Separate and Unequal?: The Problematic Segregation of Special Populations in Charter Schools Relative to Traditional Public Schools

SEPARATE AND UNEQUAL? THE PROBLEMATIC SEGREGATION OF SPECIAL POPULATIONS IN CHARTER SCHOOLS RELATIVE TO TRADITIONAL PUBLIC SCHOOLS Julian Vasquez Heilig, Jennifer Jellison Holme, Anthony V. LeClair, Lindsay D. Redd & Derrick Ward* The extent to which special student populations (ELL, Special Education and Economically Disadvantaged) gain access to charter schools is understudied. In this article, we compare the enrollment of high-need special populations in charter schools with non-charter public schools at the state, district, and local levels. State-level dissimilarity analyses show only modest disparities in segregation and access of high-need students within the Texas charter system compared to traditional public schools. However, local-level descriptive and geospatial analyses of charters in a large metropolitan area shows that there are large disparities in the enrollment of high-need students relative to traditional public schools nearby. We conclude by discussing implications for law and policy. * Julian Vasquez Heilig is the Director, of the Doctorate in Educational Leadership at California State University Sacramaento. He is Education Chair of the California NAACP, and received a Ph.D in Education Administration and Policy Analysis from Stanford University. He blogs at Cloaking Inequity. Jennifer Jellison Holme is an Associate Professor of Educational Policy and Planning at The University of Texas at Austin. She received her Ph.D in Education Policy from UCLA. Anthony V. LeClair is a doctoral student in Education Policy and Planning at the University of Texas at Austin. His academic interests are focused on mechanisms designed to relieve between and within school socioeconomic and racial segregation. Lindsay Redd works as a data analyst in the Colorado public school system and is a doctoral candidate at The University of Texas at Austin. Formerly, Lindsay taught social studies and literacy at the middle school level. Derrick Ryan Ward is an attorney and former high school teacher who enjoys working on matters involving labor, civil rights, and the U.S. Constitution in support of a strong, free public education for every student. He lives in Dallas. 251 252 STANFORD LAW & POLICY REVIEW [Vol. 27:251 INTRODUCTION ....................................................................................................... 253 I. BACKGROUND ................................................................................................... 256 II. THE TEXAS CHARTER SCHOOL CONTEXT ......................................................... 259 III. DATA/METHODOLOGY ...................................................................................... 261 A. State-Level Analyses ................................................................................... 261 B. Local-Level Analyses .................................................................................. 262 1. Procedures ...................................................................................... 263 2. Charters Versus Attendance Zone Schools Within a One-Mile Radius ............................................................................................. 266 3. Calculations of Demographic Difference ....................................... 268 IV. FINDINGS .......................................................................................................... 268 A. State-Level Descriptive and ANOVA Statistical Analyses .......................... 269 1. ANOVA Analysis........................................................................... 269 2. Dissimilarity Index Analysis .......................................................... 270 B. Local-Level Analyses: Charters in Houston Footprint .............................. 271 1. Charters Versus HISD Schools: Descriptive Analysis ................... 271 2. Charters Versus Nearby HISD Schools: Spatial Analysis ............. 272 3. Exemplar Schools Analysis ............................................................ 273 V. DISCUSSION ...................................................................................................... 278 VI. POLICY IMPLICATIONS ...................................................................................... 279 A. Second-Order Substantial Approach .......................................................... 279 B. First-Order Incremental Approaches ......................................................... 281 1. Enrollment and Retention ............................................................... 281 2. Discipline Disparities ..................................................................... 282 2. Local Control .................................................................................. 284 CONCLUSION .......................................................................................................... 285 2016] SEGREGATION IN CHARTER SCHOOLS 253 INTRODUCTION More than sixty years ago, the U.S. Supreme Court announced a unanimous ruling in Brown v. Board of Education. (Brown I)1 In contravention of then-prevailing wisdom and popular opinion across large swaths of the United States, the Court declared, “in the field of public education the doctrine of ‘separate but equal’ has no place. Separate educational facilities are inherently unequal.”2 In sum, segregation in schools violated students’ right to equal protection of the laws guaranteed by the Fourteenth Amendment.3 The legacy of the Brown decision goes well beyond education. The underlying promise of Brown was equality. Yet sixty years later, race and class abide as vibrant issues that animate American life. As another decade passes since the Court issued its ruling, undertaking robust examinations of its lasting impact on American education seems fitting, especially in the face of a rapidly changing education landscape. As such, this work sets out to provide an examination of that impact on one particular and rapidly growing component of public education in the United States: charter schools. Texas provides a fitting setting for this inquiry given its history of struggles with race and its ongoing efforts at the intersection of race and education. Indeed, it was a case from Texas that laid the foundation upon which Brown would be built just a few years later. 4 Sweatt v. Painter recognized that despite the State’s efforts to create a separate and substantially equal law school for black students, the refusal to admit Mr. Sweatt to The University of Texas Law School denied him “his full constitutional right: legal education equivalent to that offered by the State to students of other races.”5 The court also used the decision to acknowledge “those qualities which are incapable of objective measurement but which make for greatness in a law school,”6 a consideration the Court would later find to “apply with added force to children in grade and high schools.”7 In the Brown case itself, the Court lent its ear to Texas in crafting a remedy intended to effectuate its ruling from a year earlier.8 In Texas Attorney General John Ben Shepperd’s amicus brief to the Court, Mr. Shepperd advocated a “gradual adjustment in view of the complexities of the problem,” including “the unwillingness of the Texas people immediately to abide by the decision, the varying degrees in which different areas of the State of Texas would be affected, and the result such a decision would have on the State’s public school 1. 347 U.S. 483 (1954). 2. Id. at 495. 3. Id. 4. Sweatt v. Painter, 339 U.S. 629 (1950). 5. Id. at 635. 6. Id. at 634. 7. Brown I, 347 U.S. at 493-94. 8. Brown v. Bd. of Educ. (Brown II), 349 U.S. 294, 299 (1955). 254 STANFORD LAW & POLICY REVIEW [Vol. 27:251 system which has been maintained on a segregated basis for generations.”9 Even today, legal questions about the value and necessity of diversity in education are alive and well in Texas.10 In light of these concerns, as well as those presented by other states and the U.S. Attorney General, the Court largely left it to states and localities to determine the appropriate course for implementing its 1954 ruling. The Court instructed that “the defendants make a prompt and reasonable start toward full compliance with” that ruling and that such compliance should be accomplished “as soon as practicable” and “with all deliberate speed,” leading to a legal and political battle lasting decades.11 Sixty years later, we ask how charter schools are affecting the legacy of this decision in Texas. Charter schools are public schools of choice operated under contract with an authorizing agency (districts, management organizations, non-profits, or universities). Charters are granted freedom from many of the regulations governing traditional public schools (such as staffing, calendar, class size, etc.), and they are given greater authority over budget decisions.12 In exchange for this increased flexibility, charters are supposed to be held more accountable for outcomes than traditional public schools. If charters fail to produce results, the schools will (in theory) either lose students and thus funding, and/or face the revocation of their charter by their authorizing agency. Charters have grown rapidly since the enactment of the first charter school law in Minnesota in 1991. As of 2013, there were 5,696 charters operating across 39 states and the District of Columbia enrolling more than 2 million students.13 The rise in charters has been particularly rapid in the past five years.14 Many states have lifted caps on the number of charter schools contained within the original state legislation, owing in part to financial incentives created by federal grant programs such as Race to the Top.15 Federal and state grant programs for charter planning and implementation have also encouraged charter growth.16 As a result of this support, charters are now, according to one 9. Brief for Kansas, John Ben Sheppard as Amici Curiae Supporting Respondents, Brown v. Bd. of Educ., 349 U.S. 294 (1955) (Nos. 1, 2, 3, & 5). 10. See generally Fisher v. Univ. of Tex., 133 S. Ct. 2411 (2013). 11. Brown I, 349 U.S. at 300-01. 12. Luis A. Huerta & María-Fernanda González, Cyber and Home School Charter Schools: How States Are Defining New Forms of Public Schooling, 81 PEABODY J. EDUC. 103, 103 (2006). 13. NAT’L CTR. FOR EDUC. STATISTICS, COMMON CORE OF DATA, PUBLIC ELEMENTARY/SECONDARY SCHOOL UNIVERSE SURVEY (2013), https://nces.ed.gov/ccd/pubsc huniv.asp. 14. SUSAN AUD ET AL., NAT’L CTR. FOR EDUC. STATISTICS, THE CONDITION OF EDUCATION 2012, at 22 (2012), http://nces.ed.gov/pubs2012/2012045.pdf. 15. Genevieve Siegel-Hawley & Erica Frankenberg, Does Law Influence Charter School Diversity? An Analysis of Federal and State Legislation, 16 MICH. J. RACE & L. 321 (2011). 16. Press Release, U.S. Dep’t of Educ., U.S. Department of Education Awards Nearly $5 Million in Charter School Grants for Planning, Program Design, Implementation and Dissemination (October 5, 2011), https://www.ed.gov/news/press-releases/us-department- 2016] SEGREGATION IN CHARTER SCHOOLS 255 report, “the fastest growing sector of American public education.”17 As of the 2011-12 academic year, twenty-five districts in the United States (nearly all of them urban) had at least 20% of their student enrollment in charter schools.18 The rapid growth in charter schools has occurred alongside significant and equally rapid demographic changes in U.S. schools, particularly in urban areas where charters are most common.19 According to William H. Frey’s analysis of 2010 Census data, central cities have experienced a dramatic increase in the proportion of Latinos and African Americans in the past decade. As of the 2010 Census, 43% of large metro areas were predominately non-White, up from 29% in 1990 at the creation of the charter school movement.20 Poverty rates have also risen among these groups. 21 The number of non-native English speakers also increased 80% between the 1990 and 2010 Census.22 A large proportion of the students who are classified as English Language Learners (ELL) also reside within central cities.23 The rapid rise in charter school numbers and enrollment, and the concurrent demographic shifts in the contexts in which charters are most likely to open, lead us to question how charters interact with these demographic patterns. The extent to which charters, particularly in central cities, are serving the highest need populations in those contexts (English Language Learners, low-income students, and Special Education students) has been relatively under-examined within the research literature. In this article, therefore, we examine the extent to which charters in the state of Texas are serving high needs populations (English Language Learners, Special Education, and low-income students) at the same rates as traditional public schools. We first conduct statewide analyses to compare charter school and traditional public district demographics by locality. We also compare levels of segregation of those populations between traditional public schools by locality and charter status. We then conduct local-level analyses to understand education-awards-nearly-5-million-charter-school-grants-planning-program-design- implementation-and-dissemination. 17. NAT’L ALL. FOR PUB. CHARTER SCH., A GROWING MOVEMENT: AMERICA’S LARGEST CHARTER SCHOOL COMMUNITIES 2 (7th ed. 2012), http://www.publiccharters.org/wp- content/uploads/2014/01/NAPCS-2012-Market-Share-Report_20121113T125312.pdf. 18. Id. 19. Erica Frankenberg et al., Choice Without Equity: Charter School Segregation, 19 EDUC. POL’Y ANALYSIS ARCHIVES (2011), http://epaa.asu.edu/ojs/article/view/779. 20. WILLIAM H. FREY, BROOKINGS INST., STATE OF METROPOLITAN AMERICA, THE NEW METRO MINORITY MAP: REGIONAL SHIFTS IN HISPANICS, ASIANS, AND BLACKS FROM CENSUS 2010, at 4 (2011), http://www.brookings.edu/~/media/research/files/papers/2011/8/31%20ce nsus%20race%20frey/0831_census_race_frey.pdf. 21. SUZANNE MACARTNEY, U.S. CENSUS, AMERICAN COMMUNITY SURVEY BRIEFS, CHILD POVERTY IN THE UNITED STATES 2009 AND 2010: SELECTED RACE GROUPS AND HISPANIC ORIGIN (2011), https://www.census.gov/prod/2011pubs/acsbr10-05.pdf. 22. CHHANDASI PANDYA ET AL., MIGRATION POL’Y INST., LIMITED ENGLISH PROFICIENT INDIVIDUALS IN THE UNITED STATES: NUMBER, SHARE, GROWTH, AND LINGUISTIC DIVERSITY 3 (2011). 23. See NAT’L CTR. FOR EDUC. STATISTICS, supra note 13, at 30. 256 STANFORD LAW & POLICY REVIEW [Vol. 27:251 high-need students demographic patterns within the footprint of a large urban district to evaluate the extent to which students with greater than average instructional needs are served by charter schools in equal proportion to the neighboring public schools. We conclude by descriptively examining the access and enrollment of high-need students in several popular “exemplar” charters. We find that, while Texas charters appear to be demographically similar to traditional public schools at the aggregate, the granularity provided by geospatial analyses demonstrates that charters under-enroll ELL students and special education students relative to nearby non-charter schools. We argue that states should hold charters more accountable for special populations by designing policy approaches that remedy the extent to which they are failing to serve our nation’s highest needs students. I. BACKGROUND Since the inception of the charter school movement, concerns have been raised about access and equity, particularly for high needs students.24 These concerns are linked directly to the incentives embedded in markets: under conditions of competition, organizations (such as charters) may seek to maximize their profits, or their market position, by targeting relatively easier- to-serve clientele.25 Consistent with this theory, charters have been accused by many of strategically recruiting relatively advantaged, or “easier-to serve,” students from nearby public schools.26 Others contend that competition, instead of leading to stratification, reduces market barriers by un-linking residence from schooling opportunity.27 Charter advocates, in support of this theory, point to national data showing that, in the aggregate, charter schools serve higher percentages of low-income students, and higher proportions of African American and Latino students, than traditional public schools. 28 Indeed, a recent report by charter advocacy organization The National Alliance for Public Charter Schools noted “public 24. Julian Vasquez Heilig et al., Is Choice a Panacea? An Analysis of Black Secondary Student Attrition from KIPP, Other Privately Operated Charters, and Urban Districts, 2 BERKELEY REV. EDUC. 153 (2011). 25. Natalie Lacireno-Paquet et al., Creaming Versus Cropping: Charter School Enrollment Practices in Response to Market Incentives, 24 EDUC. EVALUATION & POL’Y ANALYSIS 145 (2002). 26. See Diane Ravitch, Con: Say ‘No Thanks’ to Charter Schools, MONTGOMERY ADVERTISER (Feb. 11, 2012), https://iearegion28.wordpress.com/2012/02/12/con-say-no- thanks-to-charter-schools-diane-ravitch-for-the-montgomery-advertiser-montgomeryadverti ser-com. 27. See JOSEPH P. VITERITTI, CHOOSING EQUALITY: SCHOOL CHOICE, THE CONSTITUTION, AND CIVIL SOCIETY (1999); Joe Nathan, Heat and Light in the Charter School Movement, 79 PHI DELTA KAPPAN 499, 499-505 (1998). 28. CAL. CHARTER SCH. ASSOC., Dispelling Myths About Charter Schools, http://tinyurl.com/jf5h9ag; NAT’L ALL. FOR PUB. CHARTER SCH., supra note 17. 2016] SEGREGATION IN CHARTER SCHOOLS 257 charter schools across the nation enroll, on average, a greater percentage of low-income students (46% versus 41%), Black and Latino students (27% versus 15% and 26% versus 22%, respectively), and students who perform lower on standardized assessments before transferring to charter schools (percentages).”29 Researchers analyzing data at the local district level, however, have found that the illusion of diversity tends to disappear when charters are compared to their home districts. Several researchers have found, using district demographics as the point of reference, that charters are in fact quite segregated, enrolling either disproportionately more white students, or disproportionately high concentrations of students of color. 30 Studies examining individual student transfer data between traditional public schools and charters have similarly found that students tend to transfer into charter schools in which students from their own background are more represented.31 Advocates counter these data by arguing that, to the degree that segregation exists within the charter system, it is a byproduct of both the geographic location of charters, and the explicit goal of many charters to serve the most disadvantaged student populations.32 Some “ethno-centric” charters have, in fact, been founded with an explicit goal of serving students from a particular cultural background, typically those who have often been marginalized in traditional public school settings. There has been criticism, however, about the failure of even these (often intentionally) ethnically and racially isolated schools to serve sub-populations 29. NAT’L ALL. FOR PUB. CHARTER SCH., DETAILS FROM THE DASHBOARD: CHARTER SCHOOL RACE/ETHNICITY DEMOGRAPHICS 1 (2012), http://www.publiccharters.org/wp- content/uploads/2014/01/NAPCS-2010-2011-Race_Ethnicity-Details-from-the-Dashboard_ 20120516T152831.pdf. 30. GARY MIRON ET AL., EDUC. & PUB. INT. CTR. & EDUC. POL’Y RES. UNIT, SCHOOLS WITHOUT DIVERSITY: EDUCATION MANAGEMENT ORGANIZATIONS, CHARTER SCHOOLS, AND THE DEMOGRAPHIC STRATIFICATION OF THE AMERICAN SCHOOL SYSTEM (2010), http://epicpolicy.org/files/EMO-Seg.pdf; GARY MIRON & CHRISTOPHER NELSON, WHAT’S PUBLIC ABOUT CHARTER SCHOOLS? LESSONS LEARNED ABOUT CHOICE AND ACCOUNTABILITY (2002); Casey D. Cobb & Gene V. Glass, Ethnic Segregation in Arizona Charter Schools, 7 EDUC. POL’Y ANALYSIS ARCHIVES (1999), http://epaa.asu.edu/ojs/article/view/536; Linda A. Renzulli & Lorraine Evans, School Choice, Charter Schools, and White Flight, 52 SOC. PROBS. 398 (2005). But see NAT’L ALL. FOR PUB. CHARTER SCH., supra at note 29. 31. Robert Bifulco & Helen F. Ladd, School Choice, Racial Segregation, and Test- Score Gaps: Evidence from North Carolina’s Charter School Program, 26 J. POL’Y ANALYSIS & MGMT. 31 (2006); David A. Garcia, Academic and Racial Segregation in Charter Schools: Do Parents Sort Students into Specialized Charter Schools?, 40 EDUC. & URB. SOC’Y 590 (2008); Yongmei Ni, The Sorting Effect of Charter Schools on Student Composition in Traditional Public Schools, 26 EDUC. POL’Y 215 (2012); Kevin Booker et al., The Effect of Charter Schools on School Peer Composition, (RAND CORP., Working Paper No. WR-306-EDU, 2005), http://www.rand.org/pubs/working_papers/WR306. 32. Dave Weber, Grouping Kids by Race or Ethnicity in Charter Schools Has Merit, Backers Say, ORLANDO SENTINEL (May 1, 2011), http://articles.orlandosentinel.com/2011- 05-01/news/os-charter-schools-segregation2-20110501_1_charter-schools-kipp-charter- poorer-quality-teachers. 258 STANFORD LAW & POLICY REVIEW [Vol. 27:251 with greater instructional needs. Several studies that have compared charters to the districts in which they are located have found that charters under-enroll English Language Learner (ELL) students,33 Special Education students,34 and students eligible for free or reduced-price lunch (FRL).35 Researchers have posed a number of reasons for these trends. Some speculate that this local under-enrollment is attributable to special restrictions on enrollment that charters are able to implement, such as admissions criteria and parent involvement requirements, which can deter enrollment of the most high-need student populations.36 The under-enrollment of the most high-needs students, others contend, may also be due to intentional recruitment and marketing efforts aimed at students who are relatively less costly. 37 Such incentives, as Lacireno-Paquet et al. (2002) argued, may be particularly strong for for-profit charters. The lack of a requirement to provide transportation in some states, or to provide transportation over longer distances, also may contribute to under-enrollment of the most at-risk students.38 While the existing research literature is suggestive of problems with access to charters, particularly vis-à-vis high-need students, the existing studies rely on comparisons between charter demographic data and the aggregate demographics of the district in which the charters are located.39 Such charter to district comparisons, however are limited by the size, boundaries, and demographics of the reference school district. These comparative analyses furthermore miss important spatial dimensions of access to charters. Consider, for example, a charter school with a poverty rate of 35%: if the charter is located in a district with a 35% rate of poverty, the charter would be considered reflective of the context in which the school was located, which would lead to the conclusion that this particular school was “not skimming” students. However, if this charter school were located in a high poverty neighborhood within that district, and was proximal to several schools with poverty levels of 70% or greater, a key dimension of inequity would be missed by the first analysis; the local “differential” between the school and the local neighborhood schools would be much higher, at 35%––a clear indication that the school is not 33. See MIRON ET AL., supra note 30, at 18-22; Frankenberg et al., supra note 19, at 42- 46. 34. KARA FINNIGAN ET AL., U.S. DEP’T OF EDUC., EVALUATION OF THE PUBLIC CHARTER SCHOOLS PROGRAM: FINAL REPORT (2004), https://www2.ed.gov/rschstat/eval/choice/pcsp- final/finalreport.pdf; U.S. GOV’T ACCOUNTABILITY OFF., GAO-12-543, CHARTER SCHOOLS: ADDITIONAL FEDERAL ATTENTION NEEDED TO HELP PROTECT ACCESS FOR STUDENTS WITH DISABILITIES (2012), http://www.gao.gov/assets/600/591435.pdf. 35. Siegel-Hawley & Frankenberg, supra note 15, at 363. 36. See MIRON ET AL., supra note 30, at 7; Frankenberg et al., supra note 19, at 35-42. 37. See MIRON ET AL., supra note 30, at 16; Lacireno-Paquet et al., supra note 25, at 155. 38. Siegel-Hawley & Frankenberg, supra note 15, at 347-350. 39. See MIRON ET AL., supra note 30, at 3. 2016] SEGREGATION IN CHARTER SCHOOLS 259 serving low income students at equal rates. This is a particularly relevant point given that many charters are intentionally located in such neighborhoods.40 Prior studies, therefore, have largely yet to consider the spatial dimensions of access to charter schools, by understanding how charters compare with the schools in their immediate (and often highly segregated) neighborhoods. One study that has considered the spatial dimensions of access in charters is Cobb and Glass (1999), which focused on racial and ethnic segregation in Arizona charter schools.41 This study illustrated that, in the aggregate, charters were reflective of the state’s demographics; yet when compared with schools that were geographically nearby, they found charters were highly segregated. This present analysis seeks to extend the Cobb and Glass analysis by examining the extent to which charters are serving high-need students (ELL, FRL, and Special Ed) at the same rates as nearby public schools in Texas. II. THE TEXAS CHARTER SCHOOL CONTEXT The Texas law authorizing charter schools was passed in 1995 and approved the creation of three different classes of charter schools: campus charters (conversions of traditional public schools, or in-district charters established by districts); open enrollment charters (brand new schools created by non-profits, governmental agencies, or institutions of higher education); and “home rule” charters which allows an entire school district to convert to charter status.42 When the law was originally passed, a cap was set on the number of open enrollment charter schools, with a limit of twenty.43 In 1997, state legislation increased the cap to 120, and instituted the “75% rule”, allowing an unlimited number of charters to be created (above the cap) as long as their student population consisted of at least 75% “at risk” students.44 This provision resulted in a significant increase in the number of charters, many of which were perceived to be low quality. As a result, in 2001 the “75% rule” was eliminated and the number of charters was capped at 215 total, although these charters can (and do) operate multiple campuses.45 There are no limits on the number of charters schools sponsored by colleges and universities.46 The legislation also 40. Jeffrey R. Henig & Jason A. MacDonald, Locational Decisions of Charter Schools: Probing the Market Metaphor, 83 SOC. SCI. Q. 962 (2002). 41. See Cobb & Glass, supra note 30. 42. CATHERINE MALONEY ET AL., TEX. CTR. FOR EDUC. RESEARCH, TEXAS OPEN- ENROLLMENT CHARTER SCHOOLS: 2005-06 EVALUATION 5 (2007), http://tea.texas.gov/Work Area/DownloadAsset.aspx?id=2147502646; Francisco Penning & John R. Slate, Charter Schools in Texas: An Overview, 6 INT’L J. EDUC. LEADERSHIP PREPARATION 1, 2 (2011). 43. See Penning & Slate, supra note 42, at 2. 44. Id. at 2. 45. LORI L. TAYLOR ET AL., STATE OF TEX. EDUC. RESEARCH CTR. AT TEXAS A&M UNIV., EVALUATION OF TEXAS CHARTER SCHOOLS 2009-10, at ii (2011), http://tea.texas.gov/ WorkArea/DownloadAsset.aspx?id=2147502001. 46. Id. 260 STANFORD LAW & POLICY REVIEW [Vol. 27:251 gave the commissioner increased oversight over charters and charter application approvals, and as a result the number of new charters approved each year was reduced.47 The state of Texas currently has the second largest number of charter schools (581) in the United States, below California (985). At 190,000 students, Texas is also second to California (413,000) in terms of the number of students enrolled in charter schools.48 The overall proportion of students enrolled in charter schools in Texas, however, was relatively low as of 2012. Just 3.8% of the state’s students attended a charter school in the state, which is under the national average of 4.2%.49 Consistent with previous national studies of charter demographics, state aggregate data shows that charters in Texas serve a highly diverse student population, although demographics vary somewhat by charter type. On average, Texas’ open enrollment charters (non-district affiliated) serve a larger proportion of Latino and African American students and a higher proportion of students eligible for free and reduced-price lunch compared to traditional public school districts across the state.50 In-district charters (charters affiliated with public districts) serve even higher proportions of these populations compared with traditional public districts across Texas as a whole.51 Both types of charters, however, serve substantially fewer students receiving Special Education services. 52 The proportion of ELL students served is roughly equivalent between traditional public districts and open enrollment charters; in- district charters, however, serve higher proportions of ELL students.53 In Texas, most charters are located within the state’s major metropolitan areas. According to Taylor et al., more than half of all open enrollment charters are located in the Houston, Dallas, and San Antonio metropolitan areas.54 The largest numbers of charters were in the Houston metro (with 109 charters, enrolling 2.4% of students in the area); the Dallas metro (with 87 charters, 3.5% of overall enrollment in the area); the San Antonio metro (55 charter schools enrolling 3.1% of the metro’s students); and the Austin metro (35 charters, enrolling 1.9% of the metro’s students).55 Statewide, 90% of in-district charters were located in Houston, Dallas, or San Antonio.56 It is important to note that the growth of charters in Texas has coincided with a rapid increase in the diversity of the overall Texas student population. Between the 2000-01 and 2009-10 academic years, ELL enrollment has grown 47. See MALONEY ET AL., supra note 42, at 11. 48. NAT’L CTR. FOR EDUC. STATISTICS, supra note 13. 49. Id. 50. See TAYLOR ET AL., supra note 45, at vi-vii. 51. Id. 52. Id. at vii. 53. Id. 54. Id. at v. 55. Id. at 15 56. Id. at v. 2016] SEGREGATION IN CHARTER SCHOOLS 261 by more than 24%, from 569,000 to 708,000 students.57 The proportion of students designated by the state as “Economically Disadvantaged”—those eligible for free lunch (income at 130% of the federal poverty line) or reduced- price lunch (185% of poverty) and other federal assistance—rose from 52% in 2003 to 59% percent in 2011. 58 Notably, these populations rose most substantially in the metropolitan areas (Houston, Dallas, San Antonio) housing the greatest number of the state’s charter schools.59 Given the rapid growth in charters alongside swift demographic change in Texas public schools, we seek to examine levels of charter school access and segregation for students from different backgrounds. We specifically seek in this analysis to examine the extent to which students with relatively higher learning needs (ELL, Special Education students, and students eligible for free and reduced-price lunch) are represented in Texas charter schools. III. DATA/METHODOLOGY In this Article, we examine access and segregation of ELL, Special Education (SPED), and Economically Disadvantaged students in Texas charter schools. We chose not to focus on the access of racial/ethnic groups (i.e., African-American, Latino, etc.) because as noted previously, some charter schools are explicitly founded to serve a particular racial/ethnic sub-group or cultural group, making racial and ethnic segregation a complex (albeit important) question vis-à-vis charters. Furthermore, few studies have specifically focused on the extent to which charters serve the “highest need” learners, such as ELL, SPED, and low-income students, who often require extra supports in school. This study is therefore intended to fill this gap in the literature. In our analysis, we first examine patterns of segregation for each of the previously mentioned groups in charter schools at the state level. We then conduct a more specific analysis of charters compared with the different school options within their immediate proximity in the Houston metropolitan area. A. State-Level Analyses For the state-level analysis, we utilized publicly available school-level data from the Texas Public Education Information Management System (PEIMS). We conducted ANOVAs, models used to analyze the differences among group means, to consider levels of access and segregation for Special Education, Economically Disadvantaged, and ELL students in Texas charter schools. We compared access and segregation in charters schools compared to traditional 57. AUD ET AL., supra note 14, at 155 tbl. A-8-1. 58. TEX. EDUC. AGENCY, SELECTED AEIS STATE DATA: A MULTI-YEAR HISTORY FOR 2003-2011 (2012), https://rptsvr1.tea.texas.gov/perfreport//aeis/hist/state.html. 59. D’Ann Petersen & Laila Assanie, The Changing Face of Texas: Population Projections and Implications, FED. RES. BANK OF DALLAS 37 (2005), https://www.dallasfe d.org/assets/documents/research/pubs/fotexas/fotexas_petersen.pdf. 262 STANFORD LAW & POLICY REVIEW [Vol. 27:251 public districts by locality (urban, suburban, rural, etc.). To examine segregation between students in our high-need student populations compared with the overall student population, we conducted a Dissimilarity Index (DI) Analysis. The DI, models used to measure the relative separation or integration of groups across all schools, indicates the percentage of a group's population that would have to change schools in order to have each school equal the overall population in the state. The specification of the DI is: ! 1 ℎ! 𝑠! − 2 𝐻 𝑆 !!! where: si = the high needs (ELL, FRL, and Special Ed) population of the ith locality S = the total high needs population of students in Texas hi = the non-high needs student population of the ith locality H = the total non-high needs student population in Texas B. Local-Level Analyses Houston is an informative case, because it is the seventh largest school district in the United States, is the largest public school district in the state, and contains numerous school types within the district. Within the Houston Independent School District (HISD) boundaries, there are more than 100 charter schools in operation, some of which are “campus charters” operated by HISD, others which are under the umbrella of the district but externally managed, and still many more which operate independently of the school district entirely. The school district is also home to an extensive number of magnet programs in both primary and secondary schools, many of which are schools of choice. There are also a large number of “traditional public schools” in the district without any magnet or charter affiliation. This mixture of schooling types in the area is representative of school choice options playing out in the broader national context. As stated previously, prior studies of charter demographics that compare characteristics of charter schools to state or national aggregates tend to mask significant local variations in patterns of segregation in charter schools vis-à- vis the contexts in which they are located. The few studies that have attempted to provide a more nuanced understanding about how charter schools compare to nearby public schools have largely compared local charter demographics to that of their home district.60 This type of analysis is limited in that districts vary widely in terms of levels of school segregation, and thus comparing charters to aggregate district level populations has more limited specificity. 60. See, e.g., MIRON & NELSON, supra note 30. 2016] SEGREGATION IN CHARTER SCHOOLS 263 In this analysis, we compare charters not to state or district averages, but to schools that are geographically nearby. We build on the work of Cobb and Glass (1999) who analyzed how charters in Arizona compared to nearby public schools utilizing a spatial geographic mapping analysis. This type of geographic analysis is required to understand the relationship between charters and segregation, they argue, to deal with the insufficiency of existing statistical measures of segregation vis-à-vis small-enrollment charter schools. They note: Attempts to depict the magnitude of differences among schools’ ethnic compositions while holding constant size and grade level through various statistical measures prove problematic. Popular measures of level of segregation, such as the Dissimilarity Index, and measures of equity, such as the Gini coefficient or Lorenz Curve, are highly sensitive to numbers of students in schools. The relative smallness of charter schools makes comparisons via these types of measures questionable. Moreover, within this context, these indices are simply powerless to detect between-school segregation. No statistical technique can aptly discern differences among urban schools as completely as maps.61 Although Cobb and Glass’ (1999) geographic analysis of charters improved on previous studies with its focus on nearby schools, they acknowledged a few limitations. First, their analysis lacked information regarding segregation of ELL students, as well as other high-need students (including students eligible for Special Education and students eligible for free or reduced-price lunch). They focused instead on racial segregation (specifically on white/non-white segregation) exclusively. Second, operationally their analysis was limited by the lack of specificity about how they defined “nearby.” While they used maps to identify nearby schools, they provided no explicit definition of “nearby” (e.g., a particular radius around a school) which limits replicability.62 To deal with these limitations, in this local-level analysis we build upon and extend Cobb and Glass’ (1999) spatial analysis, as well as the Miron et al. (2009) analysis in several ways. We utilize mapping technology to examine how charter schools in Houston compare to nearby local schools on three demographic measures: Segregation of ELL, Special Education, and Economically Disadvantaged students. We also sought explicit, replicable, procedures for our mapping analysis. 1. Procedures We first identified all charter schools that were located physically within the boundaries of HISD. Because the state does not provide an aggregate list of charters operating within school districts, we utilized the National Center for 61. Cobb & Glass, supra note 30, at 8. 62. Id. at 9. 264 STANFORD LAW & POLICY REVIEW [Vol. 27:251 Educational Statistics’ (NCES) School District Demographic System (SDDS) mapping software, which contains data on all public school districts and most local school attendance boundaries within districts.63 Once the charter schools that lay within the defined boundary were identified, we compared each school’s location on the map with the physical address location provided by each school’s website. The address was then placed into Google Maps and verified with each of the two maps.64 Based on this procedure, we identified 113 charter schools operating within HISD’s boundary. We then sought to eliminate from the data outlier schools such as those classified as juvenile detention centers, residential treatment centers, virtual schools, foreign language schools, and otherwise similarly situated for highly unique student populations. Eleven schools were classified as unique outliers, leaving 102 charter schools in Houston for our analysis. We then further analyzed this list to identify schools that were labeled as “charters,” but were not necessarily operating as schools of choice. Thus, we pulled out the six HISD campus charters that had a designated and required attendance boundary. Given that these six schools were not technically schools of choice, we added them instead to the HISD public schools. We also eliminated one additional school (HISD’s MC Williams Elementary), which was classified in the PEIMS as both a charter and a magnet school in the data set. Because it is a school with a dedicated attendance boundary, we considered it a magnet school (see Table 1). 63. School District Demographic System, NAT’L CTR. FOR EDUC. STATISTICS, https://nces. ed.gov/surveys/sdds/datatools.asp (last visited Aug. 6, 2016). 64. For some schools this was a daunting task because the name of the individual school campus had changed. To remedy this issue, we utilized the school and district websites to provide more consistency in the geo-spatial analyses. 2016] SEGREGATION IN CHARTER SCHOOLS 265 TABLE 1: Classification System for Schools in Spatial Analyses • Dedicated attendance zone Traditional Public • Adheres to district- and state- School level policies and Houston ISD Affiliated requirements • Offered magnet program Magnet within a traditional public School school • Dedicated attendance zone • Dedicated attendance zone with opt-out only option for HISD Charters area students with Attendance • HISD buildings and facilities Zone used • Classified by HISD as HISD Internal Charter • No attendance zone • Pulling from multiple HISD attendance zones HISD Charter • Staffed by HISD staff with no • HISD buildings and facilities Attendance Zone used Open Enrollment Charters • Classified by HISD as HISD Internal Charter • No attendance zone • Not staffed by HISD staff HISD External • Not held in HISD buildings Campus Charter • Contract for operation between HISD and Charter school renewed annually • Classified by HISD as open enrollment charter Externally • Charter granted by the state of Managed Texas Charters • No HISD jurisdiction • Enrolls students who would otherwise attend HISD • Various types of schools not included in study due to Excluded specialized circumstances or Excluded Schools populations served (i.e., juvenile justice centers, dropout prevention and credit recovery, severely disabled) 266 STANFORD LAW & POLICY REVIEW [Vol. 27:251 This procedure left us with ninety-five charter schools within the HISD boundaries operating as schools of choice without a dedicated attendance zone. Each of these ninety-five schools was then analyzed to verify whether that school was actually operating under a charter, and whether or not that charter relied on a partnership with HISD or was functioning independently (operated by an external agency). The list of schools was verified via five main sources: The NCES SDDS Map, The HISD Website, Texas Education Agency Academic Excellence Indicator System (AEIS) reports, a Texas state Senate List, and a HISD Charter School list obtained from the district. Of the ninety- five open enrollment charters, twenty-six had a relationship with HISD, and sixty-nine were independent of the district altogether. These ninety-five schools serve as the basis of our core analysis, in which we directly compared them to the public schools in their immediate proximity. 65 Once all charters were verified by location, operation type, relationship to HISD, and correspondence with pertinent years of operation under that designation, we proceeded to compare the charters to nearby non-charter public schools.66 2. Charters Versus Attendance Zone Schools Within a One-Mile Radius In our analysis, we compared charters to the schools whose attendance zones were located within a one-mile geographic radius. We used this radius because HISD averages a school every 1.2 miles. 67 This approach to the analysis is important because charters draw students from more than the local school attendance zone in which they are located. As a result, we used the NCES SDDS mapping software and its included radial tool to draw a one-mile radius around each of the 95 charter schools to identify all attendance boundaries of schools that sit within that area. We then compared the charter demographics to the demographics of any schools with attendance boundaries in the one-mile radius (see Figure 1). In our mapping analysis we found two different types of schools with which to compare the charter schools: traditional public schools and magnet schools (the majority of which had a dedicated attendance boundary).68 65. There were a number of barriers to discovering the status of charters (in partnership with HISD, or independently operated). Schools operating in HISD were the most difficult to track, because there was no single exhaustive list of external charter partnerships with the HISD available. Instead, as stated in the main text, the schools had to be verified via five main sources. Each list displays a different set of schools. Once we had a name for a school, using the state-level PEIMS data through the Academic Excellence Indicator System (AEIS), which clearly identifies the operating entity for each school under “District Name,” we were able to verify the chartering entity. 66. See Appendix C. 67. HISD is 333 square miles and has 238 schools. Hous. Indep. Sch. Dist., 2015-2016 Facts and Figures, http://tinyurl.com/hmpljcn. 68. Of the ninety-five charter schools in operation, forty of them were housed at a site that was home to one or more schools with separate PEIMS codes. In each of these cases, a  2016] SEGREGATION IN CHARTER SCHOOLS 267 FIGURE 1: Determining Schools for Comparison Diagram Deady MS Milby HS Sanchez Elem. Crespo Elem. Raul Yzaguirre School for Success Chavez HS Ortiz MS, Legend Jones HS Park Place El. School Boundaries High School Middle School Elementary School School Type Charter School Traditional Public School or School Note: Comparison schools included any school with an attendance boundary within a one- mile radius zone of the selected charter school. Further, we found that many charter schools served grade levels that were not perfectly comparable to the traditional public and magnet schools. Where many of the traditional and magnet schools follow a traditional elementary, middle, and high school breakdown within their respective buildings, a number of charter schools serve grades K-12 and numerous variations thereof. In such instances, the school was compared with the K-12 aggregate within that mile radius. Within our comparisons the numerator was between one and ten. Typically, charter elementary schools were compared with a greater number of schools than those at the high school level. This is the case due to the fact there are more elementary schools in any given district. On average, we found four (3.77) comparable schools with which to compare each HISD area charter school. total of eighteen sites, the population totals were weighted and compared to each of the individual HISD campus attendance zones that fell within that one-mile radius. 268 STANFORD LAW & POLICY REVIEW [Vol. 27:251 3. Calculations of Demographic Difference For each set of comparisons, we calculated the weighted percentage point differential between the charter’s enrollment of high-need students (ELL, students identified as Special Education, and students designated as “Economically Disadvantaged”69) to that of the weighted average of all schools within their one-mile radius (either traditional public school “TPS” or magnet school). Once we calculated the differential for each comparison group, we set a threshold for identifying different levels of existing segregation within schools and area. These numbers are related to the cutoffs established by Cobb and Glass and were tailored to the type of population being compared. As Special Education populations are a much smaller share of a school’s total population, segregation was established at a much smaller differential than was socioeconomic status (FRL), which makes up a much larger portion of a school’s population. The cutoffs were as follows: English Language Learners (ELL): Segregative = +/- 10%, Extreme Segregative = +/- 20% Special Education (SPED): Segregative = +/- 6%, Extreme Segregative = +/- 10% Economically Disadvantaged: Segregative = +/- 10%, Extreme Segregative = +/- 20% Beyond these individual comparison calculations, we identified all of the public schools operating within the HISD boundary, save for those previously excluded unique campuses, and calculated the area aggregate. Here, we calculated 332 schools operating within the area. These numbers were then broken down and compared by type. In operation we found 122 HISD traditional public school campuses (including the 6 HISD charter campuses with attendance boundaries), 115 HISD magnets, and our 95 external charters. IV. FINDINGS Our findings are organized into two sections. In the first section, we present our state-level analysis comparing the demographics of charter schools to the demographics of the overall state population. In the second section, we present our local level analysis, comparing charters to traditional public schools in Houston. 69. Students designated as Economically Disadvantaged by the Texas Education Agency are those students who are eligible for free or reduced price lunch or other public assistance. 2016] SEGREGATION IN CHARTER SCHOOLS 269 A. State-Level Descriptive and ANOVA Statistical Analyses In our first analyses, we utilized ANOVAs to compare charter schools as a group to the overall traditional public districts by locality across the state. We then conducted Dissimilarity Index (DI) analyses to examine segregation between students in our high-need students (ELL, Special Education, and Economically Disadvantaged students) compared with the overall student population by locality and charter school designation. 1. ANOVA Analysis The student enrollment of ELL students in charters is about 14% on average across the state. The average composition of charter schools is about 9% less than urban schools, 3% less than suburban schools, and 7% more than rural schools. Not only are charter schools serving a substantially lower proportion of ELL students than urban schools, but also they are also enrolling less than suburban schools. Each of the ELL enrollment gaps tested significant (p < .000) in the ANOVA analyses when you compare charters to districts by locality (Urban, Suburban, Rural). The student enrollment of Economically Disadvantaged students in charters is about 72% on average across the state. The average composition of charter schools is about 1% more than urban schools, 18% more than suburban schools, and 12% more than rural schools. The gap in Economically Disadvantaged student enrollment at charters compared to rural and suburban schools tested significant (p < .000) in the ANOVA analyses. The Economically Disadvantaged student enrollment gap between charters and urban schools was not significant. The student enrollment of Special Education students in charters is about 2% more on average across the state. The average composition of charter schools is about 1% more than urban schools, 2% more than suburban schools, and 0.2% less than rural schools. The gaps in the enrollment of Special Education students at charters compared to urban, rural, and suburban schools did not test significant in the ANOVA analysis. 270 STANFORD LAW & POLICY REVIEW [Vol. 27:251 TABLE 2: ANOVA Sum of Mean Squares df Square F Sig. Campus 2011 Between Groups 714432.470 3 238144.157 275.244 .000 Student: Within Groups 7148377.263 8262 865.211 Hispanic Total 7862809.733 8265 Percent Campus 2011 Between Groups 307204.008 3 102401.336 304.952 .000 Student: LEP Within Groups 2774339.982 8262 335.795 Percent Total 3081543.991 8265 Campus 2011 Between Groups 18227.482 3 6075.827 124.940 .000 Student: Gifted Within Groups 401779.780 8262 48.630 & Talented Total 420007.262 8265 Percent Campus 2011 Between Groups 206879.269 3 68959.756 127.032 .000 Student: At Risk Within Groups 4485046.567 8262 542.852 Percent Total 4691925.836 8265 Campus 2011 Between Groups 8049.632 3 2683.211 23.858 .000 Student: Special Within Groups 929177.678 8262 112.464 Ed Percent Total 937227.310 8265 Campus 2011 Between Groups 137796.227 3 45932.076 157.568 .000 Student: African Within Groups 2408424.157 8262 291.506 American Total 2546220.384 8265 Percent 2. Dissimilarity Index Analysis The dissimilarity index shows that rural schools had the lowest DI at .06. The calculated DI for charters was 0.08, which was less than urban (.10) and suburban schools (.12). Notably, suburban schools had the highest DI for English Language Learners. The DIs for all localities are below 2% for Special Education students. This means that, relative to state proportions, very few Special Education students would need to move in order for the Special Education and Non- Special Education populations to have the same distribution as the total group in the state of Texas. The dissimilarity index shows that urban public schools are the most segregated by SES. In the State of Texas, charters had the lowest DI at 4%. Rural and suburban schools had similar DIs at 9% and 8%, respectively. 2016] SEGREGATION IN CHARTER SCHOOLS 271 TABLE 3: Texas English Language Learner Dissimilarity Index by Locality ELL SPED Economically Disadvantaged Charter .08 .01 .04 Urban .10 .00 .13 Suburban .12 .02 .08 Rural .06 .01 .09 B. Local-Level Analyses: Charters in Houston Footprint In the following section, we present our local-level analyses of charter schools in the Houston Independent School District. We conduct two separate analyses. We first descriptively compare charters as a group to district averages in terms of enrollment of high needs students (ELL, Economically Disadvantaged, and Special Education students). We then conduct several spatial analyses, models utilizing the locations of the schools being analyzed, to examine the high-need student demographics through a comparison of charters with nearby non-charter public schools. 1. Charters Versus HISD Schools: Descriptive Analysis We now turn to descriptively comparing charters versus the averages by school in HISD. We find that, at the aggregate, there are some disparities between charters and HISD schools with respect to the proportion of ELL students, Special Education students, and Economically Disadvantaged students served. When comparing charters to nearby public schools (or “neighborhood” schools) in HISD (those that are not schools of choice) some differences become apparent with respect to ELL enrollment: although traditional public schools serve about 45% ELL students, externally managed charters enroll just 30% as a whole (see Table 4). Charters as a whole also enroll fewer Special Education students compared with traditional public schools (5% versus 7%). The proportion of Economically Disadvantaged students enrolled in charter schools, however, is comparable to the proportion enrolled in HISD’s traditional public schools. 272 STANFORD LAW & POLICY REVIEW [Vol. 27:251 TABLE 4:Student Totals by School Type & Subcategory (2011-2012) % SPED % Econ. Student % ELL Disadv. Disadv. Enroll SPED Econ ELL N HISD Area 332 224,228 67,063 29.9% 16,856 7.5% 183,285 81.7% Aggregate* HISD Affiliated 279 203,066 60,639 29.9% 15,900 7.8% 163,199 80.4% Schools* HISD Traditional Public Schools 116 79,417 36,090 45.4% 5,716 7.2% 72,505 91.3% Excluding Campus Charters HISD Campus 6 3,922 958 24.4% 226 5.8% 2,861 72.9% Charters* HISD 115 105,474 19,324 18.3% 9,189 8.7% 76,547 72.6% Magnets Open Enrollment 95 35,415 10,691 30.2% 1,725 4.9% 31,372 88.6% Charters External 69 24,495 7,387 30.2% 1,335 5.5% 21,691 88.6% Charters HISD Affiliate Charters 26 10,920 3,242 29.7% 389 3.6% 9,513 87.1% with no Attendance Zone Note: HISD Area Aggregate excludes extraordinary campuses including detention and treatment centers. The number of all HISD Affiliated Schools is determined by HISD Facts and Figures, thus the variation in total number of schools. Additionally, HISD Campus Charters excludes one campus: M.C. Williams Middle School, which is dually classified as a campus charter school and STEM magnet school, was calculated as a magnet school. N.D. indicates no data. 2. Charters Versus Nearby HISD Schools: Spatial Analysis In this second part of our analysis, we compare charters physically located within HISD district boundaries to several different groupings of HISD schools. As with the prior comparison, our analysis of charter schools includes both charters that are open enrollment charters operated by an external agency (non- 2016] SEGREGATION IN CHARTER SCHOOLS 273 profit, university, etc.) and those that are run by HISD but which have no attendance boundary.70 First, we compare charters with no attendance boundaries to all schools within HISD that have an attendance boundary (including magnets with boundaries and “campus charters”). This set of analyses was aimed at understanding the degree to which charters physically located within HISD were serving students that were similar to, or different from, HISD students as a whole (see Figure 2). Second, we compared charters with no attendance boundaries to traditional public schools—schools that are not charters or magnet schools; these are simply schools that serve local neighborhoods. This set of analyses was intended to show the degree to which charters located in certain communities may draw particular students from traditional neighborhood public schools (see Table 5). In our third set of analyses, we compare charters to magnet schools operated by HISD. The goal of these analyses, as noted earlier, is to compare district-run schools of choice (magnet schools with no attendance boundaries) with charters in terms of the population served. This set of analyses compares two types of schools of choice that could be potentially serving fewer high-need students. For example, magnet schools can set admissions criteria (though they do provide transportation), while charters may or may not provide transportation and can require parents and students to commit to codes of conduct and various other policies that may limit equity and access. This analysis is aimed at understanding how within- district choice compares to out-of-district choice (see Table 5). 70. We felt that we would combine both types of charters, as we did not believe there was a justifiable reason to distinguish between the types of charter “providers.” In other words, we felt that distinguishing between HISD as a provider and other non-profits was arbitrary. 274 STANFORD LAW & POLICY REVIEW [Vol. 27:251 FIGURE 2: Levels of Segregation: Comparing Open Enrollment Charter Schools to HISD Affiliated Schools, Traditional Public Schools (TPS), and Magnet Schools Within One-Mile Radius (AEIS 2011-2012)71 80 Number of Open Enrollment Charters 70 60 50 40 Reverse Segregative 30 Segregative Not Segregative 20 10 0 HISD TPS HISD TPS HISD TPS Magnet Magnet Magnet English Language Economically Special Education Learners Disadvantaged 71 Within the one-mile radius surrounding charter schools, we found differing configurations of all Houston ISD affiliated schools (HISD), traditional public schools (TPS), and magnet schools. Some charters did not have TPS or magnet schools within their one- mile radius leading to different sample sizes when comparing HISD, TPS, and magnet schools on segregation by English Language Learners, Economically Disadvantaged, and Special Education populations. Levels of segregation are as follows: not segregative (±10% difference, ± 6% difference for SPED), segregative (-10% to -19% difference, -6% to -9% difference for SPED), extreme segregative (-20% difference or greater, -10% or greater for SPED), reverse segregative (10% to 19% difference, 6% to 9% difference for SPED), extreme reverse segregative (20% difference or greater, 10% or greater for SPED). TEX. EDUC. AGENCY, supra note 58. 2016] SEGREGATION IN CHARTER SCHOOLS 275 TABLE 5: Levels of Segregation: Comparing Open Enrollment Charter Schools to all Houston ISD Affiliated Schools, Traditional Public Schools (TPS), and Magnet Schools Within One-Mile Radius (AEIS 2011-2012)72 English Language Economically Special Education Learners Disadvantaged Magnet Magnet Magnet Comparison HISD HISD HISD School Type TPS TPS TPS Total of Charters 73 51 65 73 51 65 73 51 65 for Comparison Not Segregative (less than 42.5 27.5 49.2 65.8 72.5 58.5 63.0 70.6 52.3 ±10% difference, (31) (14) (32) (48) (37) (38) (46) (36) (34) ±6% for Levels of Segregation SPED) Segregative (greater than -10% 39.7 56.9 29.2 13.7 25.5 10.8 31.5 27.5 42.0 difference, (29) (29) (19) (10) (13) (7) (23) (14) (27) -6% difference for SPED) Reverse Segregative (greater than 17.8 15.7 21.5 20.5 2.0 30.8 5.5 2.0 6.2 10% difference, 6% (13) (8) (14) (15) (1) (20) (4) (1) (4) difference for SPED) We integrate and present our findings for each of the three analyses with respect to the three sub-groups of interest (ELL students, Economically Disadvantaged students, and Special Education students) below. We then conclude by examining the access and enrollment of high-need students in several popular “exemplar” charters relative to non-charter public schools that are nearby. Our local analyses find that charter schools are, as a whole, serving significantly fewer ELL students compared with nearby schools in each category of comparison (compared to all schools, traditional public schools, and magnet schools). The most significant differences emerge when comparing charters to nearby traditional public schools: more than half of the charters we analyzed (56.9%, or twenty-nine schools) fall into a “segregative” category (serving at least 10% fewer ELL students than nearby traditional public schools.) Of these twenty-nine schools, twenty-three are in the “Extreme” category, meaning that they serve at least 20% fewer ELL students than the 72. See TEX. EDUC. AGENCY, supra note 58. 276 STANFORD LAW & POLICY REVIEW [Vol. 27:251 nearby traditional public schools. The pattern of segregation for ELL students is still present, but less severe, when comparing charters to HISD schools as a whole (as opposed to the nearby public schools)—which illustrates some of the problems with prior analyses comparing charters only to statewide and individual district averages. Comparing charters to HISD magnets, we find relatively fewer differences. This is a somewhat expected pattern, given that both types of schools, as schools of choice, have some barriers to enrollment. Our comparisons of the proportions of Economically Disadvantaged students in charters find similar patterns of under-enrollment, though the depth of this under-enrollment is more dependent upon the comparison group. As with ELL students, we find problems of under-enrollment emerging most strongly when we compare charters to traditional public schools that are nearby; one fourth of the charters we analyzed (25.5%) we found to be “segregative,” under enrolling Economically Disadvantaged students by at least 10% compared to nearby public schools. When compared with magnet schools, charters are doing relatively better in terms of serving Economically Disadvantaged students, however: on balance charters are enrolling more Economically Disadvantaged students than close-by magnet schools in HISD. Comparing charters to nearby schools yields a very clear portrait under- enrollment of Special Education students, in each category of comparison (Houston aggregate, nearby traditional public schools, and magnet schools). The under-enrollment problem, however, is most severe when comparing charters to magnet schools: 42% of charters within a one-mile of an HISD magnet are under-enrolling students eligible for Special Education services, and nearly half of these levels are “extreme.” 3. Exemplar Schools Analysis To illustrate a final level of granularity, we picked several popular “exemplar” charter schools, to illustrate some of the trends within our spatial data (see Table 6). A number of schools in the Texas data, per the prior national studies of charters, appear to be “not segregative” when compared to overall district demographic averages, but when compared spatially to local schools, they demonstrated disparities as they under-enrolled special student population groups. 2016] SEGREGATION IN CHARTER SCHOOLS 277 TABLE 6: Exemplar Open Enrollment Charter Schools Difference in Enrollment Compared to Schools Within One-Mile Radius (AEIS 2011-2012)73 Traditional Public Houston ISD Schools Magnet Schools Schools Charter Econ. Econ Econ Schools ELL SPED ELL SPED ELL SPED Disadv. Disadv. Disadv. Harmony School of -9.9% -20.7% -8.4% -26.5% -38.6% -8.1% -1.9% -11.9% -8.5% Fine Arts (N=6) KIPP 3rd Ward/ KIPP Liberation -26.8% -6.3% -3.4% -36.2% -9.5% -2.9% -12.9% -1.6% -4.1% College Prep (N=6) Raul Yzaguirre School for 8.0% 8.3% 1.5% -8.2% 2.9% 2.4% 14.3% 10.5% 1.1% Success (K-12) (N=7) Victory Prep -26.6% -32.6% -1.7% -45.7% -36.8% 2.4% -14.0% -29.8% -4.4% (K-12) (N=10) Yes Prep West/ Yes Prep 4.1% 28.1% -3.7% -19.4% 0.4% -6.3% 6.6% 31.1% -3.4% Gulfton (N=4) The Yes Prep West charter campus was illustrative of the demographic disparities between a charter campus and nearby traditional public school. According to the Texas PEIMs data, the school served significantly more Economically Disadvantaged students compared to Houston ISD as a whole; yet, when comparing the school to nearby public schools, the data shows that the school significantly under-enrolls ELL students, and enrolling about the same proportion of Economically Disadvantaged students, vis-à-vis the nearby public schools. Notably, the two charter schools (located on one physical campus) received “Exemplary” accountability ratings in the PEIMS data, compared with nearby traditional schools: Long Middle School with an “Acceptable” rating; and Lee High School with an “Acceptable” rating. 73. With the exception of Harmony School of Fine Arts, exemplars include sites with multiple charters within one campus. 278 STANFORD LAW & POLICY REVIEW [Vol. 27:251 One of our exemplar schools was KIPP Liberation College prep, which we selected given that KIPP is a lauded national corporate charter model. While the school was categorized as “not segregative” for Economically Disadvantaged students— enrolling roughly the same proportion when compared either to Houston averages or nearby traditional public schools—we found that the school was significantly under-enrolling ELL students in both comparisons (by -26.8% and -36.2%, respectively). This school received an “Acceptable” accountability rating in the PEIMS data, which is comparable to nearby traditional public schools (both Acceptable and Recognized ratings.) Some exemplar schools under-enrolled high-need students on each dimension of comparison. For example, Harmony School of Fine Arts under- enrolled Economically Disadvantaged students when compared to Houston averages. This picture was significantly worse when compared to nearby public schools: the school enrolled 26.5% fewer ELL, and 38.6% fewer Economically Disadvantaged students when compared to traditional public schools. Another school in this category was the Victory Prep school, which also under-enrolled ELL and Economically Disadvantaged students vis-à-vis district averages; this under-enrollment was significantly worse when the school was compared to nearby traditional public schools. The school received a “Recognized” accountability rating in the PEIMS data, although nearby traditional public schools did as well or better (Hobby Elementary with an “Exemplary” rating; and Shearn Elementary which also received a “Recognized” rating.) We did find some charter schools in the PEIMS data that should be commended based on their access and enrollment of high-need students reflected in the PEIMS demographic data. For example, Raul Yzaguirre charter was not “segregative” for any of the high-need student populations. Not only was the school representative in terms of high-need students relative to nearby traditional public schools, it received an “Acceptable” accountability rating in the PEIMS data. V. DISCUSSION Our analysis, which looked at high-need student enrollment in charter schools relative to non-charter public schools at three unit of analysis (state, district, and local), illustrates that the claims by many charter school providers that they are serving disadvantaged students at comparable rates equal to or greater than public schools is misleading when examined spatially. While aggregate data at the state level indeed show little evidence of inequity, our local analyses illustrated that, when looking spatially at high-need students (ELL, low-income and Special Education students), disparities are readily apparent. Our local-level spatial analyses illustrate these disparities between charter schools and nearby traditional public schools, particularly with ELL students and Special Education students, particularly when compared to nearby public schools (neighborhood schools). These data contradict many claims by charter 2016] SEGREGATION IN CHARTER SCHOOLS 279 advocates that charters are serving comparable concentrations of at-risk youth. Charters are, as our spatial analyses demonstrate, clearly under-enrolling high- need students relative to non-charter public schools nearby. Thus, this article provides an important blueprint for future work in urban areas nationwide to consider whether similar disparities exist when considered spatially. These quantitative findings also suggest that future qualitative works is necessary to understand whether charter schools may be having an adverse impact on traditional public schools. High-need students enrolled in nearby public schools, often in highly disadvantaged contexts, appear to be “left behind” by choice— as charters attract largest proportions of students that are easier to serve. As a result, nearby traditional public schools are left with an even higher concentration of high needs students. This concentration of disadvantage may make it organizationally difficult for such schools to improve, and lead to further disadvantage for the students left in those schools. We found a somewhat more complicated picture when comparing charters to HISD magnet schools. We find charters in some instances are, in many cases, enrolling both lower and higher proportions of ELL students and Economically Disadvantaged students compared with HISD magnets. The opposite is true with respect to Special Education students— charters appear to be significantly under-enrolling Special Education students vis-à-vis HISD magnets. In sum, our analysis of Texas data suggests that understanding the enrollment of high-need students of charters compared to non-charter public schools requires a local-level spatial analysis. Our work is only a snapshot in time, so future research could longitudinally compare the enrollment of high- needs student populations in traditional public schools versus nearby charter schools to understand the dynamics of stratification in the charter system. Future research could also examine the relationship between high-needs student populations exclusion and high-stakes testing and accountability ratings over time, to discern whether charters obtain a ratings advantage by serving less ELL and Special Education students. VI. POLICY IMPLICATIONS The policy implications that logically emerge from the geographic granularity of these data could either be first-order incremental or second-order substantial. On the one hand, a set of first-order changes to educational policy related to charter schools would seek to take what is in place and make incremental adjustments to policy that aim to better regulate public charter schooling. On the other hand, a second-order change would be an approach that is a substantial departure that would purposefully curtail growth that charters have exhibited over the past two decades. A. Second-Order Substantial Approach One example of a second-order change that sought to challenge charters 280 STANFORD LAW & POLICY REVIEW [Vol. 27:251 existentially came through litigation in the state of Washington. In 2015, the Washington Supreme Court found that charters resulted in “the loss of local control and local accountability,” found that charters were not “common” public schools under the Washington Constitution and thus could not be constitutionally funded as such, noting that charters resulted in “the loss of local control and local accountability.”74 In 2012, voters in Washington State approved Initiative 1204 (I-1204), often known as the Charter School Act and codified as RCW 28.A.710. The Act established charters in the State of Washington and authorized up to 40 schools in the State. The Charter School Act purposefully labeled charter schools as “common school[s]” allowing them to receive public tax dollars on a per pupil basis. 75 Further, the Act governed charters under a politically appointed board and established that charters were “exempt from all school district policies . . . all state statutes and rules applicable to school districts” beyond those specifically identified within the Act.76 The Washington Supreme Court ruled in League of Women Voters of Washington v. State that charter schools were not common schools as defined in Article IX, section 2 of the Washington Constitution and voided the Charter School Act.77 The decision upheld and relied upon the 1909 ruling in School District No. 20 v. Bryan, which established that common schools must be under the control of voters and uniform for every child.78 This aspect of the decision upheld the ruling of the lower court. The Washington Supreme Court, however, overturned the lower court ruling that the Act was severable because the Act’s unconstitutional funding source was “so intertwined with the remainder of the Act and so fundamental to the Act’s efficacy” as to render the Act inviable as a whole. The Court explained that I-1204 clearly indicated that charters were “to be funded on the same basis as common schools,” but that such funds are restricted to use for “common schools,” which charters are not. Because the Act unconstitutionally diverted funds from common schools to charters, the court found the Charter School Act unconstitutional in its entirety. The Washington Supreme Court decision also declared that legislatures could not fund charters from the general fund because property taxes, which partly fund common schools, could not be segregated within the general fund. Bringing challenges to charter policy through constitutional litigation presents challenges that are highly context dependent. The variety of state constitutional provisions and language means that an approach that may have legs in one state would be nonsensical in another, particularly given the variations in how each state’s constitutional provisions have been interpreted over the years. Each state’s constitutional provisions have a rich history of 74. League of Women Voters of Wash. v. State, 355 P.3d 1131, 1134 (Wash. 2015). 75. WASH. REV. CODE ANN. § 28A.710.010(5)-(6) (West 2016). 76. WASH. REV. CODE ANN. § 28A.710.040(3) (West 2016). 77. 355 P.3d at 1133. 78. Sch. Dist. No. 20, Spokane Cty. v. Bryan, 99 P. 28, 30 (Wash. 1909). 2016] SEGREGATION IN CHARTER SCHOOLS 281 being interpreted as they relate to the public schooling system in that state, and a variety of innovative litigation strategies directed at school employment, school funding, or the like have likely created a rich and idiosyncratic foundation of doctrine that would need to be evaluated on a case-by-case, state- by-state basis. This is not to say that litigation is not an important tool for achieving desirable and equitable ends, but the approach depends heavily on the specifics of each state’s constitutional doctrine surrounding schools and education. Given the unique nature of courts and their limited ability to fashion a policy-oriented remedy, a strategy advancing any particular policy aim may be better suited for the political branches. B. First-Order Incremental Approaches Given the increasingly accepted role that charters play in the public education landscape, first-order incremental policy changes present a set of approaches to foment accountable charter schools that serve all student populations equitably.79 The data in this paper suggest that claims by charter operators of comparable levels of enrollment of high needs students should be regarded with some suspicion. These findings also indicate that policymakers and the courts should find ways to hold charters accountable for serving high- needs students at the same rates as nearby schools so that charters don’t become an engine of stratification, draining the “easier to serve” students from strained nearby non-charter public schools. To address these challenges, a variety of policy recommendations are already gaining wide-spread acceptance among other scholars looking at the emerging research around charter schools. 1. Enrollment and Retention Just last year, the Annenberg Institute for School Reform at Brown University released a set of recommendations that were the culmination of multiple years of collaborative work and research on charters.80 The Institute recommended that schools engage the public in robust discussions aimed at developing long-term plans for the schools that take demographic factors and changes into account and that charter authorizers require impact studies that consider these factors before approving new charter applications. 81 Beyond planning and transparency, the report specifically addresses enrollment and 79. Personal communication with Cynthia Liu aided in the development of these recommendations. Email from Cynthia Liu, Founder, K12 News Network, to Julian Vazquez Heilig, Professor, Cal. State Univ. Sacramento (March 30, 2016) (on file with author). 80. ANNENBERG INST. FOR SCH. REFORM AT BROWN UNIV., PUBLIC ACCOUNTABILITY FOR CHARTER SCHOOLS: STANDARDS AND POLICY RECOMMENDATIONS FOR EFFECTIVE OVERSIGHT (2014), http://annenberginstitute.org/sites/default/files/CharterAccountabilityStd s.pdf. 81. Id. at 4. 282 STANFORD LAW & POLICY REVIEW [Vol. 27:251 retention procedures employed by charter schools, recommending that policies around enrollment and retention be transparent, detailed, and publicly available.82 In order to hold charter schools accountable on these practices, the Institute suggests public disaggregated data-reporting requirements and enrollment tracking as well as an ombudsman to whom parents can address and challenge enrollment decisions and enrollment-related grievances.83 2. Discipline Disparities Relatedly, and of particular public interest at the moment, the Institute provides recommendations about discipline policies that can ensure greater equity and consistency across sectors. 84 The report notes that the U.S. Department of Education’s Office for Civil Rights (OCR) has taken increased interest in discipline disparities between the sectors.85 In one of OCR’s “Dear Colleague” letters, the Office reminded charter schools in particular that they are subject to the same nondiscrimination laws as traditional public schools.86 In particular, the letter reminds charter schools of their duty to comply with Title VI of the Civil Rights Act of 1964, prohibiting discrimination on the basis of race, color, or national origin, Title IX of the Education Amendments of 1972, prohibiting discrimination on the basis of sex, and Section 504 of the Rehabilitation Act of 1973 and Title II of the Americans with Disabilities Act of 1990, which both prohibit discrimination based on disability, and refer specifically to schools’ obligations to comply with these laws in their discipline policies and practices.87 Policy proposals around student discipline have been gaining traction lately and are particularly attractive policy levers because they have a real potential for success in state legislatures across the country. More importantly these proposals have the potential to prevent the increases in segregation that may accompany charter sector growth by imposing limits and transparency requirements on student discipline, particularly in-school and out-of-school suspension, expulsion, or unnecessary referral to disciplinary alternative education program. A growing body of research shows that vulnerable populations are disproportionately impacted by these discipline policies. For example, a recent study from the University of Pennsylvania’s Center for the Study of Race and Equity in Education shows that Southern states, Texas included, suspend and 82. Id. at 8. 83. Id. 84. Id. 85. Id. at 7. 86. Letter from Catherine E. Lhamon, Assistant Sec’y for Civil Rights, U.S. Dep’t of Educ. Office for Civil Rights, (May 14, 2014), http://www2.ed.gov/about/offices/list/ocr/lett ers/colleague-201405-charter.pdf. 87. Id. at 2, 6. 2016] SEGREGATION IN CHARTER SCHOOLS 283 expel black students at significantly higher rates than their peers.88 This finding is consistent with research elsewhere, which shows similar disparities for other populations, including Latino students, students who are homeless or in foster care, English language learners, and students who require special services.89 Research suggests that at least some charter schools employ these discipline methods at much higher rates than traditional public schools.90 Due largely to current gaps in data and large differences between how charter schools operate, considerable debate remains as to whether charter schools are particularly bad actors with regard to disparities in student discipline. While the reality undoubtedly varies depending upon the operator and the context, where these discipline methods are overemployed by charter schools, they may contribute to segregation between the charter and traditional public sector schools by pushing vulnerable student populations out of the charter sector. Requiring consistent, transparent discipline policies in charter schools will help stem the flow of students into the school-to-prison pipeline and ensure compliance with federal law. It may also have the collateral effect of reducing segregative effects of the sort seen in Houston. To this end, the Annenberg Institute recommends that charter authorizers require operators to promulgate and implement clear policies on student 88. EDWARD J. SMITH & SHAUN R. HARPER, UNIV. OF PA., CTR. FOR THE STUDY OF RACE AND EQUITY IN EDUC., DISPROPORTIONATE IMPACT OF K-12 SCHOOL SUSPENSION AND EXPULSION ON BLACK STUDENTS IN SOUTHERN STATES (2015), http://www.gse.upenn.edu/eq uity/sites/gse.upenn.edu.equity/files/publications/Smith_Harper_Report.pdf. 89. See, e.g., KIMBERLÉ WILLIAMS CRENSHAW ET AL., AFRICAN AM. POL’Y FORUM & CTR. FOR INTERSECTIONALITY AND SOC. POL’Y STUDIES, BLACK GIRLS MATTER: PUSHED OUT, OVERPOLICED, AND UNDERPROTECTED (2015), http://www.atlanticphilanthropies.org/app/upl oads/2015/09/BlackGirlsMatter_Report.pdf (black female students); U.S. DEP’T OF EDUC. OFFICE FOR CIVIL RIGHTS, CIVIL RIGHTS DATA COLLECTION: DATA SNAPSHOT: EARLY CHILDHOOD EDUCATION (2014), https://www2.ed.gov/about/offices/list/ocr/docs/crdc-early- learning-snapshot.pdf (black students and Native Hawaiian or Pacific Islander females in preschool); DEBORAH F. FOWLER ET AL., TEX. APPLESEED, TEXAS’ SCHOOL-TO-PRISON PIPELINE: DROPOUT TO INCARCERATION (2007), http://www.njjn.org/uploads/digital- library/Texas-School-Prison-Pipeline_Dropout-to-Incarceration_Texas-Appleseed_Oct2007. pdf (black, Latino, and special education students in Texas); OFFICE OF THE STATE SUPERINTENDENT OF EDUC., REDUCING OUT-OF-SCHOOL SUSPENSIONS AND EXPULSIONS IN DISTRICT OF COLUMBIA PUBLIC AND PUBLIC CHARTER SCHOOLS (2014), http://osse.dc.gov/sit es/default/files/dc/sites/osse/publication/attachments/OSSE_REPORT_DISCIPLINARY_G_ PAGES.pdf (black students, Latino students, homeless and foster youths, and students with disabilities in the District of Columbia). 90. DC LAWERS FOR YOUTH, EVERY STUDENT EVERY DAY COAL., DISTRICT DISCIPLINE: THE OVERUSE OF SCHOOL SUSPENSION AND EXPULSION IN THE DISTRICT OF COLUMBIA (2014), http://d3n8a8pro7vhmx.cloudfront.net/dcly/pages/64/attachments/original/1371689930/Distr ict_Discipline_Report.pdf?1371689930 (noting high rates of discipline by charter schools in the District of Columbia); Jaclyn Zubrzycki et al., Charter Schools’ Discipline Policies Face Scrutiny, EDUC. WEEK (Feb. 20, 2013), http://www.edweek.org/ew/articles/2013/02/20/21ch arters_ep.h32.html; Discipline Data: Charters vs. Noncharters, EDUC. WEEK, http://www.ed week.org/ew/section/infographics/charter-discipline-infographic.html (last visited Aug. 7, 2016). 284 STANFORD LAW & POLICY REVIEW [Vol. 27:251 discipline that comply with federal laws, publish those policies and provide students with due process protections and parental appeals before extreme disciplinary measures are imposed, and adhere to reporting requirements that break down discipline by subgroup in order to ensure transparency.91 3. Local Control To ensure that all schools in the community have the proper local control in which students can thrive, states could pass a suite of bills that emphasize local accountability. Legislation could be designed to repeal the portions of charter school acts that writ-large gave away local control and local accountability by exempting charter schools from the vast majority of the education codes in any particular state. Many of these codes, some of which date from the 1990s when very little was known about charter schools in the research literature, should now be updated based on the empirical literature and close various loopholes that have allowed charters to function in education “markets” in ways that are more segregative and discriminatory towards special populations than traditional public schools. 92 For example, laws could be enacted where they don’t currently exist that require all schools that receive public funding to be subject to public records requests and publicly elected boards with public meetings. Parents in the community from diverse backgrounds must also feel that their students have access and are safe in the school. States should provide funding for charter school monitors that ensure charters comply with building safety codes (i.e., earthquake and current lead/asbestos), provide school lunch, abide by the American Disability Act (ADA) and the Individuals with Disability Act (IDEA), and remain open to collective bargaining and employment agreements to ensure that classes are staffed with credentialed teachers and to limit excessive teacher turnover. Locally-based policy solutions can also hold charters accountable to data derived from GIS analyses. While charter proponents may prefer to discuss average demographics of charter schools, policymakers should look beyond state demographics and discern whether charter schools are serving local communities equitably—if they don’t do so, then codified consequences would result. One potential way to do this is to transition a charter into an in-district charter or all-school magnet or community school if the school neglects special populations or selectively enrolls less expensive subsets. This process could be triggered by parents in the schools, just as charter advocates have sought to use trigger laws to turn public schools into charters. The state or county would be required to hold a series of town halls, collaborative proposal development meetings, and community votes to ascertain the needs of the existing school 91. ANNENBERG INST. FOR SCH. REFORM AT BROWN UNIV., supra note 80, at 9. 92. Julian Vasquez Heilig, Charters and Access: Here is Evidence, CLOAKING INEQUITY (Nov. 20, 2015), http://cloakinginequity.com/2015/11/20/drinking-charter-kool-aid-here-is- evidence/. 2016] SEGREGATION IN CHARTER SCHOOLS 285 community and to project what the future needs and unique resources required or offered by the school and district.93 Such a transition could also be initiated by a publicly-elected charter authorization board exercising its authority in a meaningful way that promotes equity between and amongst charters and traditional public schools. Former charter schools would receive access to district facilities only if they agree to return to the district and abide by all employment, curricular requirements, and other regulations to ensure equity and access to a high quality education for all students in the community. CONCLUSION Charters have a choice whether they want to be racially and economically diverse schools that serve ELL, Special Education and low-SES kids. Based on the various admissions and management policies documented in the research literature,94 charters can currently choose their students, rather than families choosing their schools— in essence, school choice has evolved to mean that charter schools, and not families, choose. To address this issue, policymakers and communities must have extensive background knowledge and data to understand the charter conundrum. These groups must also exhibit the political will power to hold charters accountable despite entrenched support from the charter lobby, foundations, wealthy philanthropists and other proponents. It is still an open question whether charters will be beacons of opportunity or harbingers of another century of racial and economic segregation. But we hope this Article points the way forward to opportunity. 93. Julian Vasquez Heilig, The Gem on the Hill: Ho.w to Create a Community-Based In-District Charter, CLOAKING INEQUITY (Aug. 20, 2014), http://cloakinginequity.com/2014 /08/20/the-gem-on-the-hill-austin-creates-a-community-based-in-district-charter/. 94. Heilig, supra note 93. 286 STANFORD LAW & POLICY REVIEW [Vol. 27:251 APPENDIX A: CHARTER SCHOOLS EXCLUDED FROM ANALYSIS DUE TO UNIQUE POPULATIONS 1. University of Texas-University Charter School: Helping Hand Home for Children: Charter run by the University of Texas serving as a foster care facility for emotionally disturbed children in K-5. (www.utexas.edu/ce/ucs/our-campuses/detail/helping-hand-home/) 2. University of Texas-University Charter School: Texas Neurorehabilitation Center: The charter, housed on the Texas NeuroRehab site, is specifically for children 8-17 whose IQs fall roughly between 40 and 90. The school focuses on pre-vocational training of its students. (www.texasneurorehab.com/behavioral- services/residential-neurobehavioral/education/education.stml) 3. University of Texas- University Charter School: The Oaks Treatment Center is a school, in partnership with The Oaks Psychiatric Residential Treatment Center, that caters to students with severe emotional, behavioral and developmental issues. The charter school aspect of this treatment center was discontinued after the 2008-2009 School year. (www.caring4youth.org/1025.html) 4. University of Texas- University Charter School: Settlement Home. This is a residential treatment center for female students between the ages of 7 and 18. There is a major focus on 24-hour therapy for each of its students (www.utexas.edu/ce/ucs/our-campuses/detail/settlement- home/). 5. University of Texas-University Charter School: George M. Kozmetsky Serving families residing at the Kozmetsky Shelter. A confidential shelter for families of sexual and domestic violence. (www.utexas.edu/ce/ucs/our-campuses/detail/kozmetsky/) 6. University of Texas-National Elite Gymnastics Charter School: Program for students who are participating at the elite level in competitive gymnastics. (http://www.utexas.edu/ce/ucs/our- campuses/detail/national-elite-gymnastics/) 2016] SEGREGATION IN CHARTER SCHOOLS 287 APPENDIX B: DEFINITIONS95 “Limited English Proficient” (LEP): These are students identified as limited English proficient by the Language Proficiency Assessment Committee (LPAC) according to criteria established in the Texas Administrative Code. Not all students identified as LEP receive bilingual or English as a second language instruction, although most do. In the Profile section of the reports, the percent of LEP students is calculated by dividing the number of LEP students by the total number of students in the school or district. “Special Education”: This refers to the population served by programs for students with disabilities. Assessment decisions for students in Special Education programs are made by their Admission, Review, and Dismissal (ARD) committee. “Economically Disadvantaged”: The percent of Economically Disadvantaged students is calculated as the sum of the students coded as eligible for free or reduced-price lunch or eligible for other public assistance. divided by the total number of students. 95. TEX. EDUC. AGENCY, Glossary for the Academic Excellence Indicator System 2010- 2011 (2011). 288 STANFORD LAW & POLICY REVIEW [Vol. 27:251 APPENDIX C: HISD AREA SCHOOLS BY CLASSIFICATION TYPE HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus Academy of Davy Briarmeadow A.A. Milne El.* Askew El (Vanguard) Accelerated Crockett El.* Charter Learning Challenge Early Accelerated Highland Alcott El.* Attucks MS (STEM)* College High Interdisciplinar Heights El. School y Academy Dominion Amigos Por Mabel Almeda El. Austin HS (Teaching Pro)* Academy Vida- Friends Wesley El. Charter School for Life East Early Baker-Ripley Anderson El.* Bell El. (Physical Dev.)* Osborne El.* College High Charter School School Beatrice Mayes Rufus Cage Eastwood Ashford El. Bellaire HS (World Lang.)* Institute El.* Academy Charter School Sidney Brazos School Empowerment Lanier for Inquiry and Atherton El.* Berry El. (Environment) College Prep. Middle Creativity (SW High School School Campus) Brazos School Energized for for Inquiry and Barrick El. Black MS (Vanguard)* Excellence Creativity Academy Gano (NW Campus) Diversity Energized for Roots and Excellence Bastian El.* Bruce El. (Music)* Wings Early (DRAW) Childhood Academy Energized for DRAW STEM Academy Early Benavidez El.* Burbank El. (Fine Arts) Academy INC Learning High School Center Energized for George I. STEM Benbrook El.* Burbank MS (Vanguard) Sanchez High Academy INC School Middle School Girls and Boys Hope Academy Blackshear El.* Burrus El. (Fine Arts) Prep Academy Charter School Elementary Houston Girls and Boys Academy for Bonham El. Carnegie HS (Vanguard) Prep Academy International High School Studies Inspired for Girls and Boys Bonner El. Carrillo El. (Vanguard)* Excellence Prep Academy Academy West Middle Chavez HS (Environment International Harbach- Braeburn El.* Science)* High School at Ripley Charter 2016] SEGREGATION IN CHARTER SCHOOLS 289 HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus Sharpstown School Harmony Kaleidoscope/ School of Fine Briargrove El.* Clifton MS (STEM)* Caleidoscopio Arts and Technology Harmony Kandy Stripe Briscoe El.* Codwell El. (Fine Arts) School of Academy Ingenuity Harmony Corneluis El. (Math and Liberty High Brookline El.* Science Science) School Academy Harmony Mount Carmel Science Browning El. Crespo El. (Fine Artsz)* Academy Academy Houston Davis HS (Media, North Houston Houston CAN Burnet El.* Culinary Arts, Early College Academy Restaurants and Hotels)* High School Charter School Houston Pro-Vision Bush El. Deady MS (Comm. Arts)* Gateway School Academy Houston Project Gateway DeBakey HSHP (Health Condit El.* Chrysalis Academy Professions) Middle (Coral Campus) Houston REACH Coop El. DeZavala El. (Vanguard) Heights Charter Charter School Houston TSU Charter Heights Cullen MS* Dodson El. (Montessori)* Lab School Learning Academy INC Cunningham Vision Joshua's Dowling MS (Fine Arts)* El.* Academy Learning Land Durham El. (Leadership Juan B Galaviz Davila El.* Young Learners Dev.) Charter Young Scholars Elrod El. (Emerging KIPP 3D De Chaumes El. Academy for Medical Scholars)* Academy Excellence Felix Cook Jr. El. (Fine KIPP 3rd Ward DeAnda El. Arts) School KIPP Academy Dogan El.* Fleming MS (Fine Arts)* Middle Fondren Middle (IB KIPP East End Durkee El. Campus)* (Explore) Furr HS (Tech & Fine KIPP Houston E.O. Smith El.* Arts)* High School Garden Oaks School KIPP Intrepid Edison MS* (Montessori) Preparatory Garden Villas El. (Fine KIPP Eliot El. Arts)* Liberation 290 STANFORD LAW & POLICY REVIEW [Vol. 27:251 HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus College Prep. KIPP North Emerson El.* Grady MS (IB Campus)* East Lower School Dream KIPP Gregory-Lincoln Center Farias ECC Sharpstown (Fine Arts, 6-8)* College Prep. Gregory-Lincoln Center KIPP Spirit Field El. (Fine Arts, EE-5)* College Prep. KIPP Foerster El.* Hamilton MS (Vanguard) Sunnyside High School KIPP Hartman MS (Medical & Fondren El.* Sunnyside Health Sci.)* School Koinonia Community Fonville MS* Harvard El. (STEM)* Learning Academy Leader's Foster El.* Helms El. (Dual Language) Academy Medical Center Franklin El. Henry MS (Fine Arts) Charter School Southwest MeyerPark Frost El. Herod El. (Vanguard)* Elementary NCI Charter Herrera El. (Integrated Gallegos El.* School without Tech.) Walls Northwest High School for Law Preparatory Garcia El. Enforcement and Criminal Campus Justice (Wileyvale Campus) Raul Yzaguirre School for Golfcrest El. Hogg MS (STEM) Success Elementary Raul Yzaguirre School for Gregg El.* Holland MS (Vanguard) Success High School Raul Yzaguirre School for Grissom El. Horn El. (Academy) Success Middle Ripley House Gross El.* Jackson MS (Vanguard)* Charter School Ripley House Johnston MS (Performing Halpin ECC Middle Arts)* Campus Harris JR El.* Jones HS (STEM)* Ser-Ninos 2016] SEGREGATION IN CHARTER SCHOOLS 291 HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus Charter Academy Elementary Ser-Ninos Harris RP El.* Jordan HS (Careers) Charter Academy II Ser-Ninos Kashmere HS (Music & Charter Hartsfield El.* Fine Arts) Academy Middle Henderson JP Key MS (Math & Foreign Southwest El.* Lang.)* Elementary Henderson N Q Southwest Kolter El. (Foreign Lang.)* El.* High School Hines Caldwell Lamar HS (Business Southwest El.* Administration)* Middle Southwest Lanier Charter Middle Schools Hobby El.* (Vanguard) Mangum Elementary Houston Gardens El./ Lantrip El. (Environment, Texas Serenity Ernest Science)* Academy McGowan El. The Varnett Isaacs El. Law El. (STEM) Charter School Lee HS (Modern The Varnett Janowski El. Humanities)* School East University of Houston Jefferson El. Lockhart El. (STEM)* Charter School Tech Kashmere Victory Prep Longfellow El. (Fine Arts)* Gardens El. Elementary Victory Prep Kelso El.* Lovett El. (Fine Arts)* High School MacGregor El. (Music & Village at Kennedy El. Sciences) South Park Madison HS (Meteorology WALIPP-TSU Ketelsen El. and Space Science)* Prep. Academy YES Prep Lewis El. Mark Twain El. (Literature) Brays-Oaks YES Prep East Looscan El.* Marshall MS (Fine Arts)* End Campus YES Prep Love El.* MC Williams MS (STEM)* Gulfton YES Prep Long MS* Milby HS (Science Inst.)* South West Campus Lyons El. Oak Forest El. (Vanguard) Yes Prep West Zoe Learning Mading El.* Parker El. (Music)* Academy 292 STANFORD LAW & POLICY REVIEW [Vol. 27:251 HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus Martinez C El.* Patterson El. (Literature) Performing & Visual Arts Martinez R El. HS Pershing Middle (Fine McNamara El.* Arts)* McReynolds MS Pin Oak MS (Languages) Pleasantville El. Memorial El. (Vanguard) Mistral Center Poe El. (Fine Arts) Mitchell El. Pugh El. (Science & Tech)* Reagan HS (Computer Montgomery El. Tech.)* Moreno ES. Red El. (STEM)* Neff El. Revere MS (STEM)* Northline El. River Oaks El. (Vanguard) Oates El. Roberts El. (Fine Arts) Ortiz MS* Roosevelt El. (Vanguard) Park Place El.* Ross El. (STEM)* Patrick Henry Ryan MS (Vanguard)* MS* Scarborough HS Peck El. * (Architecture)* School at St. George Place Petersen El. (IB Campus)* Pilgrim Scroggins El. (Fine Arts) Academy* Sharpstown HS Piney Point El.* (Leadership)* Sharpstown International Port Houston El. HS Sinclair El. Ray Daily ES. (Communications)* Reynolds El.* Sterling HS (Aviation)* Robinson El.* Stevenson MS (STEM) Roderick R. T.H. Roger's School Paige El. (Vanguard) The Rice School (Spanish Rodriguez El.* & Tech.) Rucker El. The Rusk School (STEM)* Sam Houston Math Science Travis El. (Vanguard) and Technology Center HS* Sanchez El.* Valley West El. (STEM) Wainwright El. (Math & Seguin El. Science)* Waltrip HS (Research & Shadowbriar El. Tech.)* Shearn El.* Washington BT HS 2016] SEGREGATION IN CHARTER SCHOOLS 293 HISD Affiliated Open Enrollment HISD Charters w/o Attendance Traditional Campus External Magnet School Zones or Public Schools Charters Charters External Campus (Engineering Pro.)* Sherman El* Welch MS (Physical Dev.)* Wesley El. (Math, Science Smith El.* & Tech.) West University El. (Math Southmayd El.* & Science) Stevens El.* Westbury HS (Fine Arts)* Sugar Grove Westside HS (Integrated Academy MS* Tech) Sutton El.* Wharton Dual Language Wheatley HS (Tech Thomas MS* Careers)* Whidby El. (Health Thompson El. * Science)* Tijerina El. Williams MS (STEM) Tinsley El. Wilson School (Montessori) Windsor Village El. Walnut Bend El. (Vanguard)* Worthing HS (Math, West Briar MS Science & Tech.)* Yates HS White El. (Communications)* Whittier El. Young Men's College Prep. Woodson Young Women's College School* Prep. Young El.* Note: HISD Affiliated schools within the one-mile radius of charters for comparison are indicated with an asterisk (*). 294 STANFORD LAW & POLICY REVIEW [Vol. 27:251