
extent (Ladner & Hammons, 2001; Serwatka et al., 1995), the
influence of other systemic factors such as quality of curriculum,
instruction, resources, or teacher training on differential rates of
special education referral and eligibility determination have yet to be
SPECIAL EDUCATION ELIGIBILITY AND DECISION-MAKING PROCESSES
Disparities in special education could be influenced by
inadequacies in practice or bias generated at the level of special
education referral and decision making. Although this possibility has
received some research attention, the pattern of results is somewhat
Referral. Available data suggest that racial disparities in the
classification of students as disabled begin at the stage of initial
classroom referral. Reviewing records of students referred for special
education evaluation in an urban school system, Gottlieb, Gottlieb, and
Trongone (1991) found that teachers referred minority children more
often than nonminority children and tended to refer minority students
for behavioral rather than academic issues. In a meta-analysis of 10
studies between 1975 and 2000 examining referral to special education,
Hosp and Reschly (2003) found that both African American and Latino
students were referred more often to special education than White
Examination of prereferral decision making by teachers has yielded
mixed results. Bahr, Fuchs, Stecker, and Fuchs (1991) found that,
despite relatively minor differences in descriptions of academic and
behavioral functioning, general education teachers were more likely to
describe African American students as difficult to teach and, hence,
more likely to be referred to special education. Shinn, Tindal, and
Spira (1987) compared teacher recommendations for referral based on
curriculum-based measures and found that teachers were more likely to
refer Black than White students based on those results in Grades 2 to 4.
In contrast, MacMillan and Lopez (1996) found that Black students
referred to a student support team prior to special education referral
were more likely to have lower test scores and more severe behavioral
ratings, leading the researchers to conclude that teachers may wait to
refer Black students until their academic or behavioral problems reach a
higher level of severity. On a positive note, Gravois and Rosenfield
(2006) found that changes in prereferral practice can significantly
impact disproportionate representation: Schools using an instructional
consultation model significantly reduced both their overall rate of
special education referral and identification and reduced racial/ethnic
discrepancies in rates of referral and identification.
Assessment and Decision Making. Investigations of the possibility
of bias during the assessment and decision-making process have not been
undertaken recently and present a somewhat conflicting picture. Analogue
studies using a case study vignette (e.g., Prieto & Zucker, 1981)
found a greater willingness among both general and special education
teachers to recommend minority students for special education given
identical referral information. In two studies using a similar simulated
research paradigm, Tobias and colleagues (Tobias, Cole, Zibrin, &
Bodlakova, 1982; Tobias, Zibrin, & Menell, 1983) found that teachers
rated students of minority backgrounds different than their own as more
appropriate for special education identification in the first but not
the second study. Reviewing tapes of case review teams making placement
decisions, Ysseldyke, Algozzine, Richey, and Graden (1982) reported that
factors such as student race and SES contributed more to placement
decisions than did performance data. Tomlinson, Acker, Canter, and
Lindborg (1978) examined special education referral and decisionmaking
processes and found that minority students were referred more often,
that their parents were contacted significantly less often to
participate in the special education process, and that the
recommendations to minority parents were more restrictive and less
comprehensive than recommendations for nonminority parents.
Large discrepancies between actual practice and the ideal due
process provisions outlined in IDEA have been documented in the
literature, and those discrepancies may well contribute, to some extent,
to disproportionality in service. Gottlieb, Alter, Gottlieb, and Wishner
(1994) noted that, in the urban school districts they studied, many
students received services for learning disabilities despite not meeting
the LD discrepancy criteria for identification. Similarly, MacMillan and
Reschly (1998) argued that up to half of all students identified as LD
do not meet their state's criteria for identification. In their
ethnographic exploration, Harry and Klingner (2006) described numerous
inconsistencies in the special education conferencing phase that may
contribute to disproportionality, including rates of special education
referral differing by the race and ethnicity of the teacher, the
disproportionate weight given the opinion of the referring teacher at
the case conference, and the weak emphasis on prereferral strategies.
Thus, racial and ethnic disparities in special education
identification appear to begin at the stage of initial teacher referral,
and it seems likely that breakdowns in the due process provisions
governing special education can contribute to the inappropriate
identification of minority students in special education. Yet given the
lack of consistency in this research, as well as the age of many of the
studies, the extent to which current special education eligibility
determination processes contribute to special education inequity is
unclear. The most recent National Research Council (NRC) panel (Donovan
& Cross, 2002) concluded that evidence of bias in the referral to
placement process was mixed, but that the process has sufficient
shortcomings as to be unable to ensure that the correct students are
being identified. Further, the panel contended that the entire process
is weighted toward referral and placement only after a student has
experienced failure, thus ensuring that child's problems will be
relatively intractable by the time he or she is finally placed in
BEHAVIOR AS THE NEXUS OF RACE AND DISABILITY
Special education is, of course, not the only educational domain in
which students of color are disproportionately represented. Consistent
evidence has documented large gaps between students of color and their
peers in academic achievement as measured by accountability test scores
(Jencks & Phillips, 1998); graduation and dropout rates (Holzman,
2004); and placement in educational programs such as gifted and talented
and Advanced Placement/Honors courses (Donovan & Cross, 2002; Ford,
Grantham, & Whiting, 2008; Joseph & Ford, 2006).
The disproportionate representation of African American students in
school suspension has been widely documented. For more than 30 years, in
national, state, district, and local data, African American students
have consistently been found to be suspended out-of-school at higher
rates than other students, and similarly overrepresented in office
referrals, corporal punishment, and school expulsion (e.g.,
Children's Defense Fund, 1975; Raffaele Mendez & Knoff, 2003;
Skiba, Michael, Nardo, & Peterson, 2002; Wu, Pink, Crain, &
Moles, 1982). In one study of a large and diverse school district, 50%
of African American male and one third of African American female middle
school students experienced out-of-school suspensions during one school
year (Raffaele Mendez & Knoff), rates that were substantially higher
than White male (25%) and White female (9.3%) middle school students.
Disproportionality in school suspension has not been as consistently
documented for Latino or other ethnic minority groups (Skiba &
The contributing factors or causes of racial and ethnic disparities
in school discipline have not been conclusively determined. Although it
has been argued that disproportionality in school punishments is
primarily a function of poverty (National Association of Secondary
School Principals, 2000), race remains a significant predictor of
suspension and expulsion, even when socioeconomic status is controlled
in multivariate analyses (Skiba, Michael, et al., 2002; Wu et al.,
1982). Nor does disciplinary disproportionality appear to be the result
of differential rates of misbehavior by African American students. Any
racial differences in reasons for suspension that have been found
suggest that African American students receive more severe punishments
for less serious infractions (Shaw & Braden, 1990) or are referred
to the office more frequently for more subjective reasons, such as
disrespect or loitering (Skiba, Peterson, et al., 2002). Other
explanations for disciplinary disproportionality include the possible
misinterpretation by classroom teachers of culturally based behaviors
(Townsend, 2000) or stereotypes regarding Black males that increase the
likelihood of office referral (Ferguson, 2001).
There are also indications of racial disproportionality in the
application of the specific disciplinary provisions of IDEA. A recent
state report (Rausch & Skiba, 2006) found that about 3% of African
American students with disabilities received at least one of the IDEA
disciplinary provisions, a rate 2.8 times higher than all other students
with disabilities. Further, the greatest racial disparities were found
in the IDEA disciplinary provision other suspension/expulsion greater
than 10 days, in which African American students were found to be 3.4
times as likely as their peers with a disability to receive this
provision. Disproportionality in specific school districts ranged from
relatively proportional use (relative risk ratio = 1.03) to a rate in
one school district in which African American students with disabilities
were more than 10 times more likely than other students with
disabilities to receive one of the IDEA disciplinary provisions.
The intersection of disproportionality in school discipline and
special education has been commented on (Gregory, 1997) but
insufficiently explored. Investigations of disproportionality in
referrals to special education or prereferral teams consistently find
that African American students are more likely to be referred for
behavioral reasons (Gottlieb et al., 1991; MacMillan & Lopez, 1996).
The nature and causes of disciplinary disproportionality represent an
important avenue for further research on racial disparities in special
CULTURAL MISMATCH AND CULTURAL REPRODUCTION
Emerging scholarship has conceptualized the disproportionate
representation of minority students in special education, African
American students in particular, as a symptom of a broader disconnect
between mainstream educational culture and the cultural orientations of
communities of color. A number of scholars have argued that contemporary
mainstream educational systems, special education systems in particular
(Patton, 1998), closely reflect the knowledge, values, interests, and
cultural orientations of White, middle-class cultural groups (Delpit,
1995; King, 2005). Education that fails to explicitly teach the codes
and rules necessary for successful participation in unfamiliar cultural
contexts (Delpit), does not connect knowledge produced in schools to
students' lived experiences (Ladson-Billings, 1994), or ignores the
foundational role of culture in knowledge production (Sheets, 2005) may
yield inadequate and inappropriate educational experiences for a range
of cultural groups.
Notably, such knowledge is not well-represented in mainstream
scholarship (Trent et al., 2008). The intensive observation required by
such research may make it more difficult to conduct, compared to tests
of more prevalent hypotheses present in contemporary scholarship (e.g.,
poverty, test bias). Alternatively, it has been argued that
non-mainstream epistemologies, paradigms, discourses, and research
orientations have been systematically devalued or "silenced"
(Delpit, 1995), producing a database that has explored only a limited
range of hypotheses for unequal educational outcomes of African American
and Latino students in general (King, 2005), and disproportionality in
special education in particular (Patton, 1998).
One theoretical perspective that holds promise for providing a
framework within which to view racially disparate educational outcomes
is the model of cultural reproductive systems and actions (Bowles &
Gintis, 1976). Developed as an explanation of the perpetuation of social
class hierarchies, the theoretical framework of cultural reproduction
has been utilized by equity researchers to demonstrate how institutional
and individual actions maintain a hierarchical status quo at the expense
of less-privileged groups (Harry & Klingner, 2006; Mehan, 1992;
Oakes, 1982). Cultural reproduction implies that individuals can become
a part of institutional patterns through constitutive actions (Mehan,
1992; Mehan, Hertweck, & Miehls, 1986) that can reproduce the status
quo without being consciously aware of their contribution to inequity.
Recent ethnographic investigations have found clear evidence of
reproductive processes that may well contribute to inequitable outcomes
in special education. In an ethnographic study focusing primarily on the
role of school psychologists in assessment decision making, Harry et al.
(2002) found that although psychological testing is often perceived as
an objective procedure designed to reduce the influence of individual
judgment, in fact, the process is often highly idiosyncratic, as
psychologists choose tests or test batteries more likely to produce the
results they, or the teachers making the referral, wish to see. Using
Heller et al.'s (1982) conclusion that disproportionality could be
viewed as a problem if there is evidence of inappropriate practice or
bias at any phase of the process, Harry and Klingner (2006) tracked
opportunity to learn, the special education eligibility decision-making
process, and special education programming. They found evidence of a
number of institutional constraints and constitutive actions that
appeared to influence the course of special education placement and
programming for minority students, including poor teacher quality, large
class sizes, arbitrary application of eligibility decision-making
criteria, tardiness in placement processes, and special education
programs that were themselves ineffective or overly restrictive. The
authors argued that such findings suggest the need for increased
attention to school-based risk as a contributing factor to inequity in
DISPROPORTIONALITY AS A MULTIPLY DETERMINED PHENOMENON
It should be apparent from the preceding discussion that there is
no single simple explanation that appears to fit the data on special
education disproportionality. Rather, minority disproportionality in
special education appears to be multiply determined, a product of a
number of social forces interacting in the lives of children and the
schools that serve them (see Trent et al., 2008).
Qualitative findings have highlighted the interacting forces that
may set the context for and maintain racial disparities in special
education. In an intensive case study interviewing teachers, principals,
school psychologists, and administrators about their perspectives on
special education and culture, Skiba et al. (2006a) reported a complex
picture of the factors that contribute to referral. Teachers feel highly
challenged to meet the needs of students with economic disadvantages,
yet feel they are given insufficient resources to meet those needs.
Classroom behavior proved to be a difficult issue for many teachers,
exacerbated by cultural gaps and misunderstandings. Prereferral or
general education intervention teams were seen as potentially useful in
supporting teachers working with students with academic or behavioral
challenges, but the use and perceived effectiveness of those teams
varied widely. Perceiving special education as the only resource
available for helping students who are not succeeding, classroom
teachers were quite willing to err in the direction of over-referral if
it meant access to more resources for their neediest students. Finally,
there was clear discomfort among many respondents in discussing issues
of race; although comfortable and even eloquent in describing the impact
of poverty, many respondents seemed anxious to avoid talking about
issues involving race or ethnicity.
The multidetermined nature of disproportionality likely means that
there is no single cause that can be called on to explain racial and
ethnic disparities in special education in all states or school
districts. In urban schools and districts, a lack of physical and
personnel resources may create a pressure to refer low performing
students who are predominantly minority to one of the few services
available for students who are struggling (Gottlieb et al., 1994; Skiba
et al., 2006a). Yet Ladner and Hammons (2001) found that the highest
rates of racial/ethnic disparities in special education service were not
evident in those urban districts, but rather in higher-income suburban
districts. These types of discrepancies suggest that the search for the
causes of disproportionality will need to become more attuned to
differential rates of disproportionality across locales and different
factors that may contribute to disproportionality in those locales.
Widely differing racial/ethnic patterns of disproportionate
representation suggest that the causes of disparities will vary
considerably for African Americans in Washington, DC or New York City
and Latino students in Houston or Los Angeles, and that both of these
will show a pattern of disproportionality dramatically different from a
predominantly White school system in a suburban or rural location.
STRATEGIES FOR REDUCING DISPROPORTIONATE REPRESENTATION
If disproportionality in special education is multiply determined,
no single intervention strategy can be universally relied on to reduce
racial disparity. Rather, complex causality clearly suggests the need
for comprehensive and multifaceted assessment and intervention plans. In
particular, the possibility that the determinants of disproportionality
are locale-specific suggests that remediation plans must be driven by
local needs assessment capable of identifying unique local patterns.
Team-based needs assessment models for addressing disproportionate
representation have been described by Ritter and Skiba (2006) and
Klingner et al. (2005). Central to such an approach is a process that
moves from data collection and examination, to interpretation, to
culturally competent intervention and evaluation.
EXAMINATION OF THE DATA
Data on disproportionality serves to establish both a baseline and
a method of monitoring progress. The NRC recommended a national effort
to establish both a standard data collection system and a longitudinal
assessment of trends in disproportionality (Donavan & Cross, 2002).
One important future course for practical remediation of
disproportionality at the local level will be to disseminate practical
methods of data collection analysis (Salend, Garrick Duhaney, &
Montgomery, 2002). It seems likely that the continuous feedback loop
afforded by the examination of local data on racial disparities can
create change at the systems level (Johnson, 2002). Yet, it is only
relatively recently that the field of special education has identified a
set of measures (e.g., the composition index, the relative risk ratio)
with which to monitor disproportionate representation. If local efforts
are to be made to address racial disparities, practical and efficient
methods for calculating disparities will need to become available to
A range of possible hypotheses might be brought to bear in
interpreting a set of data indicating racial disparity. On one end,
hereditarian interpretations (e.g., Herrnstein & Murray, 1994) have
tended to focus on inherent and genetic explanations of the achievement
gap and group differences in performance. Alternatively, critical race
theory (Delgado & Stefancic, 2002; Ladson-Billings & Tate, 1995)
suggests that racial and economic disparities result from the use of the
concept of race in structuring institutions and interactions to maintain
the power and privilege of the dominant group. It is clear that each of
these theoretical orientations yields very different implications for
Indeed, the effectiveness of an intervention chosen to address
disproportionate representation depends, to some degree, on the accuracy
of diagnosis of the causes of disparity. Early intervention appears to
be an extremely promising intervention for a range of developmental
issues related to socioeconomic disadvantage (Barnett, 1995). Early
intervention approaches could be expected to reduce disparities only to
the extent that economic disadvantage is at work. Early intervention
would not be expected to address systemic failures or bias and would
hence fail to address disproportionality that is due to institutional
Unfortunately, interpretation of data on differential racial
treatment itself appears to be conditioned by race. The difficulty that
educators, especially White educators, have in openly talking about race
and racism has been well documented (King, 1991; Skiba et al., 2006a;
Trepagnier, 2006). A number of authors have noted that it is common for
interpretations of equity data to be based on a majority viewpoint
(King, 2005; Patton, 1998). Recent history from the Simpson trial to
reactions to Hurricane Katrina indicate that, at this point in our
nation's history, interpretations of data on racial and ethnic
disparities will vary depending on the cultural makeup of the audience
confronting the data. Thus, educators and policy makers seeking
effective interventions to close special education equity gaps must be
willing to openly discuss and address issues of race, ethnicity, gender,
class, culture, and language. Moreover, processes chosen to address
inequity must have at their core a mechanism to ensure that the
perspectives of all stakeholders, especially those of historically
marginalized groups who have been the recipients of unequal treatment,
are represented when interpreting data on racial and ethnic disparities.
INTERVENTION AND EVALUATION
Until such time as the understanding of the complex interactions
that create disproportionality improves, intervention plans addressing
disproportionate service must be both comprehensive and local. In the
context of a multidetermined phenomenon, debates about individual versus
systemic contributions to disproportionality distract from the need to
carefully craft and implement comprehensive intervention programs that
can target a variety of sources of disparity. Thus, developing a needs
assessment process to ensure that any and all strategies are tailored to
address local needs may well be more important (and effective) than the
choice of any single intervention.
Although there is scant evidence regarding the effect of any
specific interventions on measured disproportionality, recommendations
have been offered based on research related to best practices in
instruction, education leadership, and academic and behavioral
interventions, as well as research relating to culturally and
linguistically responsive practice:
* Teacher preparation. Issues of cultural mismatch, suggesting that
teachers may simply lack the knowledge and skills to successfully
interact with students different from themselves (Ladson-Billings,
1995), highlight the importance of teacher training in culturally
responsive pedagogy (Klingner et al., 2005; Trent et al., 2008).
* Improved behavior management. The most recent NRC panel
identified inadequate classroom management as a factor increasing the
risk for overreferral of minority students (Donovan & Cross, 2002).
Culturally responsive behavioral supports have been identified as a
promising method for addressing issues of classroom disruption and
school discipline (Cartledge & Kourea, 2008; Klingner et al., 2005)
* Prevention and early intervention. The disproportionate
representation of minorities in special education is due, in some
measure, to social and demographic factors that concentrate risk factors
in minority populations (Coutinho & Oswald, 2000). A primary
prevention model, wherein universal supports are offered to all students
and more specific supports, such as cultural brokering, are offered to
students more at risk appears to be a promising model for addressing
disproportionality (Serna, Forness, & Nielsen, 1998).
* Prereferral intervention/response to intervention. Heller et al.
(1982) argued that "It is the responsibility of teachers in the
regular classroom to engage in multiple educational interventions and to
note the effects of such interventions on a child experiencing academic
failure before referring the child for special education
assessment" (p. 94). Guidance provided by the National Alliance of
Black School Educators (NABSE) and the Council for Exceptional Children
(NABSE, 2002) specifically charges school administrators with
responsibility for selecting and implementing effective prereferral
intervention systems in their schools.
* Assessment. Irrespective of the possibility of cultural bias in
standardized tests, there appears to be ample opportunity for bias to
occur during the process of special education eligibility decision
making. Artiles and Trent (1994) suggested that a functional assessment
model with its increased emphasis on context for understanding a
student's academic or behavioral difficulty will provide a more
culturally responsive means of assessment. Salend et al. (2002) add that
factors related to culture, language, and experience must be
distinguished from learning and behavior problems.
* Family and community involvement. To enable more active parent
involvement, Artiles and Trent (1994) recommended that educators assess
their own levels of cross-cultural competency. In particular, parents
and families should be involved in the prereferral/response to
intervention (RTI) process, and the values of families and culture
integrated into all special education decision-making processes (Harry,
2008; NABSE, 2002).
* Policy and systems refarm recommendations. The multifaceted and
longstanding nature of the disproportionality problem almost certainly
necessitates systemic reform or policy change. Klingner et al. (2005)
recommended examination of federal, state, district, and school policies
to create culturally responsive educational systems, including such
areas as school financing, the influence of high-stakes tests, teacher
performance with culturally diverse populations, and teacher training in
culturally competent pedagogy.
DISCUSSION AND CONCLUSIONS
Given that disproportionality in special education is grounded in a
long history of inequity, it should not be surprising that the factors
that maintain or sustain disproportionality are complex, embedded in
social and institutional practices in ways that are not yet fully
understood. Although a number of possible causes and maintaining
conditions of special education disproportionality have been identified,
in no area is the literature sufficient to accept any single cause as
fully determinative of racial disparity. Claims of some researchers in
the area of test bias notwithstanding (Jensen, 1980), bias in the
process of assessment, and perhaps even in test items, has not been
conclusively ruled out (Valencia & Suzuki, 2000). There are also
abundant sources of inequitable educational opportunity in our
nation's educational system (Kozol, 2005), but few studies have
explored the impact of racial disparities in educational resources or
instructional quality on rates of special education referral. Some
plausible sources of bias in the special education eligibility
decision-making process have been identified, but inconsistencies in
that literature suggest that evidence for special education bias is
mixed (Donovan & Cross, 2002). Factors contributing to racial and
ethnic disparity may to some extent be grounded in a social reproductive
model of schooling (Bowles & Gintis, 1976) in which educational
professionals participate in institutional practices that, left
unanalyzed, reinforce a status quo that maintains class- and race-based
The most fitting conclusion that can be drawn from the available
literature predicting special education referral and eligibility is that
disproportionality in special education is determined by a combination
of forces both within and external to our educational system. It seems
likely that future research will find complex and perhaps unexpected
interactions among variables that have, to this point, been studied only
in isolation or on a limited scale. It is reasonable to presume, for
example, that students from economically disadvantaged backgrounds will
exhibit academic or behavioral problems at a higher rate that make them
more likely to be considered by teachers as appropriate candidates for
special education services. Yet, it also seems likely that a
teacher's judgment of appropriateness for referral is conditioned
by that teacher's self-efficacy with respect to instructing or
interacting with students from a class or cultural background different
from his or her own. Further, institutional structures, sometimes at
variance with state or federal policy, appear to channel the behaviors
of the individuals within those institutions into habitual patterns that
maintain existing inequities (Mehan, 1992). In short, any view that
racial disparities are due solely to either individual characteristics
or systems or individual bias must be regarded as highly simplistic.
Ultimately, it is likely that more sophisticated research designs will
demonstrate that racial disparities in special education eligibility and
service are due to an interaction of student characteristics, teacher
capabilities and attitudes, and unanalyzed sources of structural
inequity and racial stereotype. The challenge in addressing inequity in
special education is to recognize the simultaneous contribution of those
multiple sources, and to design interventions that can respond to the
full complexity of the problem.
It cannot be assumed that interventions that have been shown to
work on average in improving educational outcomes will also be effective
for groups that have been traditionally marginalized. Systemic
strategies such as functional assessment (Sugai, Lewis-Palmer, &
Hagan-Burke, 2000) and response-to-intervention models (Fuchs &
Fuchs, 2006) hold some promise for addressing general institutional
issues that may well result in overidentification of minority children
and youth. Yet, simply improving the referral process for students in
general will not, in and of itself, guarantee an effect on the
differential rates of special education referral for racially and
ethnically diverse students. To ensure that the needs of those who are
targeted in disproportionality interventions are met, it will be
necessary to develop and implement approaches specifically designed to
be culturally responsive (Klingner et al., 2005). In this case,
culturally responsive interventions might be defined as those that are
not only intended to improve academic and behavioral outcomes in
general, but are also specifically designed and evaluated in terms of
their capability to reduce measured inequity.
There have been very few investigations, however, of the impact of
any intervention on disparate rates of special education service per se.
One notable exception is Gravois and Rosenfield (2006), who provided
evidence that a 2-year implementation of Instructional Consultation
Teams was effective in reducing both total referrals to and placements
in special education and disproportionality in referral and service.
Until such time that certain interventions can be shown to reliably
create reductions in racial disparities in special education
identification, continued monitoring of disaggregated data is a critical
component of all intervention efforts in order to ensure that systemic
efforts are truly having an impact on the variable of
concern--disproportionate representation by race and ethnicity.
Finally, the fact that a multiplicity of variables, across both
general and special education, may contribute to disproportionate
representation has important implications for the implementation of
special education policy. In promulgating IDEA 2004, Congress deemed
disproportionate representation that is the result of inappropriate
identification sufficiently important as to constitute a key monitoring
priority (IDEA 2004, 34 CFR 300.600(d)(3)). There may be some temptation
to restrict the interpretation of "inappropriate
identification" so as to focus primarily on special education
policies, practices, and procedures. Yet, the data dearly indicate that
racial and ethnic disparities in special education are not solely a
special education problem, but are also rooted in a number of sources of
educational inequity in general education, including curriculum (Ferri
& Connor, 2005); classroom management (Donovan & Cross, 2002);
teacher quality (Darling-Hammond, 2004; Peske & Haycock, 2006); and
resource quality and availability (Barton, 2003; Kozol, 2005). Students
who are referred to special education because they have failed to
receive quality instruction or effective classroom management have been
inappropriately identified as much as if they were given an
inappropriate test as part of special education assessment.
Brown v. Board of Education (1954) indeed represented a key
milestone in the struggle for equity of opportunity for all children
(Blanchett, Mumford, & Beachum, 2005; Smith & Kozleski, 2005).
Yet, it is important to understand that Brown represented only the
beginning of the end of institutionalized and legal segregation in the
United States. It was not until 1969, in Alexander v. Holmes County
Board of Education, that the Supreme Court set aside the notion of
"due deliberate speed" and set deadlines for the end of
educational segregation (Lowery & Marszalek, 1992). Thus, the period
of American history characterized by an absence of state-sponsored
segregation, discrimination, and oppression represents only about one
tenth of the time that governmental policies supported a clearly defined
and explicit racial hierarchy. Nor has the progress since Brown been
entirely consistent: Policy changes since 1980 have led some to question
to what extent the promises of that decision have been fulfilled
(Blanchett et al., 2005; Orfield & Eaton, 1996). In the face of a
nascent and perhaps still tenuous national commitment to equity, it
should not be surprising that vestiges of America's history of race
remain embedded in our consciousness, actions, and institutions. There
is still abundant work that remains to be done if such vestiges are to
be once and for all erased.
Manuscript received October 2006; accepted October 2007.
Abedi, J. (2004). The No Child Left Behind Act and English language
learners: Assessment and accountability issues. Educational Researcher,
Ainsworth, J. W. (2002). Why does it take a village? The meditation
of neighborhood effects on educational achievement. Social Forces,
Alexander v. Holmes County Board of Education, 396 U.S. 1218
Artiles, A. J. (2003). Special education's changing identity:
Paradoxes and dilemmas in views of culture and space. Harvard
Educational Review, 73, 164-202.
Artiles, A. J., Rueda, R., Salazar, J. J., & Higareda, I.
(2002). English language learner representation in special education in
California urban school districts. In D. J. Losen & G. Orfield
(Eds.), Racial inequity in special education (pp.117-135) Cambridge, MA:
Harvard Education Publishing Group.
Artiles, A. J., & Trent, S. C. (1994). Overrepresentation of
minority students in special education: A continuing debate. The Journal
of Special Education, 27(4), 410-437.
Bahr, M., Fuchs, D., Stecker, P., & Fuchs, L. (1991). Are
teachers' perceptions of difficult-to-teach students racially
biased? School Psychology Review, 20(4), 599-608.
Barrera, M. (2006). Roles of definitional and assessment models in
the identification of New or Second Language Learners of English for
special education. Journal of Learning Disability, 39, 142-156.
Barnett, W. S. (1995). Long term effects of early childhood
programs on cognitive and school outcomes. The Future of Children, 5(3),
Barton, P. E. (2003). Parsing the achievement gap: Baselines for
tracking progress. Princeton, NJ: Educational Testing Service.
Bersoff, D. N. (1981). Testing and the law. American Psychologist,
Blanchett, W. J., Mumford, V., & Beachum, F. (2005). Urban
school failure and disproportionality in a post-Brown era: Benign
neglect of the Constitutional rights of students of color. Remedial and
Special Education, 26(2), 70-81.
Blaustein, A. P., & Zangrando, R. L. (Eds.). (1968). Civil
rights and the Black American: A documentary history. New York: Clarion
Bowles, S., & Gintis, H. (1976). Schooling in capitalist
America. New York: Basic Books.
Brooks-Gunn, J., & Duncan, G. J. (1997). The effects of poverty
on children. The Future of Children, 7(2), 55-71.
Brown, R. T., Reynolds, C. R., & Whitaker, J. S. (1999). Bias
in mental testing since Bias in Mental Testing. School Psychology
Quarterly, 14, 208-238.
Brown v. Board of Education, 347 U.S. 483 (1954).
Caldas, S. J., & Bankston, C. L. (1999). Multilevel examination
of student, school, and district-level effects on academic performance.
Journal of Educational Research, 93(2), 91-100.
Cartledge, G., & Kourea, L. (2008). Culturally responsive
classrooms for culturally diverse students with and at risk for
disabilities. Exceptional Children, 74, 351-371.
Children's Defense Fund. (1975). School suspensions: Are they
helping children? Cambridge, MA: Washington Research Project.
Chinn, P. C., & Hughes, S. (1987). Representation of minority
students in special education classes. Remedial and Special Education,
Cole, N. S. (1981). Bias in testing. American Psychologist, 36,
Coutinho, M. J., & Oswald, D. P. (2000). Disproportionate
representation in special education: A synthesis and recommendations.
Journal of Child and Family Studies, 9(2), 135-156.
Coutinho, M. J., & Oswald, D. P. (2004). Disproportionate
representation of culturally and linguistically diverse students in
special education: Measuring the problem. Practitioner Brief Series:
National Center for Culturally Responsive Educational Systems.
Coutinho, M. J., Oswald, D. P., & Best, A. M. (2002). The
influence of sociodemographics on the disproportionate identification of
minority students as having learning disabilities. Remedial and Special
Education, 23, 49-59.
Darling-Hammond, L. (2004). Inequity and the right to learn: Access
to qualified teachers in California's public schools. Teachers
College Record, 106(10), 1936-1966.
Davies, H., Crombie, I., & Tavakoli, M. (1998). When can odds
ratios mislead? British Medical Journal, 316, 989-991.
Delgado, R., & Stefancic, J. (2002). Critical race theory: The
cutting edge (2nd ed.). Philadelphia: Temple University Press.
Delpit, L. D. (1995). Other people's children: Cultural
conflict in the classroom. New York: New Press.
Diana v. California State Board of Education, No. C-70, RFT, (N.D.
Donovan, M. S., & Cross, C. T. (Eds.). (2002). Minority
students in special and gifted education. Washington, DC: National
Dunn, L. M. (1968). Special education for the mildly retarded--is
much of it justifiable? Exceptional Children, 23, 5-21.
Ferguson, A. A. (2001). Bad boys: Public schools and the making of
Black masculinity. Ann Arbor: University of Michigan Press.
Ferri, B. A., & Connor, D. J. (2005). In the shadow of Brown:
Special education and overrepresentation of students of color. Remedial
and Special Education, 26, 93-100.
Fierros, E. G., & Conroy, J. W. (2002). Double jeopardy: An
exploration of restrictiveness and race in special education. In D. J.
Losen, & G. Orfield (Eds.), Racial inequity in special education
(pp. 39-70). Cambridge, MA: Harvard Education Press.
Finn, J. D. (1982). Patterns in special education placement as
revealed by the OCR survey. In K. A. Heller, W H. Holtzman, & S.
Messick (Eds.), Placing children in special education: A strategy for
equity (pp. 322-381).Washington, DC: National Academy of Sciences
National Academy Press.
Ford, D. Y., Grantham, T. C., & Whiting, G. W. (2008).
Culturally and linguistically diverse students in gifted education:
Recruitment and retention issues. Exceptional Children, 74, 289-306.
Freedle, R. O. (2003). Correcting the SAT'S ethnic and
social-class bias: A method for reestimating SAT scores. Harvard
Educational Review, 73(1), 1-43.
Fuchs, D., & Fuchs, L. S. (1986). Test procedure bias: A meta
analysis of examiner familiarity effects. Review of Educational
Research, 56, 243-262.
Fuchs, D., & Fuchs, L. S. (2006). Introduction to response to
intervention: What, why, and how valid is it? Reading Research
Quarterly, 41(1), 93-99.
Gottlieb, J., Gottlieb, B. W., & Trongone, S. (1991). Parent
and teacher referrals for a psychoeducational evaluation. Journal of
Special Education, 25(2), 155-167.
Gottlieb, J. M., Alter, M., Gottlieb, B. W., & Wishner, J.
(1994). Special education in urban America: It's not justifable for
many. Journal of Special Education, 27, 453-465.
Gravois, T. A., & Rosenfield, S. A. (2006). Impact of
instructional consultation teams on the disproportionate referral and
placement of minority students in special education. Remedial and
Special Education, 27(1), 42-52.
Greenwood, C. R., Hart, B., Walker, D., & Risley, T. R. (1994).
The opportunity to respond revisited: A behavioral theory of
developmental retardation and its prevention. In R. Gardner III et al.
(Eds.), Behavior analysis in education: Focus on measurably superior
instruction (pp. 213-223). Pacific Grove, CA: Brooks/Cole.
Gregory, J. F. (1997). Three strikes and they're out: African
American boys and American schools' responses to misbehavior.
International Journal of Adolescence and Youth, 7(1), 25-34.
Guadalupe Organization v. Temple Elementary School District #3, No.
71-435 (D. Ariz, 1972).
Harmer, H. (Ed.). (2001). The Longman companion to slavery,
emancipation, and civil rights. Harlow, UK: Longman.
Harrington, G. M. (1975). Intelligence tests may favour the
majority groups in a population. Nature, 258, 708-709.
Harry, B. (1994). The disproportionate representation of minority
students in special education: Theories and recommendations. Alexandria,
VA: National Association of State Directors of Special Education.
Harry, B. (2008) Collaboration with culturally and linguistically
diverse families: Ideal versus reality. Exceptional Children, 74,
Harry, B., & Klingner, J. (2006). Why are so many minority
students in special education? Understanding race and disability in
schools. New York: Teachers College Press.
Harry, B., Klingner, J., Sturges, K. M., & Moore, R. F. (2002).
Of rocks and soft places: Using qualitative methods to investigate
disproportionality. In D. J. Losen & G. Orfield (Eds.), Racial
inequity in special education (pp. 71-92). Cambridge, MA: Harvard
Harry, B., Klingner, J. K., & Hart, J. (2005). African American
families under fire: Ethnographic views of family strengths. Remedial
and Special Education, 26, 101-112.
Heller, K. A., Holtzman, W. H., & Messick, S. (Eds.). (1982).
Placing children in special education: A strategy for equity.
Washington, DC: National Academy Press.
Herrnstein, R. J., & Murray, C. (1994). The bell curve:
Intelligence and class structure in American life. New York: Free Press.
Hickman, J. A., & Reynolds, C. R. (1987). Are race differences
in mental test scores an artifact of psychometric methods?: A test of
Harrington's experimental model. Journal of Special Education, 20,
Hobson v. Hansen, 269 F. Supp. 401 (D.C. Cir. 1967).
Hodgkinson, H. L. (1995). What should we call people? Race, class,
and the census for 2000. Phi Delta Kappan, 77, 173-179.
Holzman, M. (2004). Public education and Black male students: A
state report card. Cambridge, MA: The Schott Foundation for Public
Hosp, J. L., & Reschly, D. J. (2003). Referral rates for
intervention and assessment: A meta-analysis of racial differences.
Journal of Special Education, 37, 67-81.
Hosp, J. L., & Reschly, D. J. (2004). Disproportionate
representation of minority students in special education: Academic,
demographic, and economic predictors. Exceptional Children, 70, 185-199.
Huebner, E. S. (1985). The influence of rural, suburban, and urban
student background and school setting upon psychoeducational decisions.
School Psychology Review, 14(2), 239-241.
Individuals With Disabilities Education Act (IDEA), 20 U.S.C.
[section][section] 1401 et seq.
Individuals With Disabilities Education Act Amendments of 1997, Pub
L. No. 105-17, 105th Cong., 1st sess.
Individuals With Disabilities Education Act Regulations, 34 C.F.R.
300.1 et seq.
Individuals With Disabilities Education Improvement Act of 2004,
Pub. L. No. 108-446 (2004).
Individuals With Disabilities Education Improvement Act of 2004,
118 Stat. 2739.
Jackson, J. P., & Weidman, N. M. (2006). Race, racism, and
science: Social impact and interaction. New Brunswick, NJ: Rutgers
Jencks, C., & Phillips, M. (Eds.). (1998). The Black White test
score gap. Washington, DC: Brookings Institution Press.
Jensen, A. R. (1980). Bias in mental testing. New York: Free Press.
Johnson, R. S. (2002). Using data to close the achievement gap: How
to measure equity in our schools. Thousand Oaks, CA: Corwin Press.
Joseph, L. M., & Ford, D. Y. (2006). Nondiscriminatory
assessment: Considerations for gifted education. Gifted Child Quarterly,
Katznelson, I. (2005). When affirmative action was White: An untold
history of racial inequality in twentieth century America. New York: W.
W. Norton & Co.
Kidder, W. C., & Rosner, J. (2002) How the SAT creates
"built-in headwinds": An educational and legal analysis of
disparate impact. Santa Clara Law Review, 43(1), 131-211.
King, J. E. (1991). Dysconscious racism: Ideology, identity, and
the miseducation of teachers. Journal of Negro Education, 60(2),
King, J. E. (Ed.). (2005). Black education: A transformative
research and action agenda for the new century. Mahwah, NJ: Lawrence
Erlbaum Associates for the American Educational Research Association.
Klingner, J. K., Artiles, A. J., Kozleski, E., Harry, B., Zion, S.,
Tare, W. et al. (2005). Addressing the disproportionate representation
of culturally and linguistically diverse students in special education
through culturally responsive educational systems. Education Policy
Analysis Archives, 13(38), 1-39.
Klingner, J. K., Artiles, A. J., & Mendez Barletta, L. (2006).
English Language Learners who struggle with reading: Language
acquisition or LD? Journal of Learning Disabilities, 39, 108-128.
Kozol, J. (1991). Savage inequalities. New York: Crown.
Kozol, J. (2005). The shame of the nation: The restoration of
apartheid schooling in America. New York: Crown.
Kramer, R. A., Allen, L., & Gergen, P. J. (1995). Health and
social characteristics and children's cognitive functioning:
Results from a national cohort. American Journal of Public Health,
Ladner, M. & Hammons, C. (2001). Special but unequal: Race and
special education. In C. E., Finn Jr., A. J. Rotherham, & C. R.
Hokanson Jr. (Eds.), Rethinking special education for a new century (pp.
85-110). Washington, DC: The Progressive Policy Institute & The
Thomas B. Fordham Foundation.
Ladson-Billings, G. (1994). The dreamkeepers: Successful teachers
of African American children. San Francisco: Jossey-Bass.
Ladson-Billings, G. (1995). But that's just good teaching! The
case for culturally relevant pedagogy. Theory into Practice, 34(3),
Ladson-Billings, G., & Tate, W. (1995). Toward a critical race
theory of education. The Teachers College Record, 97(1), 47-68.
Larry P. v. Riles, 343F. Supp. 1306 (N.D. Cal. 1972), aff'd
502 F. 2d 963 (9th Cir. 1974); 495 F. Supp. 926 (N.D. Cal. 1979),
aff'd 793 F. 2d 969 (9th Cir. 1984).
Losen, D. J., & Orfield, G. (2002). Racial inequity in special
education. Cambridge, MA: Harvard Education Press.
Losen, D. J., & Welner, K. G. (2001). Disabling discrimination
in our public schools: Comprehensive legal challenges to inappropriate
and inadequate special education services for minority children. Harvard
Civil Rights--Civil Liberties Law Review, 36(2), 407-460.
Lowery, C. D., & Marszalek, J. F. (1992). Encyclopedia of
African American civil rights: From emancipation to the present.
Westport, CT: Greenwood Press.
MacMillan, D. L., & Lopez, M. F. (1996). Comparison of students
nominated for prereferral interventions by ethnicity and gender. Journal
of Special Education, 30(2), 133-152.
MacMillan, D. L., & Reschly, D. J. (1998). Overrepresentation
of minority students: The case for greater specificity or
reconsideration of the variables examined. Journal of Special Education,
Madaus, G. F., & Clarke, M. (2001). The adverse impact of high
stakes testing on minority students: Evidence from 100 years of test
data. In G. Orfield & M. Kornhaber (Eds.), Raising standards or
raising barriers: Inequality and high stakes testing in public education
(pp. 85-106). New York: The Century Foundation
McLeskey, J., Henry, D., & Axelrod, M. I. (1999). Inclusion of
students with learning disabilities: An examination of data from reports
to congress. Exceptional Children, 66, 55-66.
McLloyd, V. C. (1998). Socioeconomic disadvantage and child
development. American Psychologist, 53, 185-204.
Mehan, H. (1992). Understanding inequity in schools: The
contribution of interpretive studies. Sociology of Education, 65, 1-20.
Mehan, H., Hertweck, A., & Meihls, J. L. (1986). Handicapping
the handicapped: Decision making in students' educational careers.
Stanford, CA: Stanford University Press.
Mercer, J. (1973). Labeling the mentally retarded. Berkeley:
University of California Press.
Mills v. Board of Education of the District of Columbia, 384 F.
Supp. 866 (1972).
National Alliance of Black School Educators. (2002). Addressing
over-representation of African American students in special education:
The prereferral intervention process. Washington, DC: National Alliance
of Black School Educators.
National Association of Secondary School Principals. (2000,
February). Statement on civil rights implications of zero tolerance
programs. Testimony presented to the United States Commission on Civil
Rights, Washington, D.C.
National Center on Culturally Responsive Educational Systems
(NCCRESt). (2006). Disproportionality by race and disability 2003-2004
[Data file]. Retrieved February 23, 2006, from National Center on
Culturally Responsive Educational Systems Web site:
Oakes, J. (1982). The reproduction of inequity: The content of
secondary school tracking. The Urban Review, 14, 107-120.
Oakes, J., Ormseth, T., Bell, R., & Camp, P. (1990).
Multiplying inequalities: The effects of race, social class, and
tracking on opportunities to learn mathematics and science. Santa
Monica, CA: Rand.
Orfield, G., & Eaton, S. E. (1996). Dismantling desegregation:
The quiet reversal of Brown v. Board of Education. New York: New Press.
Ortiz, A. A. (1997). Learning disabilities occurring concomitantly
with linguistic differences. Journal of Learning Disabilities, 30,
Oswald, D., Coutinho, M. J., & Best, A. M. (2002). Community
and school predictors of overrepresentation of minority children in
special education. In D. J. Losen & G. Orfield (Eds.), Racial
inequity in special education (pp. 1-13). Cambridge, MA: Harvard Civil
Oswald, D. P., Coutinho, M. J., Best, A. M., & Nguyen, N.
(2001). Impact of sociodemographic characteristics on the identification
rates of minority students as having mental retardation. Mental
Retardation, 39(5), 351-367.
Oswald, D. P., Coutinho, M. J., Best, A. M., & Singh, N. N.
(1999). Ethnic representation in special education: The influence of
school related economic and demographic variables. The Journal of
Special Education, 32, 194-206.
Parrish, T. (2002). Racial disparities in the identification,
funding, and provision of special education. In D. J. Losen & G.
Orfield (Eds.), Racial inequity in special education (pp. 15-37).
Cambridge, MA: Harvard Education Press.
PASE (Parents in Action on Special Education v. Hannon, 506 F.
Supp. 831 (D.N.D.I. 1980).
Patton, J. M. (1998). The disproportionate representation of
African Americans in special education: Looking behind the curtain for
understanding and solutions. The Journal of Special Education, 32(1),
Peske, H. G., & Haycock, K. (2006). Teaching inequity: How poor
and minority students are shortchanged on teacher quality. Washington,
DC: Education Trust.
Plessy v. Ferguson, 163 U.S. 537 (1896).
Prieto, A. G., & Zucker, S. H. (1981). Teacher perception of
race as a factor in the placement of behaviorally disordered children.
Behavioral Disorders, 7, 34-38.
Raffaele Mendez, L. M., & Knoff, H. M. (2003). Who gets
suspended from school and why: A demographic analysis of schools and
disciplinary infractions in a large school district. Education and
Treatment of Children, 26, 30-51.
Rausch, M. K., & Skiba, R. J. (2006). Examining patterns of
disciplinary disproportionality by disability status and racial group.
Bloomington, IN: Center for Evaluation & Education Policy.
Rebell, M. A. (1999). Fiscal equity litigation and the democratic
imperative. Equity and Excellence in Education, 32, 5-18.
Reschly, D. J. (1996). Disproportionate minority representation in
general and special education programs: Patterns, issues, and
alternatives. Des Moines: Iowa Department of Education Bureau of Special
Reynolds, C. R. (2000). Why is psychometric research on bias in
mental testing so often ignored? Psychology, Public Policy, and Law, 6,
Ritter, M. K., & Skiba, R. J. (2006). Local equity action
development (LEAD). (Education Policy Brief Vol. 4, No. 9). Bloomington,
IN: Center for Evaluation & Education Policy.
Rury, J. L. (2002). Education and social change: Themes in the
history of American schooling. Mahwah, NJ: Lawrence Erlbaum.
Salend, S. J., Garrick Duhaney, L. M., & Montgomery, W. (2002).
A comprehensive approach to identifying and addressing issues of
disproportionate representation. Remedial and Special Education, 23(5),
Serna, L. A., Forness, S. R., & Nielsen, M. E. (1998).
Intervention versus affirmation: Proposed solutions to the problem of
disproportionate minority representation in special education. Journal
of Special Education, 32(1) 48-51.
Serwatka, T. S., Deering, S., & Grant, P. (1995).
Disproportionate representation of African Americans in emotionally
handicapped classes. Journal of Black Studies, 25, 492-506.
Shaw, S. R., & Braden, J. P. (1990). Race and gender bias in
the administration of corporal punishment. School Psychology Review, 19,
Sheets, R. H. (2005). Diversity pedagogy: Examining the role of
culture in the teaching-learning process. Boston: Pearson/Allyn &
Shepard, L. A. (1987). The case for bias in tests of achievement
and scholastic aptitude. In S. Modgil & C. Modgil (Eds.), Arthur
Jensen: Consensus and controversy (pp. 177-190). New York: Falmer Press
Shinn, M. R., Tindal, G. A., & Spira, D. A. (1987). Special
education referrals as an index of teacher tolerance: Are teachers
imperfect tests? Exceptional Children, 54, 32-40.
Skiba, R. J., Bush, L. D., & Knesting, K. K. (2002). Culturally
competent assessment: More than nonbiased tests. Journal of Child and
Family Studies, 11(1), 61-78.
Skiba, R. J., Michael, R. S., Nardo, A. C., & Peterson, R.
(2002). The color of discipline: Sources of racial and gender
disproportionality in school punishment. Urban Review, 34, 317-342.
Skiba, R. J., Poloni-Staudinger, L., Gallini, S., Simmons, A. B.,
& Feggins-Azziz, L. R. (2006b). Disparate access: The
disproportionality of African American students with disabilities across
educational environments. Exceptional Children, 72, 411-424.
Skiba, R. J., Poloni-Staudinger, L., Simmons, A. B., Feggins, L.
R., & Chung, C. G. (2005). Unproven links: Can poverty explain
ethnic disproportionality in special education? The Journal of Special
Education, 39(3), 130-144.
Skiba, R. J., & Rausch, M. K. (2006). Zero tolerance,
suspension, and expulsion: Questions of equity and effectiveness. In C.
M. Evertson & C. S. Weinstein (Eds.), Handbook of classroom
management: Research, practice, and contemporary issues (pp. 1063-1089).
Mahwah, NJ: Lawrence Erlbaum.
Skiba, R. J., Simmons, A., Ritter, S., Kohler, K., Henderson, M.,
& Wu, T. (2006a). The context of minority disproportionality:
Practitioner perspectives on special education referral. Teachers
College Record, 108(7), 1424-1459.
Sleeter, C. E., & Grant, C. A. (1991). Race, class, gender and
disability in current textbooks. In M. W. Apple & L. K.
Christian-Smith (Eds.), The politics of the textbook (pp. 78-110). New
York: Routledge & Chapman-Hall.
Smedley, A. (2007). Race in North America: Origin and evolution of
a worldview (3rd ed.). Boulder, CO: Westview Press.
Smith, A., & Kozleski, E. B. (2005). Witnessing Brown: Pursuit
of an equity agenda in American education. Remedial and Special
Education, 26(5), 270-280.
Sugai, G., Lewis-Palmer, T., & Hagan-Burke, S. (2000). Overview
of the functional behavioral assessment process. Exceptionality, 8(3),
Terman, L. M. (1916). The measurement of intelligence. Boston:
Tobias, S., Cole, C., Zibrin, M., & Bodlakova, V. (1982).
Teacher-student ethnicity and recommendations for special education
referrals. Journal of Educational Psychology, 74(1), 72-76.
Tobias, S., Zibrin, M., & Menell, C. (1983). Special education
referrals: Failure to replicate student-teacher ethnicity interaction.
Journal of Educational Psychology, 75, 705-707.
Tomlinson, J. R., Acker, N., Canter, A., & Lindborg, S. (1978).
Minority status, sex, and school psychological services. Psychology in
the Schools, 14(4), 456-460.
Townsend, B. L. (2000). The disproportionate discipline of African
American learners: Reducing school suspensions and expulsions.
Exceptional Children, 66, 381-391.
Trent, S. C., Kea, C. D., Oh, K., (2008). Preparing preservice
educators for cultural diversity: How far have we come? Exceptional
Children, 74, 328-350.
Trepagnier, B. (2006). Silent racism: How well-meaning White people
perpetuate the racial divide. Boulder, CO: Paradigm.
U.S. Census Bureau. (2001). Poverty in the United States: 2002
(Series P60-222). Washington, DC: U.S. Government Printing Office.
U.S. Department of Education, Office of Special Education Programs
(OSEP). (2002). 24th Annual Report to Congress on the Implementation of
the Individuals with Disabilities Education Act. Washington, De: U.S.
Government Printing Office.
U.S. Department of Education, Office of Special Education Programs
(OSEP). (2006). 26th annual report to Congress on the implementation of
the Individuals with Disabilities Education Act, 2004. Washington, De:
U.S. Department of Education, Office of Special Education Programs
(OSEP). Disproportionality and Overidentification [Policy Brief].
Retrieved February 27, 2007 from http://idea.ed.gov/explore/view/p/
Valencia, R. R., & Suzuki, L. A. (2000). Intelligence testing
and minority students: Foundations, performance factors, and assessment
issues. Thousand Oaks, CA: Sage.
Wang, M. C., Haertel, G. D., & Walberg, H. J. (1997). Learning
influences. In H. J. Walberg & G. D. Haertel (Eds.), Psychology and
educational practice (pp. 199-211). Berkeley, CA: McCutchan.
Westat. (2003). Special populations study final report. Washington,
De: United States Department of Education, Office of Special Education
Westat. (2004). Summary of task force meeting on racial/ethnic
disproportionality in special education. Washington, DC: Author.
Westat. (2005). Methods for assessing racial/ethnic
disproportionality in special education: A technical assistance guide.
Washington, DC: U.S. Department of Education, Office of Special
Education Programs. Retrieved October 5, 2006, from
Williams, P. (2007). Disproportionality and overrepresentation.
Building the legacy: Training curriculum on IDEA 2004 (Module 5 in the
National Dissemination Center for Children with Disabilities (NICHCY).
Washington, DC: NICHCY. Retrieved July 20, 2007, from
Wright, P., & Santa Cruz, R. (1983). Ethnic composition of
special education programs in California. Learning Disability Quarterly,
Wu, S. C., Pink, W. T., Crain, R. L., & Moles, O. (1982).
Student suspension: A critical reappraisal. The Urban Review, 14,
Ysseldyke, J. E., Algozzine, B., Richey, L., & Graden, J.
(1982). Declaring students eligible for learning disability services:
Why bother with the data? Learning Disability Quarterly, 5, 37-44.
Zhang, D., & Katsiyannis, A. (2002). Minority representation in
special education: A persistent challenge. Remedial and Special
Education, 23, 180-187.
RUSSELL J. SKIBA
ADA B. SIMMONS
ASHLEY C. GIBB
M. KAREGA RAUSCH
The preparation of this manuscript was made possible by a
discretionary grant from the Indiana Department of Education Division of
Exceptional Learners. Opinions expressed herein do not necessarily
reflect the opinion of the Indiana Department of Education.
Correspondence about this article and requests for reprints should
be sent to Russell J. Skiba, Center for Evaluation and Education Policy,
509 E. 3rd St., Bloomington, IN 47401 (e-mail: email@example.com).
RUSSELL J. SKIBA (CEC IN Federation), Professor, Counseling &
Educational Psychology and Director of the Equity Project at Indiana
University; ADA B. SIMMONS; Executive Associate Director, Indiana
University School of Education Center for Research and P-16
Collaboration. SHANA RITTER, Project Coordinator; ASHLEY C. GIBB,
Graduate Research Assistant; M. KAREGA RAUSCH, Graduate Research
Assistant; JASON CUADRADO, Graduate Research Assistant; and CHOONG-GEUN
CHUNG, Statistician, The Equity Project at Indiana University; Center
for Evaluation and Education Policy, Indiana University, Bloomington.
Provisions of IDEA 2004 With Respect to Minority
Disproportionality in Special Education
* States must have policies and procedures in
place to prevent the inappropriate overidentification
or disproportionate representation by race
or ethnicity of students with disabilities, including
children with a particular impairment.
[34 CFR 300.173] [20 U.S.C. 1412(a)(24)]
* Each State that receives Part B funds must
collect and examine special education data to
determine if significant disproportionality based
on race and ethnicity is occurring at the State or
local level with respect to disability, placement
in particular settings or disciplinary actions, including
suspensions and expulsions.
[34 CFR 300.646(a)] [20 U.S.C. 1418(d)(1)]
* If significant disproportionality is found, States
must provide for a review and, if appropriate,
revision of policies, practices, and procedures
used in identification and placement. Local
education agencies identified with significant
disproportionality must devote the maximum
amount of funds (15% of Part B) to comprehensive
early intervening services directed
particularly but not exclusively towards children
from groups found to be disproportionately
represented. Changes to policies, practices, and
procedures must be publicly reported by the
[34 CFR 300.646(b)] [20 U.S.C. 1418(d)(2)]
* States must disaggregate data on suspension and
expulsion rates by race and ethnicity, comparing
those rates either among local education
agencies in the state, or to the rates of non-disabled
children within those agencies.
[34 CFR 300.646(b)] [20 U.S.C. 1418(d)(2)]
* States must monitor local education agencies
using quantifiable indicators of disproportionate
representation of racial and ethnic groups in
special education and related services, to the
extent the representation is the result of
[34 CFR 300.600(d)(3)]
[20 U.S.C. 1416(a)(3)(C)]
Note. Adapted from Disproportionality and Overidentification
[Policy Brief], by the U.S. Department
of Education, Office of Special Education Programs.
Retrieved February 27, 2007 from http://idea.ed.gov/
Risk Ratios for All Disability Categories and Racial/Ethnic Categories
From the 26th Annual Report to Congress
Indian/ Asian/ Black
Alaska Pacific (not
Disability Native Islander Hispanic)
Specific learning disabilities 1.53 0.39 1.34
Speech/language impairments 1.18 0.67 1.06
Mental retardation 1.10 0.45 3.04
Serious emotional disturbance 1.30 0.28 2.25
Multiple disabilities 1.34 0.59 1.42
Hearing impairments 1.21 1.20 1.11
Orthopedic impairments 0.87 0.71 0.94
Other health impairments 1.08 0.35 1.05
Visual impairments 1.16 0.99 1.21
Autism 0.63 1.24 1.11
Deaf-blindness 1.93 0.94 0.84
Traumatic brain injury 1.29 0.59 1.22
Developmental delay 2.89 0.68 1.59
All disabilities 1.35 0.48 1.46
Disability Hispanic Hispanic)
Specific learning disabilities 1.10 0.86
Speech/language impairments 0.86 1.11
Mental retardation 0.60 0.61
Serious emotional disturbance 0.52 0.86
Multiple disabilities 0.75 0.99
Hearing impairments 1.20 0.81
Orthopedic impairments 0.92 1.15
Other health impairments 0.44 1.63
Visual impairments 0.92 0.94
Autism 0.53 1.26
Deaf-blindness 1.04 1.03
Traumatic brain injury 0.62 1.21
Developmental delay 0.43 1.06
All disabilities 0.87 0.92
Note. Drawn from U.S. Department of Education, Office of Special
Education and Rehabilitative Services (2006). 26th annual report to
Congress on the implementation of the Individuals With Disabilities
Education Act, 2004. Washington, DC: Westat. Risk ratios were
calculated by dividing the (prerounded) risk index for the racial/
ethnic group by the risk index for all other racial/ethnic groups
combined for students ages 6 through 21 with disabilities, by
race/ethnicity and disability category.