Racial Disproportionality in Special Education By Daniel J. Losen ©

Racial Disproportionality in Special Education

By Daniel J. Losen ©

Racial Disproportionality in Special Education: Measurement, Data Accuracy, and Reporting Issues

Part I:Describing Disproportionality in the

Nation and in Wisconsin

The Civil Rights Project Harvard University

3

B la c k , H is p a n ic , a n d W h i te U n d e r r e p r e s e n ta t io n a n d

O v e r r e p r e s e n ta t io n b y G i f te d , M e n ta l R e ta r d a t io n , a n d S u s p e n s io n s

1 7

8

3 3 3 3

1 59 1 0

1 5

6 3

7 6

5 45 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

B l a c k H i s p a n i c W h i t e

% E n r o l l% G i ft e d% M R% S u s p .

U .S . D e p a r tm e n t o f E d u c a t io n – O f f ic e F o r C iv i l R ig h ts : 1 9 9 8 E le m e n ta r y a n d S e c o n d a r y S c h o o l C iv i l R ig h ts C o m p lia n c e R e p o r t : N a t io n a l P r o je c t io n s – A u g u s t 2 0 0 0 .

U .S . D e p a r tm e n t o f E d u c a t io n – O f f ic e F o r C iv i l R ig h ts : 1 9 9 8 E le m e n ta r y a n d S e c o n d a r y S c h o o l C iv i l R ig h ts C o m p lia n c e R e p o r t : N a t io n a l P r o je c t io n s – A u g u s t 2 0 0 0 .


4

What is Risk?

Risk is the percentage of students of a given racial group that are identified as belonging in a particular category.

Risk =# of students of a given racial group in a disability category

# of students of a given racial group enrolled in the district


5

What is Risk?

For Example:

Black students with CD = 2 = 2%

Black students enrolled = 100

The risk of an enrolled Black student being labeled as having CD = 2%.


6

Wisconsin Risk for Other Health Impaired by Racial/Ethnic Groups 2003-04

1.2

0.4

3.2

1 1

0

0.5

1

1.5

2

2.5

3

3.5

OHI

Amer IndA/PIBlackLatinoWhite


7

Wisconsin Risk for Specific Learning Disability by Racial/Ethnic Groups 2003-04

8.2

3.7

7.1

5.3 5.6

0

1

2

3

4

5

6

7

8

9

LD



8

Wisconsin Risk for Emotional Behavioral Disability by Racial/Ethnic Groups 2003-04

4.9

0.3

2.9

1

1.8

00.5

11.5

2

2.53

3.5

44.5

5



9

Wisconsin Risk for “Cognitive Disability” by Racial/Ethnic Groups 2003-04

CD

CD

CD

CD CD

0

0.5

1

1.5

2

2.5

3

CD



10

Wisconsin Risk for Disability Category by Racial/Ethnic Groups 2003-04

0

1

2

3

4

5

6

7

8

9

CD EBD LD OHI Hard



11

Risk Ratio

• Compares the risk of one racial group with that of another; or

• compares the risk of one racial group with the risk of all the other groups combined.


12

Risk Ratios: How to Calculate

Risk Ratio =

Risk for Black students with CD

Risk for White students with CD


13

Risk Ratios: How to Calculate

For Example:

Risk for Black students with CD = 2.0 = 4.0

Risk for White students with CD = .50

• 1.0 means the same risk• 2.0 means twice as likely• .5 means half as likely


14


15

Wisconsin Risk and Risk Ratio for Disability Category by Racial/Ethnic Groups

2.9

1.2

2.42.9

1.81.6

7.1

5.6

1.3

3.2

1

3.2

0.90.81.1

0

1

2

3

4

5

6

7

8

CD EBD LD OHI Hard

BlackWhiteRisk Ratio B/W


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Q: Why is it important to analyze risk as well as risk ratio?A: Risk ratios alone leave out important information.

20

10

2

5

2.5 21 0.5

2

02

46

810

1214

1618

20

District A District B District C

Black MR RiskWhite MR RiskRisk Ratio B/W


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Racial Disproportionality in Placement and Discipline

• Disproportionality in Identification and Placement and Discipline are Linked

• The research on the factors that contribute to these patterns will be examined in Part II.


18


19

Risk of Substantially Separate Placement in Wisconsin (WDPI 2004)

34

2018 17

12

0

5

10

15

20

25

30

35

Removed from the regular classroom greaterthan 60% of the school day

BlacksLatinosAsian/PIAmer.IndWhites


20


21


22

Wisconsin’s Risk Ratios For Suspension > 10 Days By Race/Ethnicity Compared to Whites

5

3.4

6.1

1.4

0

1

2

3

4

5

6

7

Risk Ratio

Am. Ind.A/PIBlackLatino

Source: 2003 OSEP Child Count – excludes students who are educated in separate facilities.

Source: 2003 OSEP Child Count – excludes students who are educated in separate facilities.

Part II: State/District Obligations Under IDEA 2004

The many factors that may contribute to racial disproportionality.


24

Overidentification: IQ

• Larry P. in California• Construction of difference: the cut score (85 to 70)• Rampant mis-diagnosis• The IQ/ achievement differential

– IQ is just another achievement test– IQ measures poverty and other environmental factors– IQ can change– Is the bias in the test, or in the decision to rely on it to

label children?


25

Subjectivity of Evaluation and Identification

• Myth of objectivity – who is being referred?• Most referred students are identified as eligible• Technical Controversies: 10 out of 55 LD

misdiagnosed – and that was the most favorable study (Ysseldyke 2001)

• Who to test, what test to use, how to weigh the results, how to interpret the score

• IDEA provision bars discriminatory methods – is there training on culturally sensitive measures?


26

IEP TEAM

• Parents perspectives are often given little weight – especially poor and minority parents.

• Conclusions of evaluators are rarely doubted by parents or educators.

• Teachers are often reluctant to question team members (especially superiors).

• High degree of deference to the “experts.”


27

Race and Gender are Contributing Factors

Poverty and related factors correlate highly with the incidence of disability, but once socio-economic factors are accounted for, the effect of gender and race remains significant.

(See Oswald, Coutinho and Best, “Community and School Predictors of Over Representation of Minority Children in Special Education” in Racial Inequity in Special Education (September 2002)


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Black Males

In the most profound example, contrary to expectations, as factors associated with wealth and better schooling increase, Black males are at greater risk of being disproportionately labeled “mentally retarded.”

(See Oswald, Coutinho and Best, “Community and School Predictors of Over Representation of Minority Children in Special Education” in Racial Inequity in Special Education)


29

THE RACIAL COMPOSITION Of DISTRICTS MATTER

The Risk for MR and ED Among Black Children Increases as the

White Population Increases


30

Are Racial Disparities Explained by Poverty?

• Regression analysis says no.

• Blacks and Latinos have divergent patterns for MR.

• Gender differences for risk for MR among Blacks are far greater than for Whites.

• Controlling for poverty related factors ignores the legacy of discrimination.


31

Lead and other Environmental Toxins v. Bias

• National Research Council (NRC) implies environment contributes to racial disparities, but provides no correlation study linking increased risk with racial disparities for MR, ED or SLD in any location.


32

States With Extraordinarily High Percentages of Students with Mental Retardation (MR) are Mostly in the South

0 01

4

13

0

2

4

6

8

10

12

14

White Black

States where MR over5 % of enrolledStates where MR over4 % of enrolledStates where MR over2.75 % of enrolled

U.S. Dept. of Ed. OSEP 2000-2001 DATA available at www.ideadata.org. The states are: Alabama, Arkansas, Florida, Georgia, Indiana, Iowa, Kentucky, Montana, Nebraska, North Carolina, Ohio, South Carolina, West Virginia (8 of 13 are southern). Iowa does not use the IQ discrepancy test. If OCR data were used, Louisiana would be added.

U.S. Dept. of Ed. OSEP 2000-2001 DATA available at www.ideadata.org. The states are: Alabama, Arkansas, Florida, Georgia, Indiana, Iowa, Kentucky, Montana, Nebraska, North Carolina, Ohio, South Carolina, West Virginia (8 of 13 are southern). Iowa does not use the IQ discrepancy test. If OCR data were used, Louisiana would be added.


33

Where is Lead Exposure in Housing the Greatest?

According to The Prevalence of Lead-Based Paint Hazards in U.S. Housing (survey of national sample between 1998 and 2000)

• Northeast (40% risk)

• Midwest (33%)

• Lowest in South (17 %)

• West (15%)

• Government Supported Housing (17%)


34

Lead Paint Exposure by Race/Ethnicity

(in % of housing units)

• Latino 32%

• Afr. Amer. 29%

• White 25%


35

Lead Exposure and Disability Risks in Wisconsin

• Preliminary and informal analysis of UW study on positive lead tests and exposure to older housing (2004).

• Highest county for lead exposure, (double that of state) had risk levels below state averages for ED and SLD.

• CD risk was only slightly above state average.

• Low incidence categories were substantially higher than state average.

• Further study is recommended, but informal analysis yielded no obvious correlation between lead exposure and identification for CD, EBD or SLD.

36The Civil Rights Project Harvard University

Risk Ratios of “Mental Retardation” and “Hard” Disability Categories for Blacks Compared to Whites

Category CT TX NJ FL NC MS Mental Retardation 4.76 3.21 3.60 3.91 4.08 4.31 Hearing Impairment 1.22 1.22 1.09 1.31 1.09 1.57 Visual Impairment 1.60 1.08 1.09 1.12 0.94 1.44

Data from Tom Parrish - 1998/1999 school year - OSEP data.Data from Tom Parrish - 1998/1999 school year - OSEP data.


37

Restriction Risk by Disability Category

• 80-90 percent of students with MR, and over 70 percent with ED are educated in resource rooms or substantially separate settings.

• Approximately 56 percent of students with specific learning disabilities are in full inclusion placements (pulled out less than 21 percent of the school day).

• Overrepresentation for ED and MR significantly increases the risk for blacks of being educated in a substantially separate program.


38

Similarly Situated?

• Few states report data on racial disparities for inclusion within a disability category.

• Can the greater risk for segregation be explained by the greater risk for MR and SED alone?

• Data from CT suggests the answer is no.


39

Inclusion: Race with Disability

• Among students with mental retardation, emotional disturbance and specific learning disabilities in Connecticut in 1995 Black and Latino Males and Females were far less likely to be in an inclusive setting than their White counterparts.

• Dramatic improvement was noted after the filing of a lawsuit and change in the federal law requiring monitoring of these racial disparities.


40

Harvard’s Research Findings

• Subjectivity of assessment confounds determinations of special education eligibility.

• Race/Ethnicity and gender are highly correlated with significant overrepresentation of minority students in special education, even after accounting for the effect of poverty.

• Under-servicing of minority students with disabilities increases the likelihood of discipline problems and school failure.

• High-stakes testing can contribute to serious problems for minority students with disabilities.

• Minority students are more likely to receive services in restrictive special education settings.


41

The Civil Rights Project and The National Research Council Say…

• School policies and practices are contributing factors.

• Inadequate teacher training and support for classroom and behavior management may contribute to racial disproportionality.

• Research indicates that special education over-identification and overly restrictive placements reflect some inappropriate use of special education as a disciplinary tool.


42

Areas of Agreement Continued…• To focus on reducing numeric disparities alone, without

ensuring that minority students are making meaningful academic progress, is ill advised.

• Numerous studies demonstrating that racial stereotypes and bias affects decisions teachers make about students (Chapter 5 of NRC Report).

• Socio-economic and environmental factors likely contribute to heightened incidence of disability.


43

Revised 618

• New Data (618)(a)• Racial and ethnic disparities in discipline including suspensions of one

day or more• Gender and English Language Learners added for collection and

reporting• Annual public reporting of data at the state level• New Requirements (618)(d): analyze for significant disparities by

race and ethnicity in identification, placement, and discipline.• Early intervening services required where problems are evident as

well as public reporting of interventions.• Specifically triggers 15% spending on early intervention services

under 613(f)


44

Monitoring and Enforcement Priority Area in New Law 612 and 616

• 616: (a)(3) Monitoring Priorities: “Disproportionate representation of racial and ethnic groups in special education and related services, to the extent the representation is the result of inappropriate identification for special education” is one of three priority areas for the U.S. Secretary of Education.

• States must develop a plan of action with rigorous measurement and set targets.


45

614

1. Evaluation procedures (614)(b)(2)(A) Shall use a variety of assessment tools…(3) are selected and administered so as not to be discriminatory on a racial or cultural basis:

2. (b)(5)Rule out inadequate instruction and LEP issues.


46

Implicit Bias Measurement

• Brain science – based on speed of positive and negative associations.

• Implict Attitude Test (IAT) developed to elicit unconscious attitude.

• Applies to wide ranges of categories

• (Harvard v. Yale) (Age)(Gender)


47

Implicit/Unconscious Bias

• Perceptions that have been reinforced are hard to change.

• We don’t see or use all the evidence – what we pay attention to matters.

• Measured through subtle, reflexive, unconscious types of behavior.

• All races….

“Soft Bigotry of Low Expectations”

George W. Bush

Test Yourself

www.implicit.harvard.edu


50

Unconscious Racial Bias

• Against Black Adults

• Against Black Children (same)


51

Implicit and Explicit Racial Bias for Whites Exhibited by Blacks and Whites

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Implicit Explicit

BlacksWhites

Source: Nosek, Banaji and Greenwald (2002)Source: Nosek, Banaji and Greenwald (2002)


52

Schools and Unconscious Bias

• Understand the Difference Between Unconscious Bias and Intentional Racism

• Review the Data• Training Similar to Gender Bias – (Girls and

Math)• Same Concept as “Soft Bigotry of Low

Expectations.”• Understand the Magnitude: One of Many Factors


53

Racial Bias Theory is Well Grounded in Research

• The research lends support to the theory that implicit racial bias is a contributing factor.

• Addressing significant racial disparities does not require proof of intentional discrimination.


54

Implicit Bias Findings

• Conscious attitudes can influence the magnitude of implicit bias.

• Explicitly non-biased respondents showed implicit pro-White bias.

• Asian and Hispanic respondents showed implicit and explicit pro-White bias at same levels as Whites.


55

Concern That Implicit Bias Affects Many Decisions and Outcomes

• Achievement Gap and Dropout Rate

• School Finances

• Access to Highly Qualified Teachers

• Gifted and Talented and AP

• Identification for Special Education

• School Discipline


56

What Should the Remedy Look Like?

• Change the numbers: Reduce the differential? The risk? The risk ratio?

• Early Intervening Services?

• Improve the quality of regular education?

• Assuming unconscious racism contributes – how can you change that?

Documents

Racial Disproportionality in Special Education By Daniel J. Losen ©