Discussion

264 Spring 2008

Special education was borne out of, and owes a debt to, the civil rights movement. That is, the inspiration for, and the strate- gies used by, advocates whose

efforts resulted in the first national special educa- tion legislation emerged from the struggles of the civil rights movement (Smith & Kozleski, 2005). Concerns about racial inequity were central to lit- igation (e.g., Mills v. Board of Education, 1972) that led to the promulgation of the first special

education legislation (Individuals With Disabili- ties Education Act, IDEA, Public Law No. 94- 142, 1975). Thus, it is highly ironic that racial disparities in rates of special education service re- main one of the key indicators of inequity in our nation's educational system.

The disproportionate representation of mi- nority students is among the most critical and en- during problems in the field of special education. Despite court challenges (Larry P. v. Riles, 1972/1974/1979/1984; PASE v. Hannon, 1980);

Vol. 74, No. 3, pp. 264-288. ©2008 Council for Exceptional Children.

Achieving Equity in Special Education: History, Status, and Current Challenges

RUSSELL J. SKIBA

ADA B. SIMMONS

SHANA RITTER

ASHLEY C. GIBB

M. KAREGA RAUSCH

JASON CUADRADO

CHOONG-GEUN CHUNG

Indiana University

ABSTRACT: Among the most-longstanding and intransigent issues in the field, the disproportionate representation of minority students in special education programs has its roots in a long history of educational segregation and discrimination. Although national estimates of disproportionality have been consistent over time, state and local estimates may show varying patterns of disproportionality. A number of factors may contribute to disproportionality, including test bias, poverty, special edu- cation processes, inequity in general education, issues of behavior management, and cultural mis- match/cultural reproduction. This article provides a report on the history, measurement, status, and factors contributing to disproportionate representation in special education, and offers recommen- dations based on an understanding of racial and ethnic disparities in special education as a multi- ply determined phenomenon.

Exceptional Children

federal reports (Donovan & Cross, 2002; Heller, Holtzman, & Messick,1982); and abundant re- search 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 ed- ucation has persisted. Indeed, although consis- tently documented, it is fair to say that the full complexity of minority disproportionality has not yet been understood, nor has a clear or compre- hensive picture emerged concerning the causes of disproportionality (Donovan & Cross; Harry & Klingner). To address the issue of disproportion- ate minority placement, the 1997 reauthorization of the Individuals With Disabilities Education Act (IDEA 97, Public Law No. 105-17) stressed the importance of efforts to “prevent the intensifi- cation 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 Disabil- ities Education Improvement Act (IDEA 2004, Public Law No. 108-446).

This article provides a status report on mi- nority disproportionality in special education. What is the historical context for current prob- lems of racial/ethnic disparity? What are the cur- rent levels of disproportionality and how are those measured? What are the possible causes and con- ditions 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 inter- pretation, and (c) culturally responsive interven- tion and evaluation.

H I S T O R Y : A B R I E F S Y N O P S I S

O F A V E R Y O L D P R O B L E M

The initial identification of the problem of dis- proportionate representation of some groups, most notably African American students, in spe- cial education is often traced back to Dunn’s (1968) classic critique of the field. Yet the prob- lem itself has its roots far deeper, in the problems

of oppression and discrimination that have char- acterized race relations throughout American his- tory (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 sepa- rate 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 burn- ing 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 intel- lectually inferior, and that the purity of the supe- rior races should be preserved by vigorously segregating the “feeble-minded” (Terman, 1916). From Reconstruction until the 1950s, the domi- nant view of African American education was that it was intended not to educate for equal citizen- ship, but rather for the lower ranked positions that it was assumed African Americans would oc- cupy (Rury, 2002).

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 educa- tion, Dunn (1968) suggested that the overrepre- sentation of ethnic and language minority students in self-contained special education class- rooms raised significant civil rights and educa- tional concerns. Mercer (1973), highlighting ethnic differences in rates of special education ser- vice as part of her critique of the “6-hour” or situ- ationally retarded child, found that public schools tended to identify more children as mentally re- tarded than any other child service setting.

In the wake of Brown v. Board of Education (1954) and legislative action to provide equal ac- cess 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.

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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 stan- dardized testing and the reduced educational op- portunity 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 issue.

In the 1980s, examination of the U.S. De- partment of Education Office for Civil Rights survey data began to produce estimates of the ex- tent 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 disproportionality re- search has seen a sharper focus on the forces that shape and maintain disproportionate representa- tion (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 in- creased significantly with the inclusion of provi- sions 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 dis- proportionate representation is found. One of the most significant new requirements under IDEA 2004 is that local educational agencies (LEAs) de- termined 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 regu- lations, and discretion is left to the states to develop the quantifiable indicators of dispropor- tionality used for determining significance.

M E A S U R E M E N T I S S U E S I N

D I S P R O P O R T I O N A L I T Y

Disproportionality may be defined as the repre- sentation of a group in a category that exceeds our expectations for that group, or differs substan- tially 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 cate- gory or setting (e.g., underrepresentation in gen- eral education settings, gifted education, or visual impairment). Although the concept of dispropor- tionate representation seems relatively straightfor- ward, 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 (com- position 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).

CO M P O S I T I O N IN D E X

The most intuitive method of measurement of disproportionality, the composition index (CI; Donovan & Cross, 2002), compares the propor- tion of those served in special education repre- sented by a given ethnic group with the proportion that group represents in the popula- tion or in school enrollment; that is, it provides a measure of representation in the target phe- nomenon 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 & Cross).

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 percent- age of the group in question (e.g., for an overall African American enrollment of 17%, dispropor- tionality 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 ex- tremes of the scale may not have the same mean- ing 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 ex- ceeds 92%, making it impossible to find overrep- resentation (e.g., 92% + 9.2% = 101.2% using Chinn & Hughes’ criteria).

RI S K IN D E X A N D RE L AT I V E RI S K RAT I O

An alternative approach to describing dispropor- tionality 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 particu- larly 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

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F I G U R E 1

Provisions of IDEA 2004 With Respect to Minority Disproportionality in Special Education

• States must have policies and procedures in place to prevent the inappropriate overidentifi- cation or disproportionate representation by race or ethnicity of students with disabilities, includ- ing 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, in- cluding 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 compre- hensive 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 LEA. [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 inappropriate identification. [34 CFR 300.600(d)(3)] [20 U.S.C. 1416(a)(3)(C)]

Note. Adapted from Disproportionality and Over- identification [Policy Brief ], by the U.S. Department of Education, Office of Special Education Programs. Retrieved February 27, 2007 from http://idea.ed.gov/ explore/view/p/%2Croot%2Cdynamic%2CTopical Brief%2C7%2C

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 nonoc- currence data.

There are also limitations and issues of inter- pretation 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 appropri- ate 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 un- derrepresentation in special education impossible (Westat, 2004). The U.S. Department of Educa- tion, Office of Special Education Programs rec- ommends using all others as the denominator in the calculation of disproportionality (Westat, 2005), but the use of either Whites and All Oth- ers 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 dis- proportionality data, the U.S. Department of Ed- ucation, 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 instruc- tion 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 undefined.

Although there has been progress in recent years in standardizing the measurement of dispro- portionality, 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 con- ditions (Davies, Crombie, & Tavakoli, 1998). Further, the issue of a definitive criteria in deter- mining disproportionality is complex. The framers of IDEA 2004 may have deliberately in- tended to avoid cutoffs identifying significant dis- proportionality in order to allow responsiveness to regional and local variation; rigidly defined crite- ria 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

PAT T E R N S O F DI S P R O P O RT I O N A L I T Y

Analyses of data from the U.S. Department of Ed- ucation, Office for Civil Rights (OCR; e.g., Chinn & Hughes, 1987; Donovan & Cross, 2002; Finn, 1982) have revealed consistent patterns of dispro- portionality. African American students are typi- cally 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 An- nual Report to Congress on the Implementation of the Individuals With Disabilities Education Act (U.S. Department of Education, 2006; see Table 1) in- dicates that American Indian/Alaska Native stu- dents 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 stu- dents, and Latino students were somewhat more likely to receive services in the category of hearing

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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 disproportion- ality have been noted. Disproportionate represen- tation 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 over- representation tend to increase as a minority group constitutes a relatively high percentage of their states’ population. Finn (1982) reported a com- plex 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), dispro- portionality was greatest when minority enroll-

ment was 30% or less. Finally, states may show ev- idence of disproportionality in categories that ap- pear proportionate at the national level, and local school districts may show evidence of dispropor- tionality 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 spe- cial education (Artiles, Rueda, Salazar & Hi- gareda, 2002; Wright & Santa Cruz, 1983). National data, however, show that the most com- mon 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). Exami-

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T A B L E 1

Risk Ratios for All Disability Categories and Racial/Ethnic Categories From the 26th Annual Report to Congress

American Indian/ Asian/ Black White Alaska Pacific (not (not

Disability Native Islander Hispanic) Hispanic Hispanic)

Specific learning disabilities 1.53 0.39 1.34 1.10 0.86

Speech/language impairments 1.18 0.67 1.06 0.86 1.11

Mental retardation 1.10 0.45 3.04 0.60 0.61

Serious emotional disturbance 1.30 0.28 2.25 0.52 0.86

Multiple disabilities 1.34 0.59 1.42 0.75 0.99

Hearing impairments 1.21 1.20 1.11 1.20 0.81

Orthopedic impairments 0.87 0.71 0.94 0.92 1.15

Other health impairments 1.08 0.35 1.05 0.44 1.63

Visual impairments 1.16 0.99 1.21 0.92 0.94

Autism 0.63 1.24 1.11 0.53 1.26

Deaf-blindness 1.93 0.94 0.84 1.04 1.03

Traumatic brain injury 1.29 0.59 1.22 0.62 1.21

Developmental delay 2.89 0.68 1.59 0.43 1.06

All disabilities 1.35 0.48 1.46 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.

nation of Table 1 suggests Hispanic overrepresen- tation in Hearing Impairments and perhaps LD; underrepresentation is a much more common finding across a number of disability categories.

Discrepancies between findings of overrepre- sentation for African American students and un- derrepresentation 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 stu- dents, where overrepresentation in certain cate- gories 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 (Par- rish, 2002). Formal studies to evaluate these dis- crepancies have been limited (Klingner, Artiles, & Mendez Barletta, 2006). The difficulty in accu- rately distinguishing between language acquisi- tion difficulties for English Language Learners and a language disability also complicates identifi- cation and assessment issues for Latino students (Barrera, 2006; Ortiz, 1997).

DI S P R O P O RT I O N A L I T Y I N ED U C AT I O N A L

SE T T I N G S

Although less well researched, available data demonstrates that students of color, especially African Americans, are overrepresented in more restrictive educational environments and under- represented in less restrictive settings (Fierros & Conroy, 2002; Skiba, Poloni-Staudinger, Gallini, Simmons, & Feggins-Azziz, 2006b). Given the conceptual importance of inclusion and the dra- matic increases in recent years in general educa- tion placements for students with disabilities (McLeskey, Henry, & Axelrod, 1999), it could be argued that disproportionality with respect to ac- cess to less restrictive educational environments may be more important conceptually than dispar- ities in disability category (Skiba et al., 2006b).

Different interpretations might well be ap- plied to findings of racial disparities in educa- tional settings. It might be presumed, for example, that “differences in placement by race/ethnicity may reflect the disproportional rep- resentation of some minority groups in disability

categories that are predominately served in more restrictive settings” (U.S. Department of Educa- tion, 2002, p. III–45). Yet failure to find such a pattern may suggest that disproportionality in special education settings is driven, to some ex- tent, by systemic responses, such as educators who may mistake cultural differences for cogni- tive or behavioral disabilities (Harry, 2008; Os- wald 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 cate- gories 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 re- strictive settings, or underrepresented in the gen- eral education setting. Further, disproportionality in placement increased as the severity of the dis- ability 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 cate- gories such as learning disabilities (RR = 3.20) or speech and language (RR = 7.66). Such results do not support the hypothesis that minority dispro- portionality in educational environments is sim- ply 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.

C A U S E S O F D I S P R O P O R T I O N A T E

S P E C I A L E D U C A T I O N

R E P R E S E N T A T I O N

A fairly extensive database has consistently docu- mented African American disproportionality in special education service and across educational environments, although findings regarding Latino disproportionality are less extensive and less con- sistent. 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 pos- sible conditions or causes related to special educa-

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tion disproportionality have been explored, begin- ning in the 1970s with test bias.

PS Y C H O M E T R I C TE S T BI A S

In the 1970s, the issue of psychometric test bias played a central role in court cases concerning mi- nority disproportionality, specifically overrepre- sentation. 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 assess- ment has yielded misclassification (Bersoff, 1981). The possibility of bias against minorities in stan- dardized 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). Exten- sive reviews of that literature have reached somewhat different conclusions.

Perhaps the most influential review of cul- tural bias in psychometric tests was conducted by Jensen (1980). That review and others (Brown, Reynolds, & Whitaker, 1999; Cole, 1981) con- cluded 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 under- sampling 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, compar- isons of African American and White perfor- mance 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 ar- gued that the case against test bias has been con- clusively 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 con- clusions, however. Valencia and Suzuki (2000) noted that, because the majority of studies on test bias were conducted in the 1970s and 1980s, al- most 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 con- tent 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 pri- marily Mexican Americans, but also African Americans and Asian Americans) showed evi- dence for bias in predictive validity.

In particular, recent research has pointed to possible sources of item bias. Shepard (1987), ar- guing that analysis at the individual item level may be insufficient for exploring test bias, sug- gested that more sophisticated methodologies, such as item response theory, have yielded pat- terns 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 ques- tions 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 tak- ers. Further research is necessary to determine to what extent such processes may apply in the con- struction of standardized tests of intelligence or achievement used in special education assessment.

Finally, language differences and examiner ef- fects 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

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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 unfa- miliarity, defined in part as membership in a dif- ferent group from the examinee, had a significant impact on standardized test performance. In par- ticular, the examinees of low socioeconomic status (SES) were more significantly affected than exam- inees of higher SES.

SU M M A RY

An extensive literature exploring psychometric test bias has, in general, tended not to identify a level of cultural bias in standardized tests of intel- ligence 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 incon- sistent 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 premature.

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 ge- netic. 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 avail- able 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 socioe- conomic 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).

SO C I O-DE M O G R A PH I C FAC TO R S : TH E IN F LU E N C E O F POV E RT Y

A second factor that might contribute to a dispro- portionate rate of representation in special educa- tion among students of color are socio- demographic factors associated with economic disadvantage. One might expect that because mi- nority 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 mi- nority students, thus increasing the risk of minor- ity referral to special education.

[F]indings that tests are unbiased does not mean that racial differences in IQ scores are inherent or genetic.

A number of demographic factors related to geographical location and SES have been shown to be associated with student educational achieve- ment or early cognitive development. These in- clude neighborhood and housing stability (Ainsworth, 2002); the student’s home environ- ment (Caldas & Bankston, 1999); family health care (Kramer, Allen, & Gergen, 1995); and geo- graphic 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 con- text of poverty; deep and persistent poverty con- sistently predicts more deleterious effects. The 2002 National Research Council panel exploring disproportionality in special education (Donovan & Cross, 2002) affirmed that biological and so- cial/environmental factors that disproportionately affect minority students have been found to con- tribute to poor cognitive and behavioral out- comes, and they recommended a national commitment to early intervention to offset so- cioeconomic risk factors.

272 Spring 2008

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 per- sonnel (see e.g., Harry, Klingner, Sturges, & Moore, 2002; Skiba et al., 2006a).

Yet showing that poverty influences academic achievement is not the same thing as demonstrat- ing that poverty causes minority disproportional- ity in special education, Skiba et al. (2005) noted that developing a link between poverty and mi- nority disproportionality requires a series of logi- cal connections, not all of which are well-documented in the literature. Although there is a fairly strongly documented connection be- tween minority status and poverty (U.S. Census Bureau, 2001), direct links between poverty and academic and behavioral outcomes are not as im- pressive (Brooks-Gunn & Duncan, 1997). Nor do academic or social/behavioral problems neces- sarily predict special education eligibility, because the specific disability definitions of IDEA are in- tended to ensure that not all students with aca- demic 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 underachieve- ment, but of the specific types of learning and be- havior 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 con- tradict 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 & Katsiyan- nis, 2002); MR (Oswald, Coutinho, Best, & Nguyen, 2001); and ED (Oswald et al., 1999).

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 spe- cial 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 re- gression equations, poverty made a weak, inconsis- tent, and often counter-intuitive contribution to the prediction of disproportionality across a num- ber of disability categories. Where poverty made any contribution above and beyond race in pre- dicting disability identification, its primary effect was to magnify existing racial disparity.

Generalizations about the effects of poverty on parenting may also yield unwarranted assump- tions about families from groups overrepresented in special education. Although poverty has been shown to be associated with more negative par- enting styles (McLloyd, 1998), there is no evi- dence 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 educa- tors. Families of African American students were described as neglectful, incompetent, and dys- functional, often absent any firsthand knowledge of those families’ actual circumstances. Such de- scriptions also ignore significant cultural strengths in African American and Latino communities, such as the involvement and expertise of extrafa- milial adults, who may act as protective factors despite economic disadvantage (Harry & Kling- ner, 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 educa- tion. 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

273Exceptional Children

disparities in special education. In particular, al- though 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 available data.

Finally, regardless of the relationship among poverty, academic achievement, and racial dispari- ties, mechanisms for the negative effects of poverty remain unclear. It is often presumed that economic disadvantage affects educational readi- ness 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 educa- tion service must also be considered.

UN E QUA L OP P O RT U N I T Y I N GE N E R A L

ED U C AT I O N

One of the most consistent findings in educa- tional research is that students achieve in direct proportion to their opportunity to learn (Wang, Haertel, & Walberg, 1997). It might well be ex- pected that students whose educational opportu- nities are limited will be more likely to be referred for special education services (Artiles & Trent, 1994; Harry, 1994). Differential access to educa- tional resources has been consistently demon- strated for some minority groups in a number of areas (Kozol, 2005; Peske & Haycock, 2006).

Of the possible links between general educa- tion practices and special education dispropor- tionality, 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, overrepre- sentation of African American students in the emotionally disturbed category decreased. Simi- larly, 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 per- centage of more than 60%.

More generally, however, inequity in the quality and quantity of educational resources has been extensively documented. Curricula and in- structional presentation appear to disfavor work- ing-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 segrega- tion and re-segregation (Katznelson, 2005; Or- field & 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 back- grounds 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 & Haycock).

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 instruc- tion 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 stu- dents of color in low SES communities are at greater risk for poor quality educational experi- ences that undermine their academic achievement.

It is reasonable to presume that factors that limit educational opportunity will impact educa- tional achievement, thereby increasing the risk for

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special education referral (Skiba, Bush, & Knest- ing, 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 un- derstudied. Although the link between teacher demographics and special education dispropor- tionality has been explored to some extent (Lad- ner & 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 ed- ucation referral and eligibility determination have yet to be directly studied.

SPE C I A L ED U C AT I O N EL I G I B I L I T Y A N D

DE C I S I O N-MA K I N G PR O C E S S E S

Disparities in special education could be influ- enced by inadequacies in practice or bias gener- ated at the level of special education referral and decision making. Although this possibility has re- ceived some research attention, the pattern of re- sults is somewhat unclear.

Referral. Available data suggest that racial dis- parities in the classification of students as disabled begin at the stage of initial classroom referral. Re- viewing records of students referred for special ed- ucation 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 edu- cation than White students.

Examination of prereferral decision making by teachers has yielded mixed results. Bahr, Fuchs, Stecker, and Fuchs (1991) found that, despite rel- atively minor differences in descriptions of aca- demic 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) com-

pared 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 re- searchers to conclude that teachers may wait to refer Black students until their academic or be- havioral 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 repre- sentation: Schools using an instructional consul- tation model significantly reduced both their overall rate of special education referral and iden- tification and reduced racial/ethnic discrepancies in rates of referral and identification.

Assessment and Decision Making. Investiga- tions of the possibility of bias during the assess- ment and decision-making process have not been undertaken recently and present a somewhat con- flicting picture. Analogue studies using a case study vignette (e.g., Prieto & Zucker, 1981) found a greater willingness among both general and spe- cial education teachers to recommend minority students for special education given identical refer- ral information. In two studies using a similar sim- ulated 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 educa- tion identification in the first but not the second study. Reviewing tapes of case review teams mak- ing 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 decision- making processes and found that minority stu- dents were referred more often, that their parents were contacted significantly less often to partici- pate in the special education process, and that the recommendations to minority parents were more restrictive and less comprehensive than recom- mendations for nonminority parents.

275Exceptional Children

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 stu- dents received services for learning disabilities de- spite not meeting the LD discrepancy criteria for identification. Similarly, MacMillan and Reschly (1998) argued that up to half of all students identi- fied 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 conferenc- ing phase that may contribute to disproportional- ity, 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 consis- tency in this research, as well as the age of many of the studies, the extent to which current special education eligibility determination processes con- tribute to special education inequity is unclear. The most recent National Research Council (NRC) panel (Donovan & Cross, 2002) con- cluded that evidence of bias in the referral to placement process was mixed, but that the process has sufficient shortcomings as to be unable to en- sure that the correct students are being identified. Further, the panel contended that the entire pro- cess 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 special education.

BE H AV I O R A S T H E NE X U S O F RAC E A N D

DI S A B I L I T Y

Special education is, of course, not the only educa- tional domain in which students of color are dis-

proportionately 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 Ad- vanced 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 overrepre- sented 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 (Raf- faele Mendez & Knoff ), rates that were substantially higher than White male (25%) and White female (9.3%) middle school students. Dis- proportionality in school suspension has not been as consistently documented for Latino or other ethnic minority groups (Skiba & Rausch, 2006).

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 Princi- pals, 2000), race remains a significant predictor of suspension and expulsion, even when socioeco- nomic 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 differ- ences in reasons for suspension that have been found suggest that African American students re- ceive more severe punishments for less serious in- fractions (Shaw & Braden, 1990) or are referred to the office more frequently for more subjective

276 Spring 2008

reasons, such as disrespect or loitering (Skiba, Pe- terson, et al., 2002). Other explanations for disci- plinary disproportionality include the possible misinterpretation by classroom teachers of cultur- ally based behaviors (Townsend, 2000) or stereo- types regarding Black males that increase the likelihood of office referral (Ferguson, 2001).

There are also indications of racial dispropor- tionality in the application of the specific disci- plinary provisions of IDEA. A recent state report (Rausch & Skiba, 2006) found that about 3% of African American students with disabilities re- ceived at least one of the IDEA disciplinary provi- sions, a rate 2.8 times higher than all other students with disabilities. Further, the greatest racial disparities were found in the IDEA disci- plinary 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. Dispro- portionality 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 stu- dents 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 rea- sons (Gottlieb et al., 1991; MacMillan & Lopez, 1996). The nature and causes of disciplinary dis- proportionality represent an important avenue for further research on racial disparities in special ed- ucation.

CU LT U R A L MI S M ATC H A N D CU LT U R A L

RE P R O D U C T I O N

Emerging scholarship has conceptualized the dis- proportionate representation of minority students in special education, African American students in particular, as a symptom of a broader discon- nect between mainstream educational culture and the cultural orientations of communities of color. A number of scholars have argued that contempo-

rary mainstream educational systems, special edu- cation systems in particular (Patton, 1998), closely reflect the knowledge, values, interests, and cultural orientations of White, middle-class cultural groups (Delpit, 1995; King, 2005). Edu- cation that fails to explicitly teach the codes and rules necessary for successful participation in un- familiar cultural contexts (Delpit), does not con- nect knowledge produced in schools to students’ lived experiences (Ladson-Billings, 1994), or ig- nores the foundational role of culture in knowl- edge production (Sheets, 2005) may yield inadequate and inappropriate educational experi- ences for a range of cultural groups.

Notably, such knowledge is not well-repre- sented in mainstream scholarship (Trent et al., 2008). The intensive observation required by such research may make it more difficult to con- duct, compared to tests of more prevalent hy- potheses 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 ex- plored only a limited range of hypotheses for un- equal educational outcomes of African American and Latino students in general (King, 2005), and disproportionality in special education in particu- lar (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 ac- tions (Bowles & Gintis, 1976). Developed as an explanation of the perpetuation of social class hi- erarchies, the theoretical framework of cultural re- production 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 re- produce the status quo without being consciously aware of their contribution to inequity.

Recent ethnographic investigations have found clear evidence of reproductive processes

277Exceptional Children

that may well contribute to inequitable outcomes in special education. In an ethnographic study fo- cusing primarily on the role of school psycholo- gists in assessment decision making, Harry et al. (2002) found that although psychological testing is often perceived as an objective procedure de- signed to reduce the influence of individual judg- ment, 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 dis- proportionality 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 evi- dence of a number of institutional constraints and constitutive actions that appeared to influence the course of special education placement and pro- gramming for minority students, including poor teacher quality, large class sizes, arbitrary applica- tion of eligibility decision-making criteria, tardi- ness 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 in- equity in special education.

DI S P R O P O RT I O N A L I T Y A S A MU LT I P LY

DE T E R M I N E D PH E N O M E N O N

It should be apparent from the preceding discus- sion that there is no single simple explanation that appears to fit the data on special education dispro- portionality. Rather, minority disproportionality in special education appears to be multiply deter- mined, a product of a number of social forces in- teracting in the lives of children and the schools that serve them (see Trent et al., 2008).

Qualitative findings have highlighted the in- teracting forces that may set the context for and maintain racial disparities in special education. In an intensive case study interviewing teachers, prin- cipals, 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 poten- tially 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 needi- est 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 respon- dents seemed anxious to avoid talking about issues involving race or ethnicity.

The multidetermined nature of dispropor- tionality 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 cre- ate a pressure to refer low performing students who are predominantly minority to one of the few services available for students who are strug- gling (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 sug- gest that the causes of disparities will vary consid- erably for African Americans in Washington, DC or New York City and Latino students in Hous- ton or Los Angeles, and that both of these will show a pattern of disproportionality dramatically different from a predominantly White school sys- tem in a suburban or rural location.

278 Spring 2008

S T R A T E G I E S F O R R E D U C I N G

D I S P R O P O R T I O N A T E

R E P R E S E N T A T I O N

If disproportionality in special education is multi- ply determined, no single intervention strategy can be universally relied on to reduce racial dis- parity. Rather, complex causality clearly suggests the need for comprehensive and multifaceted as- sessment and intervention plans. In particular, the possibility that the determinants of dispropor- tionality are locale-specific suggests that remedia- tion 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 ap- proach is a process that moves from data collec- tion and examination, to interpretation, to culturally competent intervention and evaluation.

EX A M I N AT I O N O F T H E DATA

Data on disproportionality serves to establish both a baseline and a method of monitoring progress. The NRC recommended a national ef- fort 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 remedi- ation of disproportionality at the local level will be to disseminate practical methods of data col- lection analysis (Salend, Garrick Duhaney, & Montgomery, 2002). It seems likely that the con- tinuous feedback loop afforded by the examina- tion 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 represen- tation. If local efforts are to be made to address racial disparities, practical and efficient methods for calculating disparities will need to become available to school personnel.

DATA IN T E R P R E TAT I O N

A range of possible hypotheses might be brought to bear in interpreting a set of data indicating

racial disparity. On one end, hereditarian inter- pretations (e.g., Herrnstein & Murray, 1994) have tended to focus on inherent and genetic ex- planations of the achievement gap and group dif- ferences 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 in- teractions to maintain the power and privilege of the dominant group. It is clear that each of these theoretical orientations yields very different impli- cations for intervention.

[C]omplex causality clearly suggests the need for comprehensive and multi-faceted

assessment and intervention plans.

Indeed, the effectiveness of an intervention chosen to address disproportionate representation depends, to some degree, on the accuracy of diag- nosis of the causes of disparity. Early intervention appears to be an extremely promising interven- tion 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 eco- nomic disadvantage is at work. Early intervention would not be expected to address systemic failures or bias and would hence fail to address dispropor- tionality that is due to institutional inequity.

Unfortunately, interpretation of data on dif- ferential racial treatment itself appears to be con- ditioned 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; Pat- ton, 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 audi- ence confronting the data. Thus, educators and policy makers seeking effective interventions to close special education equity gaps must be will-

279Exceptional Children

ing 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.

IN T E RV E N T I O N A N D EVA LUAT I O N

Until such time as the understanding of the com- plex interactions that create disproportionality improves, intervention plans addressing dispro- portionate service must be both comprehensive and local. In the context of a multidetermined phenomenon, debates about individual versus sys- temic 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, de- veloping 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 mea- sured 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 re- sponsive practice:

• Teacher preparation. Issues of cultural mis- match, suggesting that teachers may simply lack the knowledge and skills to successfully interact with students different from them- selves (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 re- cent NRC panel identified inadequate class- room management as a factor increasing the risk for overreferral of minority students (Donovan & Cross, 2002). Culturally re- sponsive behavioral supports have been iden- tified as a promising method for addressing issues of classroom disruption and school dis-

cipline (Cartledge & Kourea, 2008; Klingner et al., 2005)

• Prevention and early intervention. The dispro- portionate representation of minorities in special education is due, in some measure, to social and demographic factors that concen- trate risk factors in minority populations (Coutinho & Oswald, 2000). A primary pre- vention model, wherein universal supports are offered to all students and more specific supports, such as cultural brokering, are of- fered to students more at risk appears to be a promising model for addressing dispropor- tionality (Serna, Forness, & Nielsen, 1998).

• Prereferral intervention/response to interven- tion. 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 aca- demic failure before referring the child for special education assessment” (p. 94). Guid- ance provided by the National Alliance of Black School Educators (NABSE) and the Council for Exceptional Children (NABSE, 2002) specifically charges school administra- tors with responsibility for selecting and im- plementing effective prereferral intervention systems in their schools.

• Assessment. Irrespective of the possibility of cultural bias in standardized tests, there ap- pears 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 be- havioral difficulty will provide a more cultur- ally responsive means of assessment. Salend et al. (2002) add that factors related to culture, language, and experience must be distin- guished from learning and behavior problems.

• Family and community involvement. To en- able more active parent involvement, Artiles and Trent (1994) recommended that educa- tors assess their own levels of cross-cultural competency. In particular, parents and fami- lies should be involved in the prereferral/re- sponse to intervention (RTI) process, and the

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values of families and culture integrated into all special education decision-making pro- cesses (Harry, 2008; NABSE, 2002).

• Policy and systems reform recommendations. The multifaceted and longstanding nature of the disproportionality problem almost cer- tainly 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 di- verse populations, and teacher training in culturally competent pedagogy.

D I S C U S S I O N A N D

C O N C L U S I O N S

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 spe- cial education disproportionality have been identi- fied, in no area is the literature sufficient to accept any single cause as fully determinative of racial dis- parity. 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 (Valen- cia & 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 dis- parities in educational resources or instructional quality on rates of special education referral. Some plausible sources of bias in the special education el- igibility decision-making process have been identi- fied, 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 school- ing (Bowles & Gintis, 1976) in which educational professionals participate in institutional practices that, left unanalyzed, reinforce a status quo that maintains class- and race-based hierarchies.

The most fitting conclusion that can be drawn from the available literature predicting spe- cial education referral and eligibility is that dis- proportionality in special education is determined by a combination of forces both within and exter- nal to our educational system. It seems likely that future research will find complex and perhaps un- expected interactions among variables that have, to this point, been studied only in isolation or on a limited scale. It is reasonable to presume, for ex- ample, that students from economically disadvan- taged 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 ser- vices. Yet, it also seems likely that a teacher’s judg- ment of appropriateness for referral is conditioned by that teacher’s self-efficacy with respect to in- structing 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 sys- tems or individual bias must be regarded as highly simplistic. Ultimately, it is likely that more so- phisticated 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 in- equity in special education is to recognize the si- multaneous contribution of those multiple sources, and to design interventions that can re- spond 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 over- identification of minority children and youth. Yet, simply improving the referral process for

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students in general will not, in and of itself, guar- antee an effect on the differential rates of special education referral for racially and ethnically di- verse students. To ensure that the needs of those who are targeted in disproportionality interven- tions 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 im- prove academic and behavioral outcomes in gen- eral, 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 im- plementation of Instructional Consultation Teams was effective in reducing both total refer- rals 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 moni- toring of disaggregated data is a critical compo- nent of all intervention efforts in order to ensure that systemic efforts are truly having an impact on the variable of concern—disproportionate repre- sentation by race and ethnicity.

Finally, the fact that a multiplicity of vari- ables, across both general and special education, may contribute to disproportionate representation has important implications for the implementa- tion of special education policy. In promulgating IDEA 2004, Congress deemed disproportionate representation that is the result of inappropriate identification sufficiently important as to consti- tute a key monitoring priority (IDEA 2004, 34 CFR 300.600(d)(3)). There may be some tempta- tion to restrict the interpretation of “inappropri- ate identification” so as to focus primarily on special education policies, practices, and proce- dures. Yet, the data clearly 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 in- equity in general education, including curriculum (Ferri & Connor, 2005); classroom management

(Donovan & Cross, 2002); teacher quality (Dar- ling-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 re- ceive 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 eq- uity 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 delib- erate speed” and set deadlines for the end of edu- cational segregation (Lowery & Marszalek, 1992). Thus, the period of American history character- ized 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.

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A B O U T T H E A U T H O R S

RUSSELL J. SKIBA (CEC IN Federation), Pro- fessor, Counseling & Educational Psychology and Director of the Equity Project at Indiana Univer- sity; 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 Indi- ana University; Center for Evaluation and Educa- tion Policy, Indiana University, Bloomington.

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 nec- essarily reflect the opinion of the Indiana Depart- ment 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: skiba@indiana.edu).

Manuscript received October 2006; accepted October 2007.

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