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between funding and quality of education, however, is difficult to establish. Theres littlerelationship between spending and student performance in those high-poverty schools, saysEric Hanushek, an economist at the Hoover Institution. If anything, the schools that spend moremoney have less to show for it.17

Table 4 also reveals an interesting pattern. Increased class size is indeed associated with lowerrates of enrollment in special education programs. This finding is intuitively appealing becauselarger classes might make it more difficult to identify the needs of individual students. Thisassumption was reasserted by many of the educators we interviewed. If overcrowding occursmore often in less affluent districts, which tend to be majority-minority districts, this might helppartially explain why districts with greater percentages of minorities enroll fewer students inspecial education. Table 4 indicates that schools with many minority youngsters also tend tohave slightly more crowded classrooms. Although the relationship is modest, it is difficult not toconsider class size a contributor to special education enrollment rates.

A third variable of interest is teacher salary. Nationwide shortages of teachers have made pay ahot-button issue for education reform. Average salary for starting teachers in 1999 was roughly$26,000, with great variation depending on the state and district. The educators we spoke with,however, disagreed on whether salary or location is the bigger barrier to attracting goodteachers.

Matthew Ladner and Christopher Hammons

92 RETHINKING SPECIAL EDUCATION FOR A NEW CENTURY

Correlations

1.000 .027 -.255** -.401** -.519**

. .367 .000 .000 .000

1126 1126 1126 1126 1126

.027 1.000 -.273** .202** .195**

.367 . .000 .000 .000

1126 1126 1126 1126 1126

-.255** -.273** 1.000 .407** .157**

.000 .000 . .000 .000

1126 1126 1126 1126 1126

-.401** .202** .407** 1.000 .407**

.000 .000 .000 . .000

1126 1126 1126 1126 1126

-.519** .195** .157** .407** 1.000

.000 .000 .000 .000 .

1126 1126 1126 1126 1126

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

SPECED % of studentsin district labeled asspecial ed

SPENDING districtexpenditures per pupil1995

TEACHPUP teacher topupil ratio

SALARY average salaryfor teachers 1995

PMS % minoritystudents in district

SPECED %of studentsin district

labeled asspecial ed

SPENDING district

expendituresper pupil 1995


SALARY averagesalary forteachers

1995

PMS %minoritystudentsin district

Correlation is significant at the 0.01 level (2-tailed).**.

Table 4. Percentage of Students Enrolled in Special Education CoursesCorrelated with Possible Predictors

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we examine the possibility that the relationship truly being measured here is one of urban versusrural districts. We will also return to the question of class size and salaries in our final analysis.

Hypothesis 2District Competence: Urban districts are less competent inidentifying special-needs students.If financial resources do not make a difference in specialeducation enrollment rates, we must look elsewhere forexplanations. It may be that special education rates varybetween districts as a result of district competence in identifyingstudents with special needs. To this end, lower rates of specialeducation enrollment in districts with greater percentages ofminorities could indicate that minority students are poorly servedby their school districts, regardless of available finances. Wehypothesize that success in identifying learning disabilities mightbe partially a function of the competency of districts in whichminority students are enrolled.

Data from the 1990 census show that, in Florida and Texas,urban districts generally have a greater percentage of minoritystudents as part of the total student body than rural districts. Thisis a national trend as well. It has been estimated that in the mid-1990s, for example, 53.8 percent of urban schools hadpredominantly African-American student populations.18 In some cities the number is higher:Milwaukee, 61 percent; Philadelphia, 64 percent; St. Louis, 80 percent; Atlanta, 92 percent; andBirmingham, 94 percent.19

Urban districts often come under fire for doing a poor job of educating students, particularly



Our data indicatethat the moreurban a schooldistrict, the lowerthe percentage ofminority studentsenrolled in specialeducationprograms in thatdistrict.

Coefficientsa

27.872 1.072 25.995 .000

-4.81E-04 .000 -.401 -14.654 .000

28.741 1.092 26.322 .000

-4.28E-04 .000 -.356 -11.958 .000

-.158 .043 -.110 -3.691 .000

(Constant)


(Constant)



Model1

2

B Std. Error

UnstandardizedCoefficients

Beta

Standardized

Coefficients

t Sig.

Dependent Variable: SPECED % of students in district labeled as specialeda.

Table 5. Measuring District Resources: Salary and Class Size as Predictors of Special Education Enrollment

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percentages of white students also have higher special education rates, even as minoritystudents demonstrate greater special education rates in the aggregate.

To test this possibility, we divided special education students into minority and non-minoritygroups. For purposes of our analysis, minority students consisted of black, Hispanic, and Asianstudents. (Native-Americans were such a small percentage of the population that they did notalter the analysis.) Table 9 reveals a direct relationship between the racial composition of thestudent body and the racial composition of students placed in special education. Districts with agreater percentage of white students place a slightly higher percentage of their minority studentsinto special education compared to primarily minority districts.

The correlation between the percentage of white students enrolled in special education and thepercentage of white students in the district is insignificant. If predominantly white districts simplyenrolled a larger number of special education students in general, we should see an increase inenrollment in both white and minority rates. However, what we see is an increase only in therates of enrollment among minority students. This would seem to indicate that, in predominantlywhite districts, minority students are treated differently.

To explore the impact of ethnicity in special education, we plotted the enrollment rate of differentethnic groups in special education programs against the percentage of the student body that iswhite. The results are presented in Figure 2. Two things are immediately evident.

First, white districts enroll a greater percentage of minority students in special educationthan majority-minority districts. Enrollment rates for all ethnic groups are highest in



Correlations

1.000 .247** .150**

. .000 .000

1043 1043 1042

.150** -.011 1.000

.000 .715 .

1042 1118 1118

.247** 1.000 -.011

.000 . .715

1043 1126 1118

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

MSPED minorities inspecial ed as % ofminorities in district

SPECW White studentsin special ed as % of allwhite students

PWS % of whitestudents in district

MSPED minoritiesin special

ed as % ofminoritiesin district

PWS % ofwhite

studentsin district

SPECW White

students inspecial ed as% of all white

students


Table 9. District Composition and Special Education Enrollment

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There are two problems with this highly controversial assertion. First, our previous analysis ofHypothesis 2 indicated that the racial composition of the school is more important thanvariables that we might associate with the schools academic standards (dropout rate, testscores, spending, and level of urbanization). To this end, the quality of the school seemsunrelated to, or to have little influence on, enrollment once the racial composition of the studentbody is taken into account.

Second, our analysis indicates that race is important not only in terms of the student body, butalso the faculty. Table 10 reveals that districts with more white teachers have a greater rate ofminority enrollment in special education, particularly for African-American students. Thecorrelation for African-Americans is almost the same as for Hispanics. Special education ratesfor white students are unaffected by the racial composition of the faculty. Again, it seems thatminority kids are singled out, but this time the data point toward the race of faculty members asan explanation for higher minority student enrollment in special education.27

Conclusions

The data indicate that minority students are treated differently in predominantly white districtsthan in predominantly minority districts. Districts with predominantly black teachers, for example,have lower special education rates for all students, but particularly for African-American andHispanic students. That is, the data reveal that in districts with a predominantly black faculty,minority students see a reduction in special education enrollment that is three to four times



Correlations

1.000 -.077** -.500** -.211** -.274** -.076*

. .010 .000 .000 .000 .011

1126 1126 1126 1033 1118 1118

-.077** 1.000 -.824** -.137** -.076* -.012

.010 . .000 .000 .011 .700

1126 1126 1126 1033 1118 1118

-.500** -.824** 1.000 .245** .225** .059

.000 .000 . .000 .000 .050

1126 1126 1126 1033 1118 1118

-.211** -.137** .245** 1.000 .613** .169**

.000 .000 .000 . .000 .000

1033 1033 1033 1033 1032 1032

-.274** -.076* .225** .613** 1.000 .136**

.000 .011 .000 .000 . .000

1118 1118 1118 1032 1118 1113

-.076* -.012 .059 .169** .136** 1.000

.011 .700 .050 .000 .000 .

1118 1118 1118 1032 1113 1118

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

BTEACHER % ofteachers in district thatare black

HTEACHER % ofteachers in district thatare hispanic

WTEACHER % ofteachers in district thatare white

SPECBLAC African-Ameicans inspecial ed as % of allblack studentsSPECHIS Latinos inspecial ed as % of allHispanic students

SPECW White studentsin special ed as % of allwhite students

BTEACHER % of teachersin district that

are black

HTEACHER % of teachersin district thatare hispanic

WTEACHER % of teachersin district that

are white

SPECBLAC African-Ameicans in specialed as % of all

blackstudents

SPECHIS Latinos inspecial edas % of allHispanicstudents

SPECW White

students inspecial ed as% of all white

students


Correlation is significant at the 0.05 level (2-tailed).*.

Table 10. Correlations of Faculty, Race, and Racial Composition of Students in Special Education

greater than the reduction seen by white students. This does not mean that minorities havelower special education rates than whites in these districts, only that these rates drop greatly indistricts with minority faculty while those of white students experience only a slight decrease. Thisis illustrated in Figure 2, where the difference among black, Hispanic, and white students islowest in districts with less than 20 percent white faculty (that is, predominantly minoritydistricts).

These findings indicate that enrollment in special education might be determined in part byracenot only of the student but also of the students teachers and/or fellow students. Table 11presents a final comprehensive model combining district-level data from Texas and Florida,weighted by population (districts with high populations are given a higher weight). Ourdependent variable is again the number of students enrolled in special education in eachdistrict, and the key independent variable of interest is again the percentage of minority studentsin each district. Control variables include those that demonstrated some influence in our fourmajor hypothesesteacher salaries, teacher-to-student ratio, spending per pupil in the district,and the percentage of students eligible for a free or reduced lunch.

Special but Unequal: Race and Special Education

Progressive Policy Institute vv Thomas B. Fordham Foundation 105

Model Summary

.632a .400 .397 2.2812Model1

R R SquareAdjustedR Square

Std. Error ofthe Estimate

Predictors: (Constant), % of students on free lunch,teacher to pupil ratio, district expenditures per pupil1995, average salary for teachers 1995, % minoritystudents in district

a.

Table 11. Final Model: Class Size, Salary, Student Body, and Spendingas Predictors of Special Education Enrollment

Coefficientsa

15.203 1.267 11.997 .000

-9.22E-02 .005 -.847 -18.426 .000

-1.46E-04 .000 -.121 -3.983 .000

-5.29E-02 .040 -.037 -1.325 .186

7.685E-04 .000 .151 5.801 .000

6.926E-02 .007 .443 10.499 .000

(Constant)

% minority studentsin district

average salary forteachers 1995

teacher to pupil ratio

district expendituresper pupil 1995

% of students on freelunch

Model1

B Std. Error

UnstandardizedCoefficients

Beta

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Coefficients

t Sig.

Dependent Variable: % of students in district labeled as special eda.

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Rethinking Special Education for a New Century