The Voluntary Interdistrict Desegregation Program in St. Louis

and the Geography of Opportunity

 

Ain A. Grooms, University of Georgia[1]

 

 

Abstract:

 

The voluntary interdistrict desegregation program began in St. Louis in 1983 and provided Black students from urban communities with free transportation to one of 15 participating suburban school districts.  The geography of opportunity posits that location can impact the opportunities available.  This study conducts a descriptive statistical analysis of the fiscal resources in St. Louis as compared to those in the participating suburban districts, as well as among the suburban districts themselves.  Results indicate that there are significant variations in resources among the suburban districts, indicating the need for additional research on race, place, and education spending.


 

Horace Mann (1848) once declared that education was to be “‘the great equalizer’ of the conditions of men—the balance wheel of the social machinery” (para. 9).  Just over one hundred years later, in 1954, the United States Supreme Court unanimously ruled, in the Brown v. Board of Education of Topeka case, that racial segregation was unconstitutional, and that separation of the races denied Black children the equal protection guaranteed by the Fourteenth Amendment.  This case remains one of the most influential lawsuits of the past hundred years, and has helped in shaping not only the landscape of public education, but of society as a whole.  The Supreme Court’s decision initiated an ongoing nationwide discussion about equal educational opportunity.  Despite the intentions of the Brown decision, our country’s history of racial, residential, and economic segregation continues to pose a tremendous obstacle to the creation of equal schools and an equal society. 

As public schools were instructed to become racially integrated, affluent White students left city schools for neighboring suburbs, in what is known as White Flight.  In the 1960s, the White population in cities declined by 1.3 million (National Advisory Commission on Civil Disorders, 1968).  Wells and Crain (1997) contend that the Great Black Migration, the movement of millions of Blacks from southern, rural communities to northern cities during the 1940s and 1950s, was “second only to the suburbanization of the white middle class as the most profound social phenomena of twentieth-century America” (p. 42).  This movement of Black and White families across city lines affected school enrollments and demographics.

As Du Bois (1903) famously wrote, “The problem with the twentieth century is the problem of the color line” (p. 13).   Wells and Crain (1997) asserted that race plays an significant role in the shaping of our communities, stating that “the color line envelops us all, limiting the housing we rent or purchase, the schools our children attend, the transportation we have access to, and the network of friends and associates with whom we share information” (p. 8). Almost a century after the comments made by Du Bois, and almost 60 years after the Brown decision, race continues to be an integral component of discussions about equal opportunity, educational and otherwise. 

Ten years following the Brown decision, several cities created their own localized programs to address inequalities in public schools.  The earliest programs began in 1965.  These voluntary interdistrict desegregation programs[2] were implemented specifically to address racial and socioeconomic segregation in public schools by providing minority (predominately Black) and/or socioeconomically disadvantaged students from urban areas with free transportation to public schools in suburban districts.  There are currently eight programs in operation across the country: Boston, MA; Hartford, CT; Milwaukee, WI; Minneapolis, MN; Omaha, NE; Rochester, NY; Palo Alto, CA; and St. Louis, MO.  These programs were either developed through state law as a result of local grassroots movements, federal court rulings, or state court rulings (Wells et al., 2009).  Parents of participants in the voluntary interdistrict desegregation programs have openly admitted to participating in the program because of access to the “better education” being provided in the suburbs (Armor, 1972; Eaton, 2001, 2006; Orfield et al., 1998; Wells & Crain, 1997). 

The voluntary transfer program in St. Louis is the largest, as well as one of the oldest (having been founded in 1983).  At the height of the program, during the 1999-2000 school year, almost 15,000 students participated.  During the 2012-2013 school year, over 5,000 Black students from St. Louis attend suburban schools in one of 15 participating suburban school districts.

As Coleman et al. (1966) argued, with whom a student attends school is as important as family background, and this research intends to examine the suburban schools and communities in which urban students enroll.  It has long been assumed that suburban communities are inherently better than urban communities, and while families from St. Louis participate in the program due to access to “a better education” (Wells & Crain, 1997), little attention has been paid to the variation among suburban communities and how they differ from each other.  The purpose of this paper is to conduct a descriptive statistical analysis of the fiscal resources available in St. Louis as compared to those available in the 15 participating suburban districts and of the variation in resources among the suburban communities themselves.  There is an ongoing debate about whether and how increased funding impacts student achievement (Biddle & Berliner, 2003; Gamoran & Long, 2006; Hanushek, 1996), and rather than join that discussion, this research intends to specifically investigate the fiscal resources available to families participating in this school choice program.

Past quantitative studies about these busing programs have looked expressly at standardized test scores and/or high school graduation rates (Angrist & Lang, 2004; Eaton & Chirichigno, 2011), and the previous qualitative research on voluntary interdistrict desegregation programs questioned parents about their reasons for enrolling their children in the program and whether they would participate again if given the choice (Armor, 1972; Eaton, 2001, 2006; Orfield et. al, 1998; Wells & Crain, 1997).  Past studies that have investigated the intersection of race, place, and access to educational opportunities in similar contexts have focused on the Gautreaux and Moving to Opportunity programs, where participants physically relocated to suburban areas.  This study provides an alternate context, as students enrolled in the voluntary transfer program in St. Louis are able to remain in their own communities while simultaneously receiving access to suburban resources. 

Geography of Opportunity

The geography of opportunity is used as the conceptual framework for this study.   In defining the framework, Galster and Killen (1995) pose the following, “How confined are households to certain areas of residence and thus to particular markets and institutions? What are the resulting differences in the environments in which youth of various backgrounds make choices about education, fertility, work, and crime?” (p. 10).  Many scholars have continued this line of research, specifically as it pertains to housing and the educational and employment opportunities available in particular neighborhoods.  Squires and Kubrin (2005) contend that, “where one lives and one’s racial background are both social constructs which, on their own and in interaction with each other, significantly shape the privileges (or lack thereof) that people enjoy” (p. 48).  Briggs (2005) asserts that, “location matters—for economic returns, quality of life and many other reasons” (p. 17). 

Beginning in the 1960s, direct efforts were made to combat residential segregation through the creation of suburban residential relocation programs for low-income Black families.  Two such programs were the Gautreaux Program in Chicago and the Moving To Opportunity (MTO) program in Baltimore, Boston, Chicago, Los Angeles, and New York.  Results of the programs varied, but an important distinction between the two programs must be noted--the Gautreaux program in Chicago, created following the 1976 Hills v. Gautreaux Supreme Court ruling, was designed to offer Black families living in segregated housing projects the opportunity to relocate to a more racially-integrated neighborhood throughout the metropolitan area, while the MTO program, a randomized housing experiment funded by the U.S. Department of Housing and Urban Development, provided selected families a means of moving from high-poverty areas to more affluent neighborhoods, regardless of race.  Families that participated in the MTO program tended to relocate to wealthier neighborhoods, though still racially segregated (Duncan & Zuberi, 2006).  Research on the Gautreaux program indicates that participating children had higher satisfaction with teachers and better attitudes about school (Sanbonmatsu, Kling, Duncan, & Brooks-Gunn, 2006) while studies found that participating in the MTO program had minimal impact on school quality and academic performance (Briggs, Ferryman, Popkin, & Rendon, 2008; Duncan & Zuberi, 2006).

Additional studies on race, place, and class continue to necessitate the focus on the geography of opportunity. In a study conducted on the 100 largest metropolitan areas, Acevedo-Garcia, Osypuk, McArdle, and Williams (2008) found that the average White child lives in a neighborhood that has a poverty rate of 7 percent, the average Black child lives in a neighborhood with a 21 percent poverty rate, and the average Latino child lives in a neighborhood with a 19 percent poverty rate.  Poverty rates at 10 percent or lower generally indicates a low-poverty (or high-opportunity) neighborhood, and poverty rates at 20 percent or higher are generally considered high-poverty neighborhoods.

National data shows that “the average black family earning $60,000 or more lives in a neighborhood with a higher poverty rate than the average white family earning under $30,000” (Logan, Oakley, & Stowell, 2003, p. 16).  Acevedo-Garcia et al. (2008) conducted an analysis specifically focusing on poor Black, White, and Latino children, and found that even the poorest White children live in better neighborhoods (14 percent poverty rate) than the average Black and Latino children. In his book, The Truly Disadvantaged, Wilson (1987) focused on equality of life outcomes, and argued that the isolation of Blacks from White, middle class opportunities poses the greatest obstacle to academic and economic success.  This speaks to the need for a greater understanding of the geography of opportunity and its impact on children, families, and neighborhoods. 

Despite such research, it is critical to remember Yosso’s (2005) research on community cultural wealth, and to recognize that although low-opportunity neighborhoods do not have all of the access and privilege of high-opportunity neighborhoods, they do provide residents with the “knowledge, skills, and abilities…to survive and resist macro and micro forms of oppression” (p. 77).  Rather than always considering what these neighborhoods lack, it is critical to celebrate what they do possess.  Briggs (2005) notes that while housing integration can be viewed as a “proxy for access to opportunity” (p. 29), access to high-quality education is more directly related to long-term prospects. In light of these details and of the implementation of the unique voluntary transfer program in St. Louis, there exists the need to examine race and place in this specific context.

Brief History of the Voluntary Interdistrict Desegregation Program in St. Louis

The plaintiffs in the 1972 Liddell v. Board of Education of the City of St. Louis case argued that the School Board had operated in a discriminatory manner following the 1954 Brown ruling, and as a result, deprived Black students in St. Louis of equal educational opportunities.  A settlement was finally reached in 1983, which included the creation of a dual transfer program, where Black students from St. Louis were provided with free transportation to suburban schools at all grade levels, and White suburban students were eligible to enroll in city magnet schools.  Through this transfer program, the suburban districts agreed to increase the percentage of Black students by at least 15% of their current enrollment, though not to exceed 25% of total enrollment (Heaney & Uchitelle, 2004).  Applications are processed on a first-come, first-served basis, and parents indicate their preferences for the suburban districts paired with their city zones.

By 1999, following a lengthy process, a bill was passed that ended court-ordered desegregation of the city’s public schools, but would keep both the transfer program and the magnet schools.  The 1999 settlement agreement did not require the participating suburban districts to enroll the same percentage of transfer students into their schools each year, and as a result, districts began phasing out a small percentage of available seats each year, approximately five to six percent annually.  Enrollment was at its peak of 14,227 total participating students, including 1,249 suburban students attending city magnets, during the 1999-2000 school year, the first year following the settlement agreement.  Enrollment has continually fallen since the Settlement Agreement, and during the 2012-2013 school year, program enrollment totaled 5,130 total students, with 86 suburban students attending the city’s magnets (Voluntary Interdistrict Choice Corporation, 2013).  This study focuses on the ten years following the lifting of the court order in 1999, and though this is a dual-transfer program, emphasizes the urban-to-suburban aspect of the program. 

Methods and Data

Using descriptive statistical analyses, this study investigates both the differences in resources between St. Louis and the 15 participating suburban districts, and among the 15 suburban districts.  The ten years of data (1999-2009) included in this study allows for a longitudinal analysis of the fiscal resources in the suburban districts to which transfer students have access. The mean (average) of the ten years of data is calculated for each district, as well as the range of each variable (subtracting the minimum value from the maximum value) among the suburban districts only.

Data Sources

The district-level data used to examine the resources available in the 16 participating districts (including St. Louis) were obtained from the following state or federal databases: the National Center for Education Statistic’s Common Core of Data, the Common Core of Data’s Local Education Agency Finance Survey Data (F-33 file), the Missouri Department of Education, the St. Louis County Department of Revenue, and the U.S. Census Bureau.  The dollar amounts used throughout this analysis are reported in 2009 inflation-adjusted dollars based on conversion rates outlined by Sahr (2013).

 

Variables

A total of 17 variables were used compiled into three resource categories (Table 1).  The five spending variables are: per pupil expenditures, per pupil revenue received from property taxes, per pupil revenue received from Title I funding, per pupil teacher salary used for instruction, and local tax effort.  Using the F-33 file, district enrollment was used to calculate the per pupil expenditures, the per pupil revenue received from property taxes, and the per pupil teacher salary used for instruction.  The local tax effort was obtained from the St. Louis County Department of Revenue.

Table 1. Variable Definitions

Category

Variable Name

Description

Spending

PPE

Per Pupil Expenditures (in dollars)

PPRevPropTax

Per Pupil Revenue from Property Taxes (in dollars)

PPRevTitleI

Per Pupil Revenue from Federal Title I Funding (in dollars)

PPSalInstruct

Per Pupil Teacher Salary Used for Instruction (in dollars)

Local Tax

District Tax Rate (in mills) for the School System

District

Enrollment

Number of Students in the District

%BlackDistrict

Percentage of Black Students in the District

%WhiteDistrict

Percentage of White Students in the District

%FRL

Percentage of Students that Qualify for Free and/or Reduced Priced Lunch in the District

PupTchRatio

Pupil-Teacher Ratio

Community

MedHome

Median Home Value (in dollars)

MedFamInc

Median Family Income (in dollars)

%BA

Percentage of Residents aged 25 and older with a Bachelor’s degree

%FamPov

Percentage of Families living in Poverty

%BlackFamilies

Percentage of Black Families in the School District

%WhiteFamilies

Percentage of White Families in the School District

Distance

Distance (in miles) from St. Louis to the School District

 

Five district variables were obtained from the Common Core of Data and the Missouri Department of Education, and included the total district enrollment, the percentage of Black and White students, the percentage of students that qualify for free and reduced priced lunch, and the pupil-teacher ratio. The seven community variables included six collected from the U.S. Census Bureau: median home value, median family income, and demographic information pertaining to race, family poverty, and educational attainment.  Because all of the suburban districts are located in greater St. Louis county, school district data was calculated based on county subdivisions, defined by the Census Bureau (2013b) as “the primary divisions of counties and statistically equivalent entities for the reporting of decennial census data” (para. 1). 

Integrationists that have advocated for busing in the past argued that, “the greater the distance the student travels to get to the school, relative to options available to him, the more the school should offer him when he arrives” (Campbell, 1973, p. 482).  Physical distance (number of miles) between St. Louis and the suburban districts is included among the community variables to provide an estimate of students’ travel time. 

Findings

As evidenced in Table 2, across the five spending variables (per pupil expenditure, per pupil revenue from property tax, per pupil revenue from Title I funding, per pupil teacher salary used for instruction, and local tax effort), St. Louis Public Schools (SLPS) had higher average per pupil expenditures than the suburban average, had higher local tax effort, and received almost $450 more per pupil in Title I funding.  Regardless of the higher tax effort, SLPS received $2,000 less, on average, in revenue from property taxes due to lower property wealth.   Despite substantial differences in per pupil expenditures and revenue from property taxes, SLPS only spent an average of $100 less on teacher salary used for instruction per pupil.

In looking at the range of the spending variables among the suburban districts, we find significant variations, especially among the expenditure and revenue variables.  The highest-spending suburban district spent over $10,000 more per pupil than the lowest-spending (fives times the difference between the SLPS and suburban averages), and received over $8,500 more in revenue from property taxes than the district receiving the least amount (four times the difference between the SLPS and suburban averages).  These data reflect important fiscal and socioeconomic differences among the suburban districts.

Table 2. Spending Variables, 1999-2009 Averages

School District

PPE ($*)

PPRevPropTax ($*)

PPRevTitleI ($*)

PPSalInst ($*)

Local Tax

SPLS

13,532

3,799

585

4,194

4.8581

Suburban Average

11,673

5,977

118

4,257

3.8432

Affton

10,356

5,744

81

3,527

4.3712

Bayless

7,134

3,299

146

2,544

3.5962

Brentwood

16,193

7,916

105

5,691

3.0307

Clayton

17,956

10,281

83

6,870

3.4456

Hancock Place

8,871

1,771

273

3,529

4.3518

Kirkwood

11,013

6,716

88

4,216

3.9149

Ladue

17,158

9,713

20

5,647

3.0150

Lindbergh

10,882

5,445

78

4,032

2.9902

Mehlville

7,863

4,443

78

3,338

3.6101

Parkway

11,295

6,342

72

4,136

3.4380

Pattonville

14,229

7,639

106

4,923

3.8008

Ritenour

9,458

3,826

213

3,547

4.3503

Rockwood

10,161

5,069

68

3,447

4.3145

Valley Park

10,583

5,286

238

4,012

4.6376

Webster Groves

12,034

6,160

125

4,400

4.7811

Suburban Range

10,822

8,510

253

4,326

1.7909

*inflation-adjusted 2009 dollars

Source: National Center for Education Statistics, 2013a; St. Louis County Department of Revenue, 2013

 

Table 3 displays the variations in district variables.  The percentage of Black students in the suburban districts ranged from an average minimum of 12% to an average maximum of 34%.  The average percentage of students who qualify for free and/or reduced lunch was also greater, on average, in SLPS than in the suburban districts.  Four of the participating suburban districts had an average percentage of students that qualify for free and/or reduced priced lunch at 40% or higher, but the average percentage of Black students in those districts did not mirror those percentages.  It is also possible that changing suburban demographics, in addition to the transfer program, may be a factor in the variations in the percentage of Black students and students that qualify for free and/or reduced price lunch enrolled.  

Table 3. District Variables, 1999-2009 Averages

School District

Enrollment

%Black

District

%White

District

%FRL

PupTchRatio

SLPS

39,422

80.4

15.1

78.6

12.9

Suburban Average

6,304

19.9

73.5

24.9

15.2

Affton

2,543

11.7

83.9

23.4

16.5

Bayless

1,575

12.4

79.9

40.9

18.0

Brentwood

860

26.4

66.8

17.5

11.9

Clayton

2,556

21.7

68.0

11.8

11.4

Hancock Place

1,823

21.5

75.5

63.3

17.3

Kirkwood

5,249

22.5

74.8

14.9

16.0

Ladue

3,814

17.0

66.9

7.9

12.0

Lindbergh

5,448

13.1

83.7

13.5

15.1

Mehlville

11,616

12.4

84.4

17.1

17.6

Parkway

19,304

16.9

71.5

12.3

16.2

Pattonville

6,096

25.1

68.2

30.0

13.4

Ritenour

6,293

34.2

56.8

54.0

17.2

Rockwood

22,135

11.8

83.4

10.2

16.4

Valley Park

1,075

26.7

66.2

40.0

14.1

Webster Groves

4,177

25.0

72.2

17.0

14.7

Suburban Range

21,275

22.5

27.6

55.4

6.0

Source: Missouri Department of Education, 2013; National Center for Education Statistics, 2013a, 2013b

 

Data on the community variables (Table 4) obtained from the U.S. Census Bureau found that St. Louis residents were, on average, poorer, less White, and had less educational achievement than the residents of the participating suburban districts.  Average median family income was approximately $45,000 less in St. Louis, average median home values were approximately $100,000 less in St. Louis, and there were approximately 17% more families living in poverty in St. Louis than in the participating suburbs.  The percentage of Black families in the suburbs is almost negligible, averaging 5.6% across the ten years (while the average percentage of Black students in the suburban schools averaged 20%).  

Table 4. Community Variables, 1999-2009 Averages

School District

Med

Home

($*)

Med

FamInc

($*)

%BA

%Fam

Pov

%Black

District

%White

District

Distance

SLPS

108,538

40,870

13.7

20.9

50.3

44.0

-

Suburban Average

208,849

85,999

25.0

3.8

5.6

89.3

14.8

Affton

156,960

70,182

22.6

4.9

4.0

90.9

11.2

Bayless

148,461

69,806

17.4

2.9

0.5

95.5

10.0

Brentwood

328,330

115,307

32.2

2.7

9.6

84.5

9.5

Clayton

328,330

115,307

32.2

2.7

9.6

84.5

11.5

Hancock Place

126,182

55,228

12.1

7.4

1.9

95.0

9.8

Kirkwood

220,936

98,332

30.9

2.2

3.7

93.5

17.5

Ladue

328,330

115,307

32.2

2.7

9.6

84.5

12.4

Lindbergh

148,461

69,806

17.4

2.9

0.5

95.5

15.3

Mehlville

163,619

71,837

17.5

4.4

1.4

95.9

12.9

Parkway

220,206

94,497

33.0

3.0

3.7

86.9

19.9

Pattonville

136,883

67,166

17.4

4.2

11.1

84.7

16.4

Ritenour

91,618

50,605

11.1

8.9

20.1

75.1

14.8

Rockwood

301,121

115,000

33.0

1.9

2.0

92.5

28.2

Valley Park

195,217

86,981

32.9

4.1

3.5

88.0

21.2

Webster Groves

238,088

94,624

33.2

2.6

3.0

93.1

11.3

Suburban Range

236,712

60,079

22.1

7.0

19.6

20.4

18.4

*Inflation-adjusted 2009 dollars

Source: U.S. Census Bureau, 2013a

 

As evidenced by the range in the community variables among the suburban districts, there is, again, evidence of significant variation.  The difference in median home values among the suburban districts was over $200,000 (twice as much as the difference between the SLPS and suburban averages), while the range in median family income reached approximately $60,000 (about $25,000 more than the difference between the SLPS and suburban averages).  There were also noticeable differences in educational attainment among suburban families, ranging from 11% to 33%.  Interestingly, although the percentage of Black families averaged 5.6% in the suburban communities overall, four districts averaged approximately 10% while another two averaged 20%, indicating increasing suburban diversity. 

Conclusion

Tiebout (1956) explained that consumers will relocate based on their preferences, and will choose a community that best satisfies said preferences.  Parents with financial means can choose to relocate to better, higher-achieving school districts or place their children in private schools, while those parents who cannot must continue to send their children to their assigned schools or find other options, which includes joining the lottery of their local charter school in hopes of being selected. 

The voluntary interdistrict desegregation program in St. Louis presents a feasible (and popular yet limited) school choice option for those families in urban communities that do not have the means to physically relocate to the suburbs, unlike the families who participated in the Gautreaux and MTO programs.  This investigation, intended to contribute to the past studies done on several voluntary transfer program by Armor (1972), Crain and Strauss (1985), Eaton (2001, 2006), Orfield et al. (1998), and Wells and Crain (1997), illustrates the need for continued research to bridge the gap between race and place, between cities and suburbs, and between schools and society. 

The analyses of the spending and district variables find that the suburban districts had higher average per pupil revenue from property taxes and higher average per pupil teacher salary used for instruction, with lower average per pupil expenditures and lower average tax efforts despite larger average class sizes.  Suburban schools were also less diverse on average, both racially and socioeconomically.  Data on the community variables finds that St. Louis residents are, on average, poorer, less White, and have less educational achievement than the residents of the participating suburban districts.  The community variables were included in this analysis with the understanding that although transfer students do not have the direct access to those particular variables, they may experience an increase in their social and/or cultural capital through sustained interactions with the resident students and teachers. 

Families participating in the urban-to-suburban segment of the voluntary interdistrict desegregation program in St. Louis cannot chose the district in which their children are enrolled—they may indicate preference based on attendance zones but assignments are made on a space available basis.  These analyses indicate that, depending on the suburban district some transfer students have access to increased school resources, affluent communities, and potentially have increased access to suburban social and cultural capital.  In some suburban districts, however, education spending and revenue was lower than in St. Louis Public Schools.

The question of how much a high-quality education costs may not be answered any time soon, especially regarding students from traditionally underserved backgrounds, but the study presented here continues the line of research on the geography of opportunity by investigating in the differences in education spending between city and suburban communities, and among suburban communities.  Despite declining enrollment and little say in which district their children enroll, Black parents in St. Louis continue to choose the voluntary transfer program as an educational option.  Future analyses must include long-term achievement outcomes, college retention and current employment, allowing researchers to begin to understand the effects of increased (or in some cases, decreased) resources on student achievement under these specific circumstances.


 

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[1] aagrooms@uga.edu

 

[2] The terms, voluntary interdistrict desegregation programs and voluntary transfer programs, are used interchangeably throughout this research.