STUDENT SUSPENSION IN THE CHANGING SUBURBS: DEMOGRAPHIC TRANSFORMATION AND TRENDS IN EXCLUSIONARY DISCIPLINE IN CALIFORNIA SCHOOLS By Kacy Lynn Martin A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Education Policy—Doctor of Philosophy 2021 ABSTRACT STUDENT SUSPENSION IN THE CHANGING SUBURBS: DEMOGRAPHIC TRANSFORMATION AND TRENDS IN EXCLUSIONARY DISCIPLINE IN CALIFORNIA SCHOOLS By Kacy Lynn Martin Suburban areas in the United States are undergoing a transition from largely White, affluent enclaves to racially and economically diverse communities. Public schools have experienced a resulting shift in the ethnic and cultural backgrounds among students enrolled. Simultaneously, schools nationwide have responded to increasing pressure from community and policy initiatives to address the inequitable impact of exclusionary school discipline on students of color. This study examines the link between the changing racial composition of suburban schools and disciplinary practices that affect racial minorities. The results suggests that Black and Latinx students in suburban elementary, middle, and high schools experienced an increase in the proportion of students suspended relative to their enrollment share over the eight-year study period. Across all samples, the model estimated a strong relationship between increasing proportions of Black and Latinx students and the rise of suspension shares among those student groups. I argue that normative and political factors likely play a role in schools’ responses to demographic change. The results underscore the importance of acknowledging and investigating sources of racial disparities in student outcomes and inform suggestions for future research. Copyright by KACY LYNN MARTIN 2021 To Evan. Poco a poco. iv ACKNOWLEDGEMENTS It is with abundant gratitude that I acknowledge the guidance support that I received throughout this project’s development. My committee has been insightful and challenging in service of shaping this work. David Arsen, Terah Venzant Chambers, Terry Flennaugh, and Bethany Wilinski helped to advance my understanding of gentrification and school discipline. Rebecca Jacobsen, Gary Sykes, Daniel Losen, William Johnston, and Paul Wolbrink also served as invaluable mentors. Mena Alverson and Joni Burns assisted as advocates, and I give appreciation to our childcare provider, Adriana Galvan. My family, including, but not limited to, Ross and Sheryl Vlietstra, and Richard and Christina Martin, provided unending encouragement, and I am thankful for their support during these many years. Without reservation, I thank my husband, Evan Martin for his perseverance and partnership. Finally, I recognize my advisor, John Yun, whose skill as a mentor and commitment to excellence in scholarship enabled the completion of this dissertation. I will be forever grateful. v TABLE OF CONTENTS LIST OF TABLES ....................................................................................................................... viii LIST OF FIGURES ....................................................................................................................... ix CHAPTER 1: Introduction ............................................................................................................. 1 CHAPTER 2: Review of the Literature .......................................................................................... 6 Segregation and Suburban Schools ............................................................................................. 6 Suburban School Types .............................................................................................................. 8 Demographic Change in Suburban Schools ............................................................................. 10 Racial Diversity and School Discipline Practices ..................................................................... 11 Impact of Suspension on Students ............................................................................................ 12 School Discipline and Criminality ............................................................................................ 14 Suburban Educator Responses to School Discipline and Demographic Change ..................... 15 Community and Parent Responses to School Discipline and Demographic Change ............... 17 Policy Efforts to Address Racially Disproportionate Suspension Practices ............................. 18 Federal Policy. ...................................................................................................................... 18 California State Policy. ......................................................................................................... 20 District Policy. ...................................................................................................................... 21 The Limits of Policy ............................................................................................................. 22 Technical, Normative, and Political Responses ........................................................................ 23 Technical Responses. ............................................................................................................ 23 Normative Responses............................................................................................................ 24 Political Responses. .............................................................................................................. 25 Indications of Normative and Political Responses in California .......................................... 28 CHAPTER 3: Methods ................................................................................................................. 32 Rationale for the Present Study................................................................................................. 32 Study Site and Data................................................................................................................... 36 Sample................................................................................................................................... 36 Variables ................................................................................................................................... 42 Outcome Measures................................................................................................................ 44 Predictors. ............................................................................................................................. 44 Controls ................................................................................................................................. 45 Analytic Strategy ...................................................................................................................... 46 CHAPTER 4: Results ................................................................................................................... 50 Descriptive Results ................................................................................................................... 50 Enrollment Trends ................................................................................................................ 50 Suspension Trends ................................................................................................................ 55 Persistently Exclusionary Schools ............................................................................................ 58 Analytic Results ........................................................................................................................ 59 vi CHAPTER 5: Discussion.............................................................................................................. 67 Unexpected Demographic Change in California ...................................................................... 68 School Change and the Mythos of the American Suburb ......................................................... 69 Considering Technical, Normative, and Political Responses to Racial Change and School Discipline .................................................................................................................................. 71 Heterogeneity: Context Matters ................................................................................................ 74 Limitations ................................................................................................................................ 75 Implications for Policy.............................................................................................................. 76 Future Research ........................................................................................................................ 77 APPENDIX ................................................................................................................................... 79 REFERENCES ............................................................................................................................. 87 vii LIST OF TABLES Table 1: Number of California Public Schools by Suburb Type, Grade Level .............................. 9 Table 2: Technical, Normative, and Political Aspects of Demographic Change and School Discipline ...................................................................................................................................... 27 Table 3: Mean Share of Total Teachers and Students by Race .................................................... 35 Table 4: Schools Remaining in Sample by Inclusion Criteria ...................................................... 37 Table 5: Percentage of Students Represented in Samples by Race, Grade Level ........................ 40 Table 6: School Characteristics by Sample .................................................................................. 40 Table 7: Description of Variables ................................................................................................. 43 Table 8: Suburban, Urban, and Total Enrollment by Race, by Year ............................................ 51 Table 9: Number and Percentage of Schools Statewide with Increasing and Decreasing Shares of Students by Sample ....................................................................................................................... 55 Table 10: Percentage of Total Students Suspended by Race, by Time Period ............................. 56 Table 11: Percentage Point Difference Between Share of Students Suspended and Share of Students Enrolled, by Sample ....................................................................................................... 58 Table 12: Summary of Regression Results, by Sample ................................................................ 65 Table 13: Suburban, Urban, and Total Enrollment by Race, by Year .......................................... 80 Table 14: Full Regression Results, Black Elementary School Sample ........................................ 81 Table 15: Full Regression Results, Black Middle School Sample ............................................... 82 Table 16: Full Regression Results, Black High School Sample ................................................... 83 Table 17: Full Regression Results, Latinx Elementary School Sample ....................................... 84 Table 18: Full Regression Results, Latinx Middle School Sample .............................................. 85 Table 19: Full Regression Results, Latinx High School Sample .................................................. 86 viii LIST OF FIGURES Figure 1: Percentage of Schools Statewide with Increasing and Decreasing Shares of Students by Urbanicity, Race ........................................................................................................................... 53 Figure 2: Share of Students Suspended by Sample ...................................................................... 57 Figure 3: Percentage of Persistently Exclusionary Schools by Sample ........................................ 59 ix CHAPTER 1: Introduction The racial and ethnic makeup up of American suburbs has transformed in recent decades (Orfield, 2011). The effects of tensions that arise when suburban communities change have palpable in national culture and media. The most visible evidence of this friction is evidenced by violent behavior among law enforcement officers in altercations with persons of color. However, the challenges of racial integration in traditionally White communities are not limited to these incidents. Suburban schools with historically Traditionally White schools are also environments in which cultural incongruity and racial bias may contribute to inequitable discipline practices (Bonner, 2009) as student populations change. Given the link between school discipline and contact with the criminal justice system (Mowen & Brent, 2016), this study examines race and student suspension in suburban communities as an urgent issue for policymakers and educators. Broader patterns of demographic change in suburbs are particularly evident in American public schools. White students no longer make up the majority of children in suburban districts; 48% of suburban students in the country’s largest metropolitan areas are now White, a drop of nearly 20% since 2007 (Chen et al., 2020). However, suburban schools are likely to be underprepared for demographic change with respect to both policy and cultural competency (Wiley et al. 2018). Regarding matters of policy, schools regularly take on issues of equity and racial integration before housing, social services, and other public institutions set precedent to adjust to the needs of new residents (Frankenberg, E. & Orfield, 2012). With respect to cultural competency, Black and Latinx students are often associated with criminality, however unconsciously, among teachers, administrators, and White parents (Cucchiara & Horvat, 2009). Educators have a higher probability of employing zero-tolerance policies for minor infractions 1 and dispensing exclusionary discipline as the proportion of students of color increases (Hirschfield , 2008). Schools with higher proportions of Black and Latinx students are also more likely to have increased security measures such as metal detectors and law enforcement officers on the premises, and less likely to employ alternative methods of behavior management such as restorative approaches (Wolf & Kupchik, 2017). While suspension rates have largely declined throughout the country, the racial discipline gap persists (Capatosto, 2015). Black and Latinx students are suspended at higher rates than their White peers (Losen & Skiba, 2010). Across the United States, Black students in particular are suspended at a rate of at least twice the proportion of their enrollment (Mendez & Knoff, 2003). These disparities exist after controlling for the type of behavioral offense (Anyon et al., 2014; Bradshaw et al. 2010). Therefore, it is likely that race is a key element in predicting a student’s probability of punishment for behaviors when compared to peers of dissimilar racial background (Skiba et al., 2011). Perhaps attributable to teacher unpreparedness or a cultural adherence to tradition, suburban students of color are especially susceptible to exclusionary discipline as school demographics change (Evans , 2007). Federal recommendations have encouraged states to implement policies to curtail the use of suspension in schools as a primary mode of discipline. Most relevant to this study, policy makers in California have legislated changes to ameliorate racial disparities in school discipline practices relative to other states, and Los Angeles and San Francisco Unified School Districts have banned suspensions for low-level misbehavior entirely (Frey, 2014). However, even as state and district policy efforts to document and address this gap have increased, many school-level, zero-tolerance policies have remained unrevised in suburban California schools (Rafa, 2019). Among other barriers to change, the cultural and political norms in some suburban communities 2 may undermine policy efforts to address racially disproportionate suspension practices in suburban schools (Curran, 2017). The present study therefore examines the changing demographics and the persistent over- suspension of Black and Latinx students in the state of California by estimating the effect of demographic transformation on disciplinary practices in suburban schools through three research questions: RQ1: Is there a relationship between schools with increasing shares of Black and Latinx students and changes in Black and Latinx suspension shares in suburban California schools? RQ2: Is there an interaction between initial shares of Black and Latinx students enrolled and increasing enrollment of these students when predicting differences between Black and Latinx suspension rates in suburban California schools? What is the nature of this interaction? RQ3: Is there a relationship between persistently exclusionary schools and changes in Black and Latinx suspension shares in suburban California schools? Informed by prior research findings on cultural dissonance and political inertia in historically White, suburban schools, RQ1 examines the potential link between increasing shares of students of color and the use of suspension for Black and Latinx students. Where incoming students of color are viewed a threat to student safety or the cultural status quo, teachers and principals may be more likely to employ exclusionary disciplinary practices. Similarly, RQ2 considers whether Black and Latinx students in schools with low initial populations of students of color are more likely to be suspended as their share of the student body increases. If normative and political school characteristics inform educators’ views on student discipline for students of color, it 3 stands to reason that schools with few Black and Latinx at the beginning of the study would be less prepared for racial integration and more likely to use suspension as the primary intervention for conflict. Finally, RQ3 examines the possible relationship between persistently exclusionary schools as a proxy for a culture of zero tolerance. Schools with historically rigid codes of conduct may be less prepared for changing cultural norms among students and therefore use exclusionary discipline practices more liberally. California provides an appropriate site for the investigation of demographic change in suburban schools. The state contains five of the 20 most gentrified cities in the United States, with San Francisco-Oakland ranked first, and San Jose, Sacramento, San Diego, and Los Angeles experiencing similar trends (Richardson & Edlebi, 2020). Gentrification describes patterns of wealthier, often White, residents moving into urban centers, while lower-income residents are displaced (LeGates & Hartman, 2013). Seeking affordable housing while maintaining a proximity to economic opportunities in cities, displaced families often relocate to suburban and exurban areas (Cheng, 2003) and enroll their children in local public schools (Keels et al., 2013). California is also the most populous state in the country, as well as the most racially diverse (Johnson et al., 2021). While the central cities in the state are increasingly inhabited by White residents, the proportion of Lanitx and Asian residents has grown statewide every year since 1970 (Johnson et al., 2021). Simultaneously, population growth in California has slowed in recent years for the first time in the state’s history. Partially attributable to rising housing costs, lower birth rates, and fewer domestic migrants, the rate of population growth has demonstrated a slight decline as of 2020. Public school enrollment in public schools has declined even more rapidly than the general population. This mix of demographic and economic characteristics 4 suggests a complex and varied state, an examination of which might provide insight into parallel trends in other parts of the country. A discussion of the impact of suspensions on students and a summary of current research about suburban demographic change will provide context for the study. A review of the current literature on school responses to demographic change will be followed by an orientation to the theoretical framework used to form the study’s central questions. Finally, I describe the data, detail the operationalization of the variables, and explain considerations for the models and analytic strategy. 5 CHAPTER 2: Review of the Literature Segregation and Suburban Schools Following the Brown v. Board of Education decision in 1955, a mass exodus of White families from central cities to surrounding suburbs resulted in the racial isolation of Black students on a national scale in the 1960’s and 70’s (Goldring & Hausman, 1999). White, middle- class families in all areas of the country demonstrated unwillingness to participate in federally mandated integration programs by moving to physically separate spaces from their Black counterparts (Wells et al., 2005). The development and growth of the suburbs in the mid- twentieth century was therefore born out of the intentional separation of White students from students of color, which resulted in the consolidation of social and economic capital and the hoarding of opportunities afforded to students in suburban schools (Rury & Saatcioglu, 2011). Today, there remain few vocal proponents of racial segregation in schools, yet the phenomenon continues (Frankenberg & Jacobsen, 2011). Central to this pattern is the widespread return of middle- and upper-middle class White residents to central cities in recent years (Ehrenhalt, 2012). Among the findings about this demographic shift is White parents’ stated desire for racial diversity among their children’s classmates (Goldring & Hausman, 1999; Posey- Maddox, 2014). Paradoxically, parents who list diversity among their top priorities in choosing a school have demonstrated a preference for schools that serve a majority of children like their own (Billingham & Hunt, 2016; Posey-Maddox, 2014). A racially diverse school is therefore considered desirable among White parents when a critical mass of other White, middle-class families have chosen the same school (Posey-Maddox, Kimelberg, & Cucchiara, 2014). There is a tipping point at which White, middle-class families no longer hold the dominant culture within a school and thus no longer find it preferable among many options (Reay et al., 2007). 6 Parents’ endorsement of racially diverse schools is divergent from the anti-integration opinions voiced in previous generations. Upon closer examination, however, there are parallels between the ideas underlying the rhetoric of the 60’s and 70’s and the euphemistic language used in discussions about racial diversity in schools today. Previous studies have documented White parents’ desire to expose their children to diverse classmates, but only if those classmates conform to their expectations of safe and appropriate behavior (Cucchiara & Horvat, 2009). “Parents’ fears about the school’s racial composition [are] intertwined with concerns about student behavior. To many parents, the presence of large numbers of African American students and what they saw as these students’ unruly behavior was disconcerting, calling up racialized narratives of schools with large shares of students of color as dangerous places” (Cucchiara, 2013, p. 11). Racial biases and associated fears manifest themselves not only in statements about school safety, but also in discussions of student achievement. According to Cucchiara (2013), “These concerns [persist] even in the face of evidence of academic success, suggesting that [a school’s] location and racial composition serve as important signals about school quality and safety” (p. 9). When choosing public schools, middle-class, White parents report prioritizing a perception of safety and an assurance of high average student achievement. Posey-Maddox (2014) argues that taken together, these attributes serve as reassurance to White parents that they have made an acceptable decision by remaining enrolled in a racially diverse school. As demographics change in urban and suburban schools, parents with mobility and resources are free to weigh these factors to make active choices about their children’s schools. In areas with declining overall enrollment, schools must retain students to maintain funding, and the presence of White students is a social signal of a schools’ desirability (Kimelberg & Billingham, 7 2013). While no longer explicitly exclusive, suburban schools remain segregated. In recent decades, the rollback of federal pressure to desegregate schools has contributed to levels of segregation comparable to those of the pre-Brown era (Clotfelter et al., 2020). Where ethnic diversity in schools does occur within residential areas, many White families have found other means of separating their children from students of color. As Henig (1994) notes, “States and school districts turned to freedom of choice and voucher plans as a way of avoiding the implications of Brown v. Board of Education, forging in many Americans’ minds a permanent link between educational choice and racial bigotry” (p.80). While families who exercise this mobility may not do so out of overt racial prejudice, the aggregate of their individual preferences has created persistent levels of segregation in schools (Bifulco & Ladd, 2007; Duneier, 2016). Because of the incendiary legacy of school desegregation debates in the United States, contemporary politicians and policymakers have made a concerted effort to repackage the topic as apolitical and unworthy of scrutiny (Henig, 1994). Yet, however obscured the legacy of segregation may appear, district leaders and community members who influence school policy and culture do so amid the social structures that resulted from these historical trends (Orfield & Frankenberg, 2012). The language that describes racial dynamics in schools has evolved, but patterns of segregation have remained decidedly similar (Kurlaender & Yun, 2007). Suburban School Types An important caveat to this study is its limitation in defining suburban districts and schools. The data analyzed labels schools based on urbanicity. Schools in areas considered Small Suburbs, Mid-Sized Suburbs, and Large Suburbs were combined to create an indicator for whether a school was considered suburban in this study. The total makeup of suburban school type within California is described in Table 1. 8 Table 1: Number of California Public Schools by Suburb Type, Grade Level Elementary Middle High Suburb Type Schools Schools Schools Total Large Suburb 1,811 333 405 2,549 Mid-Sized Suburb 157 39 45 241 Small Suburb 142 36 31 209 Total 2,110 408 481 2,999 Size of a suburban area does not account for substantial heterogeneity in suburban schools. Frankenberg and colleagues (2012) described a typology for suburban schools that considers the economic and racial makeup of areas that moves beyond the description of suburb size described above. Among the six types of suburbs described are, (1) Exclusive Enclaves, which have high shares of white students, low poverty, and minimal racial change, (2) Countywide Districts, which are large, racially diverse districts with moderate percentages of Black and Latinx students, (3) Stable, Mixed-Income suburbs, which have very little racial change with few minority students, mixed socioeconomic status, and are located far from a central city, (4) Inner-Ring Transitioning suburbs that are experiencing rapid demographic change, are small in size, have moderate percentages of minority students, few White students, and are located close to the central city, (5) Satellite Cities that have experienced moderate change with high percentages of Black and Latinx students, and (6) Developing Immigration Areas, which have slower racial change, are larger in size, and have moderate percentages of Asian, Latinx, and low-income students. Suburban schools are not a monolith (Posey-Maddox, 2020), and should therefore be examined with an awareness of inequity in resources, racial integration and segregation, and socioeconomic variation. Few studies have quantified the disciplinary trends among suburban 9 students of color, with particular respect to the changing colloquial understanding of the meaning of suburbia. While this study does not contain the data required to define schools by the above typology, it is distinct in its analysis of discipline data in suburban schools more broadly. Demographic Change in Suburban Schools With longstanding trends of racial segregation as the backdrop of current residential and enrollment trends, suburban and exurban areas have seen a marked increase in the proportion of racial minorities enrolled in recent decades (Hanlon et al., 2009). For a variety of reasons including urban gentrification and rising housing costs in central cities, an unprecedented proportion of families of color have moved to areas previously inhabited by White residents (Frankenberg & Orfield, 2012). Within the broader demographic transformation of suburban residential areas, a particular examination of this change in schools is warranted for several reasons. First, schools are among the first institutions to experience demographic shifts in suburban communities. District and school leaders must adjust to the changing needs of the families they serve before policy and cultural precedent is established among other public institutions and social services (Orfield, 2002). Second, as relatively autonomous institutions, schools and districts have little oversight regarding how best to approach demographic change with equity as a primary goal. As federal oversight of segregation and integration has receded, schools have entered what Clotfelter (2020) observes as “a new era of federal benign neglect” (p. 29). A thorough consideration of the implications for students of color is therefore warranted to advance accountability among educational institutions. Third, schools are mediators between the social and political forces in broader society and the culture and outcomes for which they are responsible (Holme et al., 2014). 10 Finally, as market-based reforms and school choice policies have proliferated in recent decades, parents with social capital now act as consumers and may choose to opt out of schools with increasing proportions of students of color, therefore perpetuating the issues of segregation and opportunity-hoarding that are unique to schooling (Diamond & Posey-Maddox, 2021). If the implicit objective of most public schools is to educate and provide opportunity for students in an equitable manner, the conditions of structural racism, income inequality, residential segregation, and other contextual factors contribute to their ability or inability to do so. Racial Diversity and School Discipline Practices On average, Black and Latinx students are suspended at proportions that exceed their share of enrollment (Anderson & Ritter, 2016). This has remained the case every year since states began collecting disciplinary data (Morris and Perry, 2016). Racial disparities exist after controlling for the type of behavioral offense, suggesting that compared to their peers (Anyon et al., 2014; Bradshaw, Mitchell, & Leaf, 2010; Fabelo et al., 2011; Roque, 2010; Skiba, et al., 2014). It is therefore likely that race is a key element in predicting the likelihood of exclusionary punishment. The majority of exclusionary discipline is not used to address violent or illegal behavior (Bradshaw et al., 2010). Employed primarily as tools for maintaining perceived order within classrooms, in- and out-of-school suspensions are common consequences for minor infractions such as dress code violations, tardiness, disruptive classroom conduct, and other highly subjective behaviors (Wiley et al, 2018). In California, disciplinary actions that that fall under this category of subjective infractions are called suspensions for “Disruption or Defiance,” or “Willful Defiance.” Limitations on the use of Willful Defiance suspensions have varied by district and grade level statewide. As a result, the likelihood of suspension for minor misbehavior 11 differs by where a student is enrolled. Urban districts in California demonstrated earlier and broader implementation of the restriction on these suspensions than did suburban districts (Reardon et al., 2018). Impact of Suspension on Students Exclusionary discipline practices are widely used as a method of student behavioral intervention in schools (Losen & Skiba, 2010). However, suspension has been repeatedly documented not only as failing to prevent future misbehavior, but also producing negative short- and long-term effects for schools and students (Sharkey & Fenning, 2012). Academic achievement is inversely related to student suspensions (Morris & Perry, 2016). Schools with higher suspension rates have lower standardized tests scores on average than those with fewer proportionate suspensions. While this study examines the unduplicated number of students suspended rather than the average number of days students are suspended, it is worth noting that the relationship between the number of days a student is suspended and a significant inverse relationship between students’ academic progress in both reading and math in a given school year (Noltemeyer et al., 2015). Suspension is also significantly correlated with student dropout (Wolf & Kupchik, 2017). First, time away from the classroom causes students to fall behind with the pace of the curriculum, leading to short-term academic struggle and an increased likelihood of grade retention (Carpenter & Ramirez, 2007). Second, exclusion from the academic environment may contribute to anti-social behaviors and peer relationships outside of school and create an inhospitable or hostile relationship between students and the academic environment upon returning to school (Evans, 2007). A loss of a sense of place and social belonging may increase students’ likelihood of deciding not to return at all (Noltemeyer et al., 2015). 12 In addition to the deleterious impact on academic achievement, suspensions interfere with social and emotional development. Schooling serves not only in the development of skills and knowledge, but also in students’ cooperative engagement with others and a sense of self-efficacy (Labaree, 1997). Suspensions necessarily separate students from their classmates and pro-social extracurricular activities. This exclusion is likely to damage the ties between suspended students and classmates. Likewise, exclusionary punishment often has the effect of labeling students as deviant and aiding in their own self-conception as outsiders in the school community (Evans, 2007). Exclusionary school discipline might also have a labeling effect on disciplined students (Lemert, 1967). Being labeled as deviant through formal punishment creates a number of challenges that lead to further conflict between a student and educators, including heightened monitoring by authority figures, presumptions of involvement in future misbehavior, and fewer pro-social opportunities (Gregory & Fergus, 2017). Not only is this exclusion harmful for students’ social and emotional development, the impact of the estrangement from school social ties increases the likelihood of further misconduct (Chen, 2008). Finally, school suspensions have been linked to adverse experiences in later in life. Students who are habitually suspended from school are more likely to experience mental health challenges such as anxiety and depression in young adulthood (American Academy of Pediatrics, 2003). Moreover, the practice of exclusionary discipline models anti-democratic values and discourages civic and democratic participation throughout their lifetimes (Kupchik & Catlaw, 2015). There are likewise documented links between suspension and drug use, criminal victimization, and incarceration (Wolf & Kupchik, 2016). School suspension, therefore, not only 13 harms the achievement of individual students in a given school year, it is also linked negative lifelong outcomes, and to students’ contact with the criminal justice system (Mowen, 2017). School Discipline and Criminality According to Hirschfield (2008), American schools have increasingly approached the issue of student discipline as synonymous with crime control. This is evident in the physical environment of many schools, particularly public high schools. Metal detectors and full-time law enforcement officers intended to control criminal behavior have become commonplace, and schools with higher shares of Black and Latinx students are more likely to exhibit these characteristics (Irwin, Davidson, & Hall-Sanchez, 2013) However, these staffing and infrastructure decisions tend to be unsuccessful in curtailing unlikely incidents of serious violence, and instead create an environment in which students are monitored and punished frequently and severely for less serious offenses (Johnson et al., 2019). Black and Latinx students are especially affected by the paradigm of crime control in schools. Suburban educators are more likely to identify specific students as threats or troublemakers and dispense exclusionary discipline practices more harshly as the proportion of students of color rises (Chiricos et al., 2001). Prior work has also found that exclusionary and zero-tolerance approaches to school discipline are more prevalent in schools serving larger proportions of students of color, while restorative practices are less likely to be used in these environments (Curran, 2017; Welch & Payne, 2010). Cultural narratives of Black and Brown students as associated with criminality contribute to educators’ subjective decision making about punishment for minor infractions (Diamond & Lewis, 2018). Studies have shown that within some schools, Black and Latinx are targeted disproportionately to receive harsher punishment when compared to their White peers (Barrett, 14 McEachin, Mills, & Valant, 2017). This bias contributes to the close surveillance of students of color (Rios, 2011), and in relatively fewer warnings or probationary periods before patterns of problematic behavior are made clear (Young et al., 2011). According do Riddle and Sinclair (2019), implicit and explicit racial bias explains disparities in discipline policy implementation within schools. Students of color are more readily identified as on a “criminal track” (Hirschfield, 2008), which may exacerbate a student’s self- perception as an outsider in the school community, creating a-self reinforcing process whereby students suspected of criminality more readily participate in misbehavior (Skiba et al., 2011). This cycle may then serve to confirm educators’ previous associations between students of color and criminality. Suburban Educator Responses to School Discipline and Demographic Change Recent studies present evidence that suburban schools with changing populations are often unprepared with respect to both policy and cultural competency (Holme et al., 2014; Wiley et al., 2018). Because of the decentralized nature of educational institutions, school leaders in smaller suburban districts often address the needs of their changing populations without cohesive guidance or precedent on policy matters (Frankenberg & Orfield, 2012). Longtime suburban educators may apply old policies and practices to new students with limited regard for their diverse needs (Welton et al., 2015). Much of the qualitative literature on educators’ responses to suburban educator responses to increasing proportions of minority students demonstrates a culture of fear and punishment. In one study, a teacher summarized the consensus among the staff’s approach to managing the behavior of new students: “If we don’t take control, we’ll lose control” (Evans, 2007, p.335). Likewise, Irby (2018) found that the majority of teachers in a suburban school with growing 15 shares of minority students viewed disrespectful behaviors as a crisis. Teachers reported the belief that school lacked order and the idea that flexible rules were dangerous to students and the learning environment. Teachers described the prospect of moving away from zero-tolerance policies as, “students running the school” (p. 706). These studies provide insight into the normative orientation among suburban educators about school discipline and demonstrate the routine use of exclusionary discipline as a first response to student behavior problems. Oversight of school discipline policy varies widely by locale and across levels of government. Regardless of federal and state policy, district- and school-level decisions are largely left to the discretion of the principal and teachers. Anderson and Ritter (2016) found that a large proportion of the variation across in the racial school discipline gap is between schools rather than within schools, suggesting that school-level leadership is instrumental in setting norms and expectations for behavioral interventions. However, there is considerable variation within schools as well. Thornbuerg (2007) considers teachers “street level bureaucrats” (Lipsky, 1980), with significant power in decision making about the implementation of school discipline practices. When considering a teacher’s own race as compared to newly arrived students, studies have demonstrated an increased likelihood that minority students experience exclusionary discipline in classrooms with White teachers (Lindsay & Hart, 2017). Other research found that schools that adopted Positive Behavioral Interventions and Supports (PBIS) programs reported an overall decrease in incidents of referrals to law enforcement, expulsions, and suspensions. However, the program did not reduce the disproportionate use of these consequences among students of color, suggesting that the primary beneficiaries of the program were White students (Irby, 2018). 16 Whether the primary source variation in school discipline practices is within or between schools, studies have found that uniformity of policy, expectations, and accountability in school discipline policy is essential in reducing rates of exclusionary discipline (Johnson et al., 2019). Community and Parent Responses to School Discipline and Demographic Change Policymakers, school leaders, and teachers are not the only sources of influence over school discipline practices in demographically changing schools. The political environment of the community in which a school is situated also informs educators’ responses to increasing proportions of Black and Latinx students. Curran (2017) argues that parents are influential stakeholders on the issue of school discipline. Participation in parent-teacher organizations, school board elections, and the opportunity to exit the school or district allows parents to exercise power over school responses to increasing numbers of racial minorities. Educators may seek to curtail parents’ impulses to remove their children from their current schools by prioritizing the voice of long-time, often White, parents and residents over the interests of the student body as a whole (Diem et al., 2014). For example, one study documented the success of middle-class White parents in resisting reforms that would have reduced racial segregation (Turner, 2018). While not within the scope of this study, resistance to school integration demonstrates the power of community members and parents to limit changes aimed at racial equity when they depart from their personal interests. Schools are financially incentivized to retain their current pupils and seek to minimize parents’ decisions to transfer elsewhere. In attempting to do so, they may employ strategies to appease White families, such launching marketing campaigns or offering new, prestigious curricula to persuade longtime parents that schools are becoming “positively” diverse (Turner, 2018). This is particularly true in “enclave schools,” which Diem and colleagues (2014) describe 17 as affluent suburbs with traditionally higher proportions of White students and reputations as academically superior relative to other schools in the area. Meanwhile, Black parents in enclave schools reported experiences of racial microaggressions in interactions with educators and fellow parents (Posey, 2017), which suggests a broadly accepted culture of racial bias in such schools. White parents have been found to exert political power over school decisions about discipline, by voicing apprehensions about safety, perceived academic deterioration, or concerns over changing demographic makeup (Curran, 2017). Likewise, the threat of withdrawing their children from enrollment allows White parents the power to advocate for preferential treatment for minor behavioral infractions, and their relative access to economic, social, and cultural capital often results in educators’ compliance with their requests for leniency (Owens & McLanahan, 2020). Black students, in contrast, are more likely to be sanctioned for similar behaviors without successful parent advocacy (Diamond & Lewis, 2018). Policy Efforts to Address Racially Disproportionate Suspension Practices Legislative decisions about education are distributed among many levels of government, which complicates efforts to reform schools. Federal, state, county, district, and school-level laws each exert control over schools with varying degrees of authority and accountability (Curran, 2017). As a result, uniformity in changes to school discipline policy across states and districts is difficult to achieve. This study therefore focuses on California, and the policies and outcomes associated with school discipline specific to that state. Federal Policy. Like all states, California was influenced by guidance that resulted from a collaboration between the U.S. Departments of Justice and Education, which launched the national Supportive School Discipline Initiative (SSDI) in 2011. The SSDI called on states to improve data collection, expand technical assistance, and participate in reform efforts (U.S. 18 Department of Education, 2011). The agencies jointly released a federal guidance document with recommended practices for fostering supportive and equitable school discipline. Following the release of SSDI guidance, the two agencies issued a Dear Colleague letter in 2014 explaining the national and legal significance of the problem of racial disparities in school discipline. The letter made recommendations to educational leaders to revise discipline protocols, invest in professional development to improve classroom management, provide individual behavioral plans rather than using suspension as an initial intervention, and routinely collect and analyze school discipline data with the intention of identifying racial disparities (U.S. Department of Education, 2014). These federal recommendations have had some influence on state and district reforms, many of which have implemented the suggested strategies such as revising conduct codes to prohibit or limit the use of exclusionary practices (Steinberg & Lacoe, 2017). In 2015, Congress passed the reauthorization of the Every Student Succeeds Act (ESSA) which includes several of provisions aimed at reduce disciplinary exclusion and disparities in exclusion. The Every Student Succeeds Act identified school climate as an indicator of student success, required local education agencies to detail how they would reduce the overuse of exclusionary discipline, and provided federal funding for intervention services such as parent engagement, school-based mental health services, and multitiered systems of support (Gregory et al., 2017). Additionally, ESSA required accountability for discipline practices. As of 2015, states and districts are required to submit a yearly, publicly available report card detailing the rates of in-school suspensions, out-of-school suspensions, expulsions, school-related arrests, referrals to law enforcement, chronic absenteeism, and incidences of violence, including bullying and 19 harassment, at the state, district, and school level. Failure to do so results in districts losing eligibility for Title I funding (Aspen Institute, 2018). The Dear Colleague letter communicated the priority given to issues of race and school discipline in federal education agenda and brought awareness to disparities and adverse outcomes. The reauthorization of ESSA provisions on school discipline likewise marked a significant federal policy intervention. However, the Dear Colleague letter was rescinded in 2018 under the Trump administration, indicating the federal government’s shift away from an emphasis on racial inequity and school discipline. While the provisions within ESSA remain intact, the inconsistency of federal guidance on disparities in school discipline indicates the dynamic and perhaps unstable influence that federal policy has on state and district decisions. California State Policy. Induced by the federal guidance to address exclusionary school discipline practices, the California Department of Education took steps to reduce school suspensions and eliminate racial disparities beyond the scope of federal requirements. Community stakeholders and nonprofits spent time and resources advocating for legislative action on school discipline policy (Public Council, 2014). As a result, a 2013 law in California eliminated suspensions and expulsions based on Willful Defiance behaviors in grades K-3 (California Department of Education, 2020). Similar bills aimed at banning suspensions for minor misbehaviors for students in grades 4-8 failed to achieve gubernatorial approval (Wiley et al, 2018). However, other state policy requires accountability for student discipline. Enacted in 2013, California’s school funding procedure, the Local Control Funding Formula (LCFF), determines the amount of funding each school receives based on a variety of factors, including reporting school discipline information. Each school district in California is required to create an annual Local Control Accountability Plan (LCAP) that prioritizes school 20 climate and replaces punitive school discipline practices with Restorative Justice programs or other comprehensive behavior management systems (California Department of Education, 2020). As a result, California is one of a few states that has required the measurement of school discipline a determinate of annual funding (Rumberger & Losen, 2017). The progress made by utilizing additional resources in urban districts have been publicly celebrated (Frey, 2014). However, this change is not necessarily reflected in smaller, suburban districts with minimal public scrutiny, fewer resources, and less experience with racially diverse populations (Kupchik, 2016). District Policy. Los Angeles Unified, San Francisco Unified, and Oakland Unified School Districts have implemented policies specifically aimed at ameliorating racial disparities in school discipline and limiting school suspensions in general. In 2013, Los Angeles Unified School District banned Disruption and Defiance suspensions for all grades, and implemented a variety of counseling and Restorative Justice programs. Perhaps attributable to the increase in support staff and the adoption of alternative approaches to behavior problems, suspensions in the district have steadily decreased across all suspension categories, including fighting, selling drugs and bringing weapons to school (California Department of Education, 2020). Similarly, San Francisco Unified School District has invested in teacher training for restorative practices, positive behavior interventions and supports, and trauma-sensitive approaches to student discipline. The school board approved the use of suspension only as a last resort, such as in cases that involve drug or weapon possession (Frey, 2014). In another example of large urban districts pursuing alternatives to exclusionary discipline, Oakland Unified was an early adopter of a Restorative Justice pilot program in 2005. 21 Over a three-year period, the pilot schools experienced an 87% decrease in school suspensions (Sumner, Silverman, & Frampton, 2010). The pilot expanded to 24 schools in 2014, and the implementation of Restorative Justice programming contributed to a 23% decrease in suspensions and a 53% decline in dropout rates (Gregory et al., 2018). As exemplified by these districts, concerted, collective efforts to reduce suspension and implement alternative methods of behavior management can provide a safer, more successful environment for students. However, given the scope of influence that urban school boards and superintendents exert over large districts, this means of pursing widespread change in policy and practice may not be feasible among smaller, decentralized, suburban districts. Resources to invest in counselling and staff training to improve school climate may not be available to smaller districts. Likewise, a relative lack of political pressure may lead suburban educators to overlook racial disparities in school discipline. Thus, policy change at the federal and state level may not have a uniform impact across all districts in California. The Limits of Policy. Reverence for the status quo among educators and community members may undermine policy efforts to address racial disparities in school discipline. Legally or otherwise mandated approaches to school discipline reform might include interventions such as requirements to decrease the number of reported suspensions or ban suspensions for specific behavior. These rules are determined by federal, state, and district policy. However, the individual decisions of educators, as well as pressure from parents and other outside stakeholders, are significant determinants in the adoption of these policies (Curran, 2017). State and federal agencies may find it difficult to determine the level of fidelity with which a policy has been implemented. Schools and districts may even generate the appearance of improvements in school discipline rates and disparities while continuing the same punitive 22 practices. For example, 18% of charter nationwide were found to systematically underreport suspensions because of their desire to retain enrollment, comparative autonomy, and lack of accountability (Losen et al., 2016). Therefore, policy change is one contributing factor to racial equity in school discipline. Normative beliefs about race discipline, as well as political influence from parents and community members, also significantly contribute to schools’ ability to address underlying issues of privilege and bias in the application of exclusionary discipline practices (Gregory et al., 2017) Technical, Normative, and Political Responses The interplay between policy, norms, and politics with respect to demographic change and school discipline aligns with the theoretical framework that shaped this study’s design. An orientation toward the Technical, Normative, and Political Responses to demographic change in schools (Holme et al., 2014) will inform the formulation of the research questions. Likewise, a consideration of the Technical, Normative, and Political aspects of school discipline practices (Wiley et al., 2018) will support the interpretation of the empirical findings. Technical Responses. The majority of national, state, and local approaches to both demographic change and school discipline policy reform are technical in nature. Technical Responses to demographic change involve creating rules and policies to address the changing needs of a school population. For example, districts and schools have created programs for English Language Learners or implemented tracking systems to place some students remedial learning environments (Oakes et al., 1992). Other technical efforts to address demographic change involve pedagogical training for teachers or the hiring of personnel to work specifically with diverse, newly-arrived students (Holme et al., 2014). As visible and measurable initiatives, technical strategies allow educators to follow specific protocols and engage in accountability for 23 the work of accommodating a changing population of learners. Regarding school discipline, Technical Responses are, likewise, changes in rules or policies. This might involve doubling down on zero-tolerance policies or implementing other methods of managing student behavior such as Positive Behavioral Interventions and Supports (PBIS). Technical Responses also include district, county, or state rules about collecting data on racial disproportionality in school discipline and setting guidelines, incentives, and consequences for schools with persistently high numbers of minority students suspended. Among the three responses to demographic change and student discipline, the evidence of Technical Responses is ubiquitous, perhaps because of their specificity and measurable implementation. However, the Normative Responses and political power involved in demographic change and school discipline have an important influence on schools’ approaches to a changing student population (Holme et al., 2014). Normative Responses. Normative Responses to student demographic refer to the attitudes and hegemonic culture within a school or district. This might include initiatives to shift from deficit-minded approaches toward students of color toward a nuanced view of students’ characteristics and strengths. While sometimes introduced through technical means such as cultural competency training and education on the backgrounds, needs, and capabilities of the new student population, Normative Responses involve changing educators’ entrenched beliefs. The outcomes of Normative Responses are less measurable than adherence to technical approaches, as Normative progress requires that educators’ “core values and beliefs” about students, race, and demographic change transform to meet the needs of a new population (Holme et al, 2014 p.51). Normative Responses to school discipline go beyond recording school suspension data 24 and implementing specific policies. Schools and districts that take on Normative Responses to address inequities in exclusionary discipline might seek to address the source of behavioral problems, create conditions for conflict prevention, or facilitate communication with and among students. They also may attempt to cultivate a sense of responsibility among educators for helping students identify and resolve anti-social decisions (Wiley et al., 2018). Sometimes aided by technical interventions like explicitly restorative approaches to student behavior, positive Normative Responses require a core change in the educators’ assumptions and reactions to student behavioral problems. Qualitative studies have documented the success of schools with concerted and ongoing efforts to critically examine the disproportionate number of students of color suspended and overtly engage teachers in conversations about bias and systemic racism (Diem et al., 2016; Wiley et al., 2018). Because educators may revert to the default use of suspension and expulsion without a collective commitment to racial equity and constructive approaches to conflict resolution, Normative change is a necessary precondition for Technical Responses to effectively address inequities in school discipline (Riehl, 2005). Political Responses. Just as addressing Normative Responses to demographic change and school discipline is necessary to create the lasting implementation of Technical Responses, Political Responses play an important role in school and community adaptation to a changing student body. Political Responses refer to outside forces exerted on schools’ reaction to demographic change. Elite members of the school community are the source of political power in this framework; parents with time and social capital (typically White and/or wealthier members of the community), as well as school board members, members of parent teacher associations, and long-time families whose enrollment schools seek to retain. The political context of parents and the broader community may give educators incentive 25 to use exclusionary discipline practices with minority students as their share of the population of a school grows. For example, White parents are often concerned with school safety as the population of Black and Latinx students increases (Cucchiara, 2013). Long-time parents may have skill with leveraging authority in spaces like the PTA or school board meetings, and expressing fear of violence may successfully exert influence on educators’ decisions to remove students of color more readily as the share of Black and Latinx students grows. Table 2 organizes the central ideals of the theory and describes examples of each of its components as they relate to school responses to demographic change and student discipline. 26 Table 2: Technical, Normative, and Political Aspects of Demographic Change and School Discipline Technical Normative Political Structures Assumptions Stratification Use of time, Values about what More decision-making people, materials is right power among elites Strategies Beliefs Elites Curricular and Ideas about others Board members, PTA, Description pedagogical White parents Knowledge Identity Constraints Specialized Informed by Resistance to changes that professional backgrounds advance the interests of development underserved groups Personnel Entrenched views Obstruction ESL teachers, Human capacities, Redistribution of counselors, social differences, racial resources, attendance workers, data biases boundaries, racial balance analysts in schools Training Opinions Appeasement of elites Demographic Differentiation, Proper school Holding meetings, Change data coaching responses allowing exceptions Examples Reforms New views Disrupt power structure Accountability Difficult All parents’ discipline policy, data Dialogues, concerns weighed equally collection, quotas education on for academic racism and equity achievement Conflict Discipline goals prevention Data use School culture Pressure from elites about Tracking Emphasis on safety and achievement suspensions relationships Increased suspension PBIS, Restorative Belief in efficacy Justice, zero- of suspension tolerance Resource Race and equity Democratizing voices School Reorganization training Discipline Time for Systemic racism Inviting marginalized Examples community with respect to parents to participate building, school discipline additional staff 27 With respect to further sources of political influence, parents and community members may use average standardized test scores as proxies for a school’s reputation as “good” or “bad.” Moreover, nostalgia for a particular level of student achievement is described in the qualitative studies of comparable contexts, and parents’ demands to maintain a reputation as high-achieving may influence responses to demographic change (Evans, 2007). As students from diverse backgrounds enter schools that place extreme importance on student achievement, those who score below their peers on math or reading assessments may cause concern about a decline in the school and district average. There is therefore an incentive to exclude these students from the learning environment as a method of placating long-time residents and community members and demonstrating a commitment to the academic and cultural status-quo (Wiley et al., 2018). Thus, as the proportion of minority students increases, political aspects of educator and community responses, and an absence of meaningful normative change, may drive the application of the zero-tolerance discipline policies. Political forces such as pressure to maintain average test scores or a specific reputation may inhibit a careful response to change. Likewise, normative aspects of adjustment to a changing population, such as broad, cross-cultural competency and buy-in to new ways of understanding student behavior, take time and deliberate effort to implement within districts and schools. As technical standards for behavior remain or become rigid, educators may use suspension readily in order to respond to behaviors that fall under traditional ideas of disruptiveness or out of the bounds of school expectations (Pentek & Eisenberg, 2018). Indications of Normative and Political Responses in California. The California School Staff Survey is administered every year to gather information about teachers’ perceptions on a range of topics, including student discipline, school safety, and racial diversity. The data 28 collected is a representative sample of 40% districts across California and measures staff perceptions of race, equity, and school discipline. Because the sample does not contain school- level for each of the schools in this study, the direct relationship between the survey’s school climate indicators and discipline rates cannot be accurately measured. However, findings of from the teacher responses provide specific insights into the normative and political forces that may contribute to Black and Latinx students’ likelihood to experience suspension. The results of the survey indicate incongruity between teachers’ reported opinions about student diversity and school discipline and actual practices. As described above, California has implemented technical approaches to reduce rates of exclusionary discipline in schools in the past decade. As a reflection of teachers’ corresponding attitudes about school discipline, 2% of educators surveyed reported that behavioral expectations in their schools were strict, and only 4% of teachers agreed it was easy for students to get suspended or expelled. However, 25% of elementary teachers and 18% of high school teachers reported the use of zero-tolerance policies in their schools. 50% of elementary school teachers and 32% of staff agreed that zero-tolerance policies were fair. Similarly, 47% and 45% of elementary and high school teachers respectively reported that disruptive behavior was a significant problem, and roughly a quarter of all teachers reported that students generally displayed a lack of respect for staff. Despite the belief that disruptive behavior is a significant problem, only 22% of teachers reported implementing restorative practices (an 8% decrease from the previous year), and 19% indicated that their schools used any trauma-informed practices to approach behavioral issues (California Department of Education, 2020). Teachers’ reported attitudes on racial disparities and cultural competencies were similarly mismatched with school practices. The majority of teachers across grade levels agreed that 29 school staff respected differences in students and reported feelings of respect for equity and cultural sensitivity, yet just 30% of teachers felt that closing the racial discipline and achievement gap was a priority. Only two in ten teachers reported participating in training to examine their own racial and cultural biases (WestEd Health and Justice Program for the California Department of Education, 2020). These survey data suggest that despite the statewide technical approaches to addressing the total number of students suspended and ameliorating the racial discipline gap, teacher attitudes and school-level policies place less priority on alternatives to zero-tolerance approaches to behavior problems. According to the report, the low percentage of teachers who endorse alternatives to suspensions is due in part to concerns over school safety and a lack of training in cultural competency (p.14). This was particularly true in the high schools studied, where school climate ratings among teachers were the lowest. In sum, districts are implementing Technical Responses to exclusionary school discipline, but teachers are not convinced of their efficacy, or do not believe they have been adequately prepared to adopt them skillfully. With this juxtaposition between the intention of policy, and teachers’ Normative Responses to the change as ineffective, implementation with full fidelity is dubious. This is consistent with findings in previous studies that while suspension rates are decreasing overall in California, the racial disparity in share of students suspended relative to enrollment remains largely unchanged (Skiba, 2014). The normative aspects of teacher beliefs are difficult to measure, but educator bias, adherence to tradition, and cross-cultural misunderstanding are among the probable factors that inhibit fundamental changes in school discipline practices. Similarly, the political context of schools is difficult to operationalize, but teachers reported insufficient funding for counseling 30 and mental health support, and the pressure to prioritize academic achievement usurping other priorities. These unobserved political influences may contribute substantially to racial disparities in student suspensions. The theoretical orientation of this study provides a foundation from which to consider contextual factors that may be associated with the primary outcome and predictors of interest. Measurable predictor and control variables might therefore include persistently exclusionary discipline practices, the presence of law enforcement, student-counselor ratios, or changes in academic achievement, as blunt proxies for the normative and political factors that contribute to change in school discipline over time. It is not my aim to test specific elements of the theory with respect to the outcome variable, but to inform the research questions and the interpretation of the results with the added nuance the theory provides. Likewise, the theoretical framework allows for a more comprehensive set of considerations for school discipline policy school discipline in changing, suburban California schools. 31 CHAPTER 3: Methods Rationale for the Present Study As school demographics change, Technical, Normative and Political Responses such as zero-tolerance policies, absence of cultural understanding, fear of criminality, and loss of previous academic and social status, may all contribute to use of exclusionary discipline practices relative to the proportion of Black and Latinx students enrolled. Schools with changing populations that served very few students of color in the recent past may also be less prepared to meet their needs. Alternatively, many schools may invest in building relationships within the community, accommodating the needs of new students, and addressing racial bias directly. Given that cultural and political school characteristics are largely unobservable, there may be variation among schools and districts that depart from statewide trends. Rooted in these ideas, I developed three research questions: RQ1: Is there a relationship between schools with increasing shares of Black and Latinx students and changes in Black and Latinx suspension shares in suburban California schools? RQ2: Is there an interaction between initial shares of Black and Latinx students enrolled and increasing enrollment of these students when predicting changes between Black and Latinx suspension rates in suburban California schools? What is the nature of this interaction? RQ3: Is there a relationship between persistently exclusionary schools and changes Black and Latinx suspension shares in suburban California schools? Based on the theoretical and empirical literature outlined above, I aim to test three hypotheses. 32 With respect to RQ1, I anticipate that schools with increasing proportions of Black and Latinx students will experience a positive association in with changes in Black and Latinx suspension shares in suburban California schools. This hypothesis is supported by Frankenberg’s (2012) suburban typology, which argues that considerable heterogeneity exists among suburban schools. For example, stable, Mixed-Income suburbs, which have very little racial change and few minority students, may experience no change in share of Black and Latinx students enrolled over time, and might therefore not experience any related tension about school discipline. Conversely, Inner-Ring Transitioning suburbs that are small in size and have experienced rapid demographic transformation, may have scarce resources to accommodate a changing population. Because these specific community aspects are outside the scope of this study, I will approximate each school’s experience with demographic change by whether its shares of Black or Latinx enrollment increased or decreased. Regarding RQ2, I hypothesize that lower initial shares of Black and Latinx enrollment will predict a positive difference between Black and Latinx suspension rates in suburban California schools. This means that on average, schools with a lower proportion of minority students enrolled in 2011 would predict a greater increase, on average, in changes between Black and Latinx suspension rates. Likewise, I predict that that the interaction between schools with increasing proportions of Black and Latinx enrollment and low initial enrollment will be positive. This hypothesis is rooted in prior research findings that suburban schools are often unprepared for demographic change with regard to both policy and cultural competency. (Frankenberg & Orfield, 2012). Specifically, Welton and colleagues found that veteran suburban educators often applied traditional school policies and practices to new students with a limited understanding of, or regard for, their diverse needs (2015). Consistent with the theoretical 33 orientation, this work suggests that educators’ Normative Responses to demographic change in schools with very few Latinx and Black students enrolled may involve assumptions about student ability and expectations for specific behavior that contribute to decisions to suspend Black and Latinx students more readily. Moreover, Blake and colleagues (2016) found that teachers with dissimilar racial backgrounds from the students they taught were less likely to be equipped with the cultural competency necessary to modify prior beliefs and behaviors in response to new student populations. This finding was echoed in Triplett’s (2014) study, which found that White teachers were more likely to dispense exclusionary discipline to students of color than were Black and Latinx teachers. Likewise, the composition of school personnel changes at a slower rate than does the student population in most contexts. As of 2018, the average percentage of White teachers in California was 63%, while just 23% of students were White. Table 3 describes the average proportion of total teachers and students by race in California, and details the percentage point change in demographic makeup between the 2011-12 and 2018-19 academic years (California Department of Education). 34 Table 3: Mean Share of Total Teachers and Students by Race Teachers Students Mean Mean Percentage Mean Mean Percentage Share Share Point Share Share Point 2011 2018 Change 2011 2018 Change Latinx 18% 21% 3% 51% 55% 4% Black 4% 4% 0% 9% 4% -5% White 67% 63% -4% 26% 23% -3% While there has been some change in the demographic makeup of teachers in the years described with a larger share of Latinx teachers in the workforce, the difference between the overall makeup of teacher ethnicity continues to differ from that of students. While California- specific data on the racial composition of teachers in suburban schools was not included in this study, the overall share of White teachers nationwide was 69% in 2018, similar to that of California. The makeup of suburban teachers was 82% White (National Center for Education Statistics, 2019). A largely White teacher workforce in suburban areas may be an indication that schools with few initial Black and Latinx students are unprepared to address the challenges of serving all students equitably. The prediction that an interaction between initial share of minority students enrolled and schools with an increased proportion of Black and Latinx is guided by the theoretical argument that intentional change to Normative and Political context takes time. Assuming that much of the suburban workforce is made up of White teachers, and that less collective experience with diverse populations, the combined effect of initial share and proportion increased might yield an association with changes between Black and Latinx suspension rates in suburban California schools. 35 With respect to RQ3, I hypothesize that persistently exclusionary schools will be positively associated with changes in Black and Latinx suspension shares. An initial, dominant culture of persistent exclusion stands in for a school’s practice of zero-tolerance policies, whether or not demographics have recently changed. Black and Latinx students are more likely to be suspended relative to their enrollment share in schools with zero-tolerance policies (Sumner et al., 2010). Likewise, students from backgrounds that differ from the students who preceded them are held to stringent standards of conduct, perhaps bringing to the classroom varying experiences and norms that may conflict with expectations in high-suspension schools (Wolf and Kupchik, 2016). The theoretical framework further supports the hypothesis for the third research question in light of previous findings. Zero-tolerance schools may have a trifecta of response types in place that inform teacher decisions about discipline in changing schools. Technical Responses, or adherence to policies of zero-tolerance, combined with Normative beliefs that exclusionary discipline is effective, and a potential Political context of community pressure for schools hold students to rigid behavioral expectations, may contribute to higher rates of suspension overall. Among schools that experienced an increase in Black or Latinx student share, rules, beliefs, and concern voiced by parents may be associated with to a positive relationship between persistently exclusionary schools and changes in Black and Latinx suspension shares. Study Site and Data Sample. To build a data set that incorporated students suspended, students enrolled, school urbanicity, and school characteristics, I used data from three sources: The California Department of Education, the Common Core of Data (CCD), and the Office of Civil Rights Data Collection (CRDC). The California Department of Education provided suspension and 36 enrollment data linked to student demographics from 2011 to 2018. Most school characteristics were taken from the Common Core Data. However, the Office of Civil Rights Data Collection supplied school staffing data. Because the frequency of exclusionary discipline varies among schools by grade level, and because Black and Latinx students are suspended on average at different rates (Barret et al., 2017), it was appropriate to examine the relationship between demographic change and disciplinary change in each distinct context. Six sub-samples were created to examine the research questions with more specificity. Elementary schools, as defined by the CCD, included schools that serve students in grades K-6. Schools in the Middle School sample include students in grades 7 and 8, and high schools serve students in grades 9-12. Each grade level sample included only schools that were racially heterogeneous with respect to the population of interest. Table 4 lists each of the criteria for including schools in the sample and the number of schools remaining after each of the conditions was applied. Table 4: Schools Remaining in Sample by Inclusion Criteria Black Black Black Latinx Latinx Latinx Elem. Middle High Elem. Middle High n= 5,805 1,361 2,152 5,805 1,361 2,152 Characteristic Suburban 2,121 683 509 509 2,121 683 Racially Heterogeneous 654 175 298 1,732 416 586 Non-Juvenile Justice 654 175 284 1732 416 571 Non-County Offices 654 175 271 1732 416 561 Non-Virtual Schools 612 157 180 1654 365 373 Non-Charter Schools 580 146 143 1573 359 299 Non-K-8 Schools 568 146 143 1565 359 299 Non-K-12 Schools 567 146 137 1563 359 293 Non-Preschools 567 146 137 1563 359 293 Total Schools in Sample 567 146 137 1,563 359 293 37 Using the Common Core Data’s definition of urbanicity, I combined the three suburban categories to create a suburban dummy, which included schools in large suburbs (79% of schools in the sample), mid-sized suburbs (13%%), and small suburbs (7%). Schools that remained racially isolated across the study period were excluded. Because this study is interested in demographic change, persistently isolated schools are not informative to its objective. The cut points for inclusion in the sample are in large part consistent with Frankenberg’s (2007) characterization of non-White racial isolation. According to Frankenberg, racially isolated schools are defined in most social science literature as schools with more than 90% racial homogeneity in one racial group. The article likewise observes that because a large proportion of schools remain a state of isolation while others experience change, considering both the status of racial isolation, and whether demographics have changed is important to understanding the racial dynamics of a given setting. Based on this framework, I modified the benchmarks to accommodate the focus of my research questions and consider the unique context of California. First, I argue that both extremely high or low shares of one racial group indicate racial isolation in schools. Because I am interested in observing demographic and disciplinary trends among racial minorities, I set both minimum and maximum requirements for inclusion in each sample. Second, while 90% homogeneity is the cutoff established in previous literature, California had a very low rate of Black student enrollment overall during the years examined. Setting the minimum school inclusion criteria at 10% of students enrolled would have excluded roughly 60% of all Black suburban students. In order to make any meaningful observation about Black student suspension change, therefore, I adjusted the criteria for the Black samples. 38 Among the Latinx samples, Latinx students must have made up greater than 10% and less than 90% of the school’s enrollment during at least one of the two time periods in the study (details on the decisions about operationalization of the timeframe will be discussed in the upcoming section). Among the Black samples, schools with a share of Black students that was greater than 5% and less than 95% were included. Charter schools were excluded from the analysis because their enrollment patterns are often based on parent choice rather than residential assignment, so their demographic makeup may be biased by self-selection and may not reflect the surrounding population. Also, charters in California have relative autonomy regarding the discipline policies used in schools, with little guidance or influence from a common district. Finally, based on evidence that charters have historically under-report suspensions and expulsions, the data on school discipline infractions is unreliable (Losen et al., 2016). Juvenile justice education facilities and County Offices of Education schools were also excluded, as the population in these settings is largely students who have been expelled from public schools or in contact with the criminal justice system. The discipline practices in these contexts are therefore likely to deviate from patterns in traditional public schools. Despite the exclusion of schools that fell outside the above criteria, each sample contains the majority of the statewide suburban population of interest. Table 5 details the percentage of students represented within each sample. 39 Table 5: Percentage of Students Represented in Samples by Race, Grade Level Sample Black Black Black Latinx Latinx Latinx Characteristic Elem. Mid. High Elem. Mid. High n= 5,805 1,361 2,152 5,805 1,361 2,152 % Suburban Black Students in Sample 82.6% 82.7% 78.3% 75.1% 76.5% 77.9% % Suburban Latinx Students in Sample 33.0% 37.4% 33.6% 95.9% 97.5% 95.4% % Suburban White Students in Sample 25.5% 30.6% 35.2% 89.4% 87.4% 84.2% To illustrate, the Black Elementary sample contains 82.5% of the total Black students enrolled in suburban schools statewide. Likewise, the Latinx Elementary sample contains 95.9% of all suburban Latinx students, suggesting that the coverage in the sample is quite comprehensive and is likely representative of the context of suburban education for the vast majority of Black and Latinx students in California. Table 6 describes the means of each of the school characteristics by sample. Table 6: School Characteristics by Sample Black Samples Latinx Samples School Characteristic Elem Middle High Elem Middle High n= 567 146 137 1,563 359 293 ELA Proficiency 36.0% 41.8% 40.1% 44.8% 50.0% 48.0% Math Proficiency 37.9% 27.5% 16.8% 47.5% 36.1% 23.3% Percent FRL 64.6% 71.7% 70.3% 58.7% 58.8% 59.1% Percent ELL 66.5% 26.9% 17.2% 66.5% 34.0% 22.4% Police 87.7% 76.5% 61.9% 84.8% 81.3% 57.3% Teacher Ratio 24.6 24.3 25.3 24.2 24.5 24.5 Support Ratio 979.1 550.8 282.9 979.0 532.3 286.8 School Size 717 1021 1143 640 908 1200 The school characteristics reveal some disparities in resources and achievement among the samples along racial lines. Among both racial groups, math proficiency declined as students 40 progressed in age. However, schools in the Black Middle and High School samples had lower average math achievement. Likewise, ELA achievement was higher among schools in the Latinx samples across all grade levels. Schools in the Black samples had higher rates of students who qualified for free/reduced-price lunch. Students across all grade levels compared with schools in the Latinx samples, although on average, low-income students made up more than half of the student population. The percentage of English Language Learners was comparable between schools in both racial groups. This is likely because of the small proportion of enrollment of Black students in California schools. Because the samples are not mutually exclusive, large shares of Latinx students, some of whom receive ELL services, are represented in the Black school samples as well as the Latinx school samples. Police presence, teacher-to-student ratio, and support staff-to-student ratios, along were roughly similar in both groups. As a final note on the sample, the term, “suburban” carries cultural connotations and suburban areas themselves are highly varied. Urban and suburban schools have often been viewed in scholarship and popular media as diametrically opposed; that is, urban schools have been associated with poverty, an absence of resources, and high proportions of students of color. Suburban schools, on the other hand, have been traditionally associated with being predominantly White, highly resourced, and higher achieving, on average, than their urban counterparts (Lewis-McCoy, 2014). Prior studies have called for a more precise and disaggregated documentation of student demographics and educational experiences in suburban schools (Leonardo & Hunter, 2007). While nuance in suburb type would provide useful information about suburban student disciplinary outcomes based on school characteristics, this study attempts to mediate some of the bluntness of “suburban” as a category through the use of sub-samples that enable distinct 41 analyses by grade level and racial composition. Performing each analysis by grade level will create a detailed portrayal of suburban school communities beyond their geography and categorization as suburban. This is especially important when examining patterns of discipline among Black students, as the population of Black children in schools is concentrated in relatively few suburban schools due to historical de jure segregation and current patterns of de facto segregation (Holme, Diem, & Welton, 2014). The specific focus on suburban schools that serve Black students in varying proportions allows the study to estimate potential relationships between predictors and change in suspension share, controlling for socioeconomic status, roughly approximating some of the characteristics that distinguish one suburb from another. Variables Table 7 describes each of the variables. For variables that required operationalization, such as Persistently Exclusionary, the criteria for the threshold are detailed as well. 42 Table 7: Description of Variables Variable Variable Name Description Outcome Change between share of students suspended at Time 2 Suspension and Time 1, change between share of students enrolled suspchange Share Change at Times 2 and 1, and the difference between change in share suspended and change in share enrolled Predictors School = 1 if school had increasing or decreasing shares of increase Increased Black or Latinx students, 0 otherwise Initial share of Black or Latinx students enrolled. enrshare Initial Share Specific to sample Exclusionary = 1 if school had high proportions of all students exclusion suspended in 4 out of the 8 years of the study period, 0 School Controls otherwise ELA Percent students met or exceeded English Language ela Proficiency Standards. Separate values for grades 4, 8, and 11 Math Percent students met or exceeded English Language math Proficiency Standards. Separate values for grades 4, 8, and 11 Share of total students who qualify for free or reduce- percFRL Percent FRL priced lunch Share of students classified as English Language percELL Percent ELL Learners Presence of law enforcement officer on school grounds police Police in 2011 teachratio Teacher Ratio Ratio of teachers to students across the study period Ratio of combined psychologists and counselor to sprtratio Support Ratio students across the study period schoolsize School Size Average total students enrolled across the study period The percentage of students enrolled and students suspended were both required for the calculation of the outcome variable, and each was averaged across three-year periods, between the academic years of 2011-12 to 2013-14, and 2016-17 and 2018-19. These two periods are called Time 1 and Time 2 throughout the study. The decision to use three-year averages rather than simply measuring change between 2011 and 2018 was motivated by anticipation of 43 erroneous or anomalous data reporting in a given year. Using averages across three-year periods allows for the mitigation of this possibility. However, the models will be also estimated using the 2011 to 2018 change as a sensitivity test. Outcome Measures. The outcome variable is the difference in the change between shares of students suspended at Times 1 and 2 and shares of students enrolled at Times 1 and 2 of the study. This variable is calculated by subtracting average suspension shares in Time 2 from average suspension shares in Time 2, and subtracting average enrollment shares in Time 2 to average enrollment shares in Time 1 with the following equation: 𝑠𝑢𝑠𝑝𝑐ℎ𝑎𝑛𝑔𝑒 = (𝑦-!" − 𝑦-!# ) − (𝑦-$" − 𝑦-$# ) Where s is the share of students suspended, e the share of students enrolled, 2 indicates Time 2, and 1 indicates Time 1. The outcome variable is designed to capture the average disparity between shares of students suspended and shares of students enrolled between the two time periods. Predictors. The predictor of interest for Research Question 1 is increase, which is a dummy variable indicating whether a school experienced increasing or decreasing shares of Black or Latinx students between Times 1 and 2. The predictor, enrshare, measures the initial share of Black or Latinx students at the beginning of the study period, and is the key variable in the RQ2 hypothesis test. It was calculated by dividing the number of Black/Latinx students by the total number of students 44 enrolled in 2011.1 The model that introduces the interaction between enrshare and increase will use the same variable to multiply with School Increase. Like all variables, enrshare will be distinct among each sample. A dummy variable, exclusion, describing a school as persistently exclusionary will be added to the model to test the RQ3 hypothesis. Consistent with Lindsay and Hart’s (2018) methodology for measuring persistently exclusionary schools, I created an indicator based on the median of total average suspensions during Time 1 by grade level. In the elementary context, a share of 2.5% or greater of total students suspended indicated that a school practiced persistently exclusionary discipline as a norm. In middle and high school contexts, schools with a share of greater than 12% of total students suspended indicated persistent exclusionary practices. While measuring heterogeneity in school norms and suburban locale is limited with the data available, I created a measure of “persistently exclusionary” schools to stratify schools between high- suspension and lower-suspension approaches to discipline. Persistent exclusion is therefore used as a proxy for schools that had a normative response to school discipline that involves beliefs about the importance of order. Controls. Several additional school-level variables will be added to the analysis to control for school characteristics. These variables include academic achievement measures, which were calculated as schools’ average percentage of students that met or exceeded standards on the English Language Arts and Math Smarter Balanced assessments. Average achievement for 4th, 8th, and 11th grade students was calculated within their respective elementary, middle, and high school samples for both racial groups. Percent FRL was likewise centered on the mean and 1 A quadratic term for enrshare was introduced to the model to test for linearity. Because outcome of the model using the quadratic variable was not statistically significant, the relationship is assumed to be linear, and the quadratic term was omitted from the model. 45 may be interpreted as a proxy for students from low-income households. Likewise, Percent ELL quantified the share of students who received English Language Learning services. Percent ELL might be interpreted as a proxy for the share of students who may experience additional academic, cultural, and linguistic challenges as potential newcomers in a district. Among the school personnel control variables, the binary variable police indicates whether schools have at least one full-time law enforcement officer on campus. Teacher Ratio and Support Ratio quantify the number of staff per student in each school. Support staff was defined as the combined number of psychologist and counselors in a given school. All continuous variables in the study were centered on the mean and converted to a percentage to create comparable coefficients and facilitate interpretation. Analytic Strategy Six identical ordinary least squares regressions will estimate the linear relationship between suspension change and the key predictors for each sample. That is, the value of the outcomes and predictors will vary by racial group and grade level, but the models will remain consistent across each analysis. Each research question incorporates new predictors into the models, which I will discuss below, in turn. RQ1: Is there a relationship between changes in Black and Latinx enrollment shares and changes in Black and Latinx suspension shares in suburban elementary and high schools in California? The model that estimates the first research question is the following: 𝑦1 = 𝛽3 0 + 𝛽3 1 +𝜷 5 2 + 𝑒̂ where 𝑦1 is suspension share change, 𝛽3 0 is the constant, which represents the average change in the difference between suspension and enrollment shares at the baseline with no relationship 46 between the predictors and outcome variables. 𝛽3 1 is increase, a dummy variable that represents schools with increasing shares of the Black/Latinx enrollment. 𝜷 5 2 is a vector of control variables that include the school characteristics listed in Table 6. I anticipate that the constant for each sample will indicate an increase in the difference between suspension and enrollment shares. A coefficient greater than 0 would indicate that the disparity between suspension and enrollment shares widened over the study period, meaning that regardless of the predictors introduced, Black and Latinx students in suburban schools will be suspended at a rate greater than their share of enrollment between Time 1 and Time 2. For example, if the constant were statistically significant at 1.5, the model would indicate that at baseline, the difference between the share of students suspended and enrolled will have increased by 1.5% between the periods of 2011-13 and 2016-18. I hypothesize that the coefficient for an increasing proportion of Black/Latinx students will also be positive. A positive, statistically significant coefficient greater than 0 in this model would indicate that schools with increasing shares of Black/Latinx students predict an increase in the difference between suspension and enrollment shares over time. Thus, if the coefficient for Black elementary students were 3.0 with a constant term of 1.5, Black students in schools with increasing proportions of Black enrollment would be suspended, on average, 4.5 percentage points greater than their share of enrollment between Times 1 and 2. RQ2: Is there a relationship between an interaction between initial shares of Black and Latinx students enrolled and increasing enrollment shares and change in the difference between Black and Latinx suspension shares in suburban California schools? What is the nature of this interaction? 47 The second research question corresponds to the model below: 𝑦1 = 𝛽3 0 + 𝛽3 1 +𝛽3 2 + 𝛽3 3 (𝛽3 1 *𝛽3 2) +𝜷 5 4 + 𝑒̂ where 𝑦1 is suspension share change, 𝛽3 0 is the constant, 𝛽3 1 is increase, 𝛽3 2 is the initial share of Black or Latinx students enrolled at the start of the study. 𝛽3 3 is an interaction term between the proportion increase dummy and the enrshare, which will indicate whether the two predictors have a combined effect on the outcome. 𝒃 54 is a vector of control variables that include the school characteristics described in Table 6. RQ3: Is there a relationship between persistently exclusionary schools and change in the difference between Black and Latinx suspension shares in suburban California schools? 𝑦1 = 𝛽3 0 + 𝛽3 1 +𝛽3 2 + 𝛽3 3 (𝛽3 1 *𝛽3 2) +𝛽3 4 +𝜷 5 5 + 𝑒̂ The third model includes the predictors listed in the first two, but introduces 𝛽3 4, exclusionary, as a predictor. I hypothesized that schools labeled as persistently exclusionary across all student demographics will correlate with higher rates of change in suspensions of students of color. Further, I predict that persistently exclusionary schools and larger differences in the proportion of enrollment change during the study period will be more likely to have larger proportions of Black and Latinx suspensions. This would mean that the slope of the relationship between suspension share and enrollment share for Black/Latinx students would be different based on whether the school is persistently exclusionary. Separate coefficients can be interpreted to understand the effect of persistent exclusion on the relationship between the outcome and the predictor. For example, persistently exclusionary schools may have a coefficient of 2.4, while 48 non-persistently exclusionary schools may have a slope of 1.2, which would indicate that while students of color are more likely to be suspended than expected, those in persistently exclusionary schools are suspended at a rate of double those in non-persistently exclusionary schools. 49 CHAPTER 4: Results In the sections below I summarize the results of the descriptive statistics, followed by the presentation of the analytic results, organized by research question. Descriptive Results Enrollment Trends. Overall enrollment in the combined state and federal data sets indicate that California schools decreased by 5% during the study period. The drop in enrollment was greatest among Black students, which declined 21% from 293,599 to 231,451. The population of White students, which is roughly three times greater than that of Black students, declined by 14%. Latinx students, on the other hand, who account for the majority of students enrolled in California schools, dropped by just 1%. In suburban schools, the trend is similar (California Department of Education). Enrollment in California suburban schools likewise declined overall during the study period. The share of White students declined more sharply than any other group, particularly in high schools. Latinx student enrollment decreased at a lower rate than either Black or White students. In urban schools, the trend was somewhat reversed; White student enrollment dropped 13%, a lower rate of change than in suburban schools and statewide, while Black and Latinx populations in urban schools decreased at greater rates compared to suburban schools. While the Black suburban student population dropped 21% in suburban schools, it declined by 23% in urban schools. Likewise, Latinx disenrollment, while stagnant in suburban schools, fell by 4% in urban schools (See Appendix A). Comparing urban and suburban enrollment trends, students of color decreased in urban schools at a greater rate than in suburban schools, while the opposite is true for White students, who remained in urban schools in larger proportions than in suburban schools. 50 Considering schools within the study samples, Black students made up the minority of enrolled students in California schools in both time periods across all school types. The average suburban enrollment among Black students dropped from 8.2% of total students enrolled, to 4.5% of total students enrolled in California, a 3.6 percentage point change. While the enrollment change among Black students was the same between urban and suburban elementary school populations, Black student enrollment decreased at a slightly lower rate among urban middle and high school students. The total enrollment decrease among Black students in California is greater than either the suburban or urban subgroups, indicating the decline in enrollment in small towns and rural areas is driving some of the change. Table 8: Suburban, Urban, and Total Enrollment by Race, by Year Time 1 Time 2 Percentage Point Change Black Latinx Black Latinx Black Latinx Suburban Elementary 14.0% 49.2% 12.4% 51.5% -1.6% 2.3% Middle 13.0% 49.2% 10.6% 52.4% -2.4% 3.2% High 14.6% 50.4% 11.1% 53.3% -3.5% 2.8% Total 13.9% 49.4% 11.9% 51.9% -2.1% 2.5% Urban Elementary 16.6% 51.9% 14.6% 53.4% -2.0% 1.4% Middle 16.2% 51.5% 13.6% 53.5% -2.6% 1.9% High 17.8% 53.0% 15.0% 55.3% -2.9% 2.4% Total 16.7% 52.7% 14.5% 53.6% -2.2% 0.9% All Elementary 15.2% 49.1% 13.4% 51.2% -1.8% 2.0% Middle 14.5% 49.2% 12.1% 51.9% -2.3% 2.7% High 16.1% 50.4% 13.2% 52.9% -3.0% 2.5% Total 15.2% 49.3% 13.2% 51.6% -2.1% 2.2% Table 8 displays the percentage of students enrolled by racial group and grade level for the suburban schools in the sample along with urban schools that fell within the sample criteria 51 (e.g., excluding juvenile justice facilities, charter schools, racially homogenous schools). Latinx students were the only group with consistent increases in the share of students enrolled in California schools. The percentage of enrollment comprised of Latinx students increased across all grade levels in both suburban and urban schools. The statewide change in enrollment share between Time 1 and Time 2 also increases among elementary and middle school students, but decreases slightly among high school students. Comparing the change in urban and suburban enrollment among Latinx elementary schools, the share of enrollment increased at twice the rate in suburban schools. Latinx elementary student enrollment increased by 1.8 percentage points in suburban schools and 0.9 percentage points in urban schools. The share of Latinx middle and high school students also grew at a greater rate in suburban schools than in urban schools. The share of White students enrolled in California schools decreased more during the study period than did Black and Latinx students. This decrease was greatest among suburban White students across all grade levels and particularly notable among high school students. The share of White students in urban schools decreased by 4.7 percentage points, while the proportion of White students in suburban schools decreased by 7.7 percentage points. The share and total number of students enrolled by race between 2011 and 2018 communicate an incomplete description of the heterogeneity in change among schools and school types. While enrollment decreased on average statewide, and some dissimilarity among groups varies by urbanicity, as well as by school. Figure 1 provides more detail about the type of suburban and urban schools that experienced increasing shares of Black and Latinx students enrolled during the study period. 52 Figure 1: Percentage of Schools Statewide with Increasing and Decreasing Shares of Students by Urbanicity, Race Shares of increasing and decreasing students in each of the six suburban and urban categories varied by racial group. Increasing proportions of White students enrolled were greatest in urban schools. While 66% of schools in large cities experienced a decrease in White students, 34% of schools had increasing shares of White students. 22% of schools in mid-sized and small cities experienced an increase in White students. Comparatively, fewer suburban schools had increasing proportions of White students. 15% of schools in large suburban areas 53 experienced an increasing share of White students, and 9% and 16% of schools in mid-sized and small suburban areas experienced an increase in the share of White students enrolled, respectively. The pattern of greater rates of increasing enrollment in urban areas among White students was inverse in comparison to Latinx enrollment. More schools in suburban areas of all sizes experienced increasing shares of Latinx students than did schools in urban areas. 67% of schools in small suburbs experienced increasing shares Latinx student enrollment, 81% of schools in mid-sized suburbs experienced an increasing proportion of Latinx enrollment, and 69% of schools in large suburbs had rising shares of Latinx students enrolled. Comparatively, 62%, 66%, and 59% of schools in small, mid-sized, and large cities had rising shares of Latinx students enrolled during the study period. This indicates that while White families enrolled students at greater rates in cities, Latinx families chose suburban schools more frequently than urban schools. Fewer schools in California experienced increasing proportions of Black students compared to White and Latinx students. However, a relatively large percentage of schools in mid-sized and large suburbs experienced rising enrollment among Black students, at 21% and 20%, respectively. 23% of schools in large cities had rising shares of Black students, yet only 17% and 15% of schools in mid-sized and small cities had increasing proportions of Black students. On average, schools in suburban areas had higher rates of increasing Black enrollment than in urban areas. Table 9 therefore describes the number and percentage of schools within the sample that experienced an increase or decrease in share of Black and Latinx students relative to total enrollment within the study samples. 54 Table 9: Number and Percentage of Schools Statewide with Increasing and Decreasing Shares of Students by Sample Black Samples Latinx Samples Elem Middle High Elem Middle High Decreased 358 103 84 949 272 179 % Sample Decreased 63% 71% 61% 61% 76% 61% Increased 183 38 29 468 77 77 % Sample Increased 32% 26% 21% 30% 21% 26% Total Schools 567 146 137 1,563 359 293 The percentage of schools with increasing shares of Black and Latinx students is roughly consistent across all samples. While Black student shares decreased on average, between 21% and 32% of schools experienced an increase in the share of Black students. Conversely, while Latinx enrollment shares increased on average across all samples, only 21-30% of schools experienced an increase in proportion of Latinx students enrolled. This suggests that the demographic change among Latinx students is concentrated among relatively few schools. An analysis of enrollment suspension rates among White students and students in urban areas is outside the scope of this study, since its central concern suburban schools specifically. However, the description of enrollment and suspension trends among White and urban sub- populations is demonstrates the variety of change patterns in California. Given the diversity in trends in enrollment change, the relationship between key variables is likely to vary depending on racial group and grade level. Suspension Trends. The variation in enrollment change among each type of urban and suburban area suggests that not only are schools heterogeneous in their experience of demographic transformation, but also that each racial group is distinct in patterns of enrollment. Suspension rates differ between schools urban and suburban contexts as well. 55 Table 10 describes the percentage of all students suspended by race. In suburban elementary schools, for example, 29% of all students suspended were Black students at Time 1, 27.6% of all elementary suburban elementary students were Black students in Time 2, which results in a decrease of 1.5 percentage points Table 10: Percentage of Total Students Suspended by Race, by Time Period Time 1 Time 2 Percentage Point Change Black Latinx Black Latinx Black Latinx Suburban Elementary 29.1% 45.6% 27.6% 47.2% -1.5 1.6 Middle 23.8% 53.1% 21.5% 53.7% -2.3 0.6 High 23.5% 51.6% 19.4% 53.7% -4.1 2.1 Urban Elementary 36.3% 46.3% 33.2% 47.6% -3.2 1.3 Middle 30.4% 53.8% 28.1% 55.0% -2.3 1.2 High 30.7% 51.8% 29.0% 53.2% -1.7 1.4 All Elementary 32.6% 44.5% 30.2% 46.3% -2.4 1.8 Middle 27.1% 51.8% 25.0% 53.0% -2.1 1.2 High 26.7% 50.2% 24.2% 52.1% -2.5 1.9 However, the number of Latinx students far outweighs the population of Black students enrolled. It is therefore necessary to consider the change in share of students suspended in comparison to the change in share of students enrolled for each group to gain a deeper understanding of suspensions in relation to demographic change. To illustrate the share of students suspended relative to their enrollment, Figure 2 represents illustrates the total number of students suspended divided by the total number enrolled in each racial group in both suburban and urban areas. It appears that the share of Black students suspended is decreasing most in suburban elementary schools and urban high schools. Likewise, suburban and urban high schools have increased the share of Latinx students suspended over time. 56 Figure 2: Share of Students Suspended by Sample Across all grade levels, a higher proportion of Black students was suspended on average in the years from 2011 to 2018, at nearly twice the rate of Latinx and White students. There is also some disparity in the suspension rates between suburban and urban schools. Suburban schools almost invariably suspended larger proportions of Black, Latinx, and White students. Most relevant to the outcome variable, Table 11 describes the gap between the share of students suspended and enrolled. The outcome variable is operationalized somewhat differently than the figures in Table 11—suspchange was constructed as the differences between suspension shares at Times 2 and 1, the differences between enrollment shares at Times 2 and 1, and calculates the difference between the two. However, Table 11 provides a descriptive baseline to consider regarding the concept of the discipline gap. 57 Table 11: Percentage Point Difference Between Share of Students Suspended and Share of Students Enrolled, by Sample Time 1 Time 2 Change Black Latinx Black Latinx Black Latinx Suburban Elementary 15.1 -3.9 15.2 -4.4 0.1 -0.5 Middle 11.0 3.9 11.0 1.3 0.0 -2.5 High 8.8 0.9 8.8 0.4 -0.1 -0.5 Among the Black suburban elementary sample, the average difference between share of students suspended and share of students enrolled at Time 1 was 15.1 percentage points, which means that if the average share of Black enrollment in these schools were 5%, the average share of Black students suspended would have been 20.1% on average. The same calculation was made for the sample at Time 2, resulting in a 15.2 percentage point difference. The average change in this gap between Times 1 and 2 was minimal, between -0.1 and -0.1 percentage points depending on the grade level. Students in the Latinx samples did not experience parallel trends with regard to the discipline gap. In fact, students in the Elementary Latinx sample were suspended at a lower rate than their share of enrollment in both time periods. In middle and high schools, students in the Latinx samples had a relatively low gap between share of students suspended and share of students enrolled. Additionally, the gap narrowed for both groups between Times 1 and 2. Persistently Exclusionary Schools Examining the breakdown of Black, Latinx, and White samples also provides information about which type of school is more likely to use persistent exclusion as a primary method of discipline. Figure 2 illustrates the percentage of schools that were considered persistently exclusionary during the study period. 58 Figure 3: Percentage of Persistently Exclusionary Schools by Sample Schools in the Black student samples had substantially higher proportions of high- suspension schools, with more than half of the schools in each sample considered persistently exclusionary. Also of note is that a slightly higher share of elementary schools was persistently exclusionary than the other grade levels among the Black samples. Among Latinx samples, an average of 38% of schools were considered persistently exclusionary. Finally, the schools in the White had the lowest share of high-suspending schools, with 32% of elementary schools, 30% of middle schools, and 35% of high schools coded as persistently exclusionary. Analytic Results Prior to describing the results in reference to each research question, consideration of the findings regarding the constant term, suspchange, anchors the interpretation of the other coefficients in the model. The intercept is named suspchange just as the outcome variable is in 59 the model and represents the baseline change in suspension shares for Black and Latinx students during the study period absent the influence of the other variables. It therefore provides a meaningful value in the interpretation of each model. The results of the OLS analysis of the Black Elementary sample, indicate that the constant is negative and statistically significant (est. = -7.26 p<0.01). The coefficient demonstrates a 7.26 percentage point decrease in share of Black elementary students suspended during the study period. For example, if a school demonstrated 7.26 percentage point gap in students suspended relative to students enrolled at Time 1 (meaning that Black students were suspended at a rate of 7.26 percentage points higher than their share of enrollment), students in that same school would be estimated to have a suspension-enrollment share gap of 0 in Time 2 (indicating proportionate shares of students suspended relative to enrollment shares) based on the model. The intercept therefore provides a consequential baseline for interpreting the results of the coefficients of interest among each of the samples. The constant was negative and statistically significant in each of the Black Samples (est. -7.26 p<0.01 for elementary, est. - 2.919 p<0.1 for middle school, and est. -11.7 p<0.01 for high school). The baseline change in suspension share among all Black samples, therefore is negative; on average, Black students were suspended at a rate lower than their share of enrollment when other contributing factors are absent. The results of the model’s constant terms were less consistent across groups among the Latinx samples. The baseline value of suspchange was negative in the elementary and middle school samples (est. -1.67 and -3.45, respectively), but the coefficient was statistically significant only among middle schools (p.<0.1). The intercept in the high school sample had an estimated value of 3.15, but was not statistically significant. Moving forward with the interpretation, the 60 constant term provides a reference point from which to interpret the relationship between each predictor and the outcome. Examples of this interpretation will follow while the models that estimate the relationships established by each research question are discussed in turn. The results of the OLS regressions yielded some consistency among all samples with regard to the research questions. RQ1 tested the hypothesis that increasing proportions of Black and Latinx students would be positively associated with changes in Black and Latinx suspension shares in suburban California schools. This hypothesis is supported across each of the six samples. In all cases, there was a positive, statistically significant relationship (p<0.01) between increase and suspchange. The coefficients were largest among the Black student samples across all grade levels (est. = 7.95 p<0.01 for elementary, est. = 7.198 p<0.01 for middle school, and est. = 7.949, p<0.01 for high school). The coefficient was similarly high in the Latinx elementary sample (est. = 8.22, p<0.01), although the model predicted very little of the variation in change in suspension share for both Black and Latinx school samples (R2 = .062 and .042, respectively). To further illustrate the substantive interpretation results, the Black middle school sample yielded a statistically significant coefficient of 7.198, while the constant term among the Black middle school sample was -2.919. Therefore, schools in the Black middle school sample could expect a decrease in the gap between suspension shares of 2.919 percentage points during the study period on average. However, among schools in the sample with increasing shares of Black students, the change in suspension share is estimated to be 7.198 percentage points higher. Therefore, schools with increasing shares of Black middle school students would have a predicted increase in suspension share difference of 4.279 percentage points between Times 1 and 2. 61 Research Question 2 considered the relationship between initial share of students enrolled and the outcome variable. I hypothesized that schools with lower shares of initial Black and Latinx enrollment would have higher rates of change in suspension shares during the study period. I also predicted a positive relationship between the outcome variable and an interaction between initial enrollment share and schools that experienced an increase in proportions of Black and Latinx students during the study period. In contrast to the findings related to RQ 1, the regression results do not support either of these hypotheses. There appears to be no statistically significant relationship between lower shares of Black and Latinx enrollment at the start of the study and increased change in suspension share over time. Likewise, the models that included the interaction term found no association between the combined values of enrshare and increase and the outcome variable. While the results for RQ1 and RQ2 were uniform in their support for and rejection of the relative hypotheses across all samples, the findings related to Research Question 3 were varied. I hypothesized that the relationship between persistently exclusionary schools and changes in Black and Latinx suspension shares in suburban California schools would be positive and significant across all samples. The results suggest that this positive, significant relationship exists among schools in the Black elementary sample (est. 3.303, p< 0.1). There does not appear to be a relationship between persistently exclusionary schools and change in suspension share in Black high schools or in either middle school sample. Among the schools in the Latinx high school sample, however, persistently exclusionary were actually predictive of a decrease in change in suspension share (est. -3.267, p<0.05). Taken together, we can conclude that among the six samples, the RQ3 hypothesis is supported in the Black elementary school sample but must be rejected for the other five samples 62 in the study. Regarding the Latinx high school sample, persistently exclusionary schools have the opposite relationship with the outcome variable than hypothesized. To expand, the baseline change in suspension share was 3.15 without explanatory variables. This signifies a 3.15 percentage point increase in the share of Latinx high school students suspended relative to their enrollment over time (although the constant is not statistically significant). Schools that initially used persistently exclusionary practices actually improved the discipline gap over time in the Latinx high school sample. Schools suspended Latinx students at a rate of 3.15 percentage points more, on average, between Times 1 and 2, relative to their enrollment share. Those that were initially labeled persistently exclusionary, however, decreased the disparity by 3.267 percentage points. Therefore, considering the only the explanatory factors associated with persistently exclusionary status, the change in the gap between suspension and enrollment shares would be - 0.117 percentage points, an overall reduction in disproportionate discipline, among persistently exclusionary schools in the Latinx high school sample. The results of the final models for each sample are described in Table 12 (full results by sample for each model are in the Appendix). With the exception of the predictor, increase, there is little uniformity across samples with regard to the school characteristics that were associated with the outcome. Average achievement on in English Language Arts was positively correlated with the outcome in the Black middle school sample (est. .243, p<0.01), which suggests that middle schools with higher levels of English achievement increased the share of Black students suspended over time in middle schools. School size and percentage of students who qualified for free and reduced-price lunch were positively associated with the suspchange in the Black high school sample (est. .304, p<0.05 and est. .146, p<0.05, respectively) This result is unusual in the context of literature that 63 observes large schools and high shares of low-income students are more likely to have high rates of suspension. In this case, larger schools tended to reduce the share of Black students suspended over time, as did schools with a higher proportion of low-income students. Finally, the proportion of English Language Learners was negatively associated with the outcome variable in the Latinx middle and high school samples. While the coefficients were modest (est. -.073, p<0.1 and est. -.082, p<0.1), these results suggests that schools with more ELL students decreased the share of Latinx students suspended relative to their enrollment share over time. 64 Table 12: Summary of Regression Results, by Sample Black Black Black Latinx Latinx Latinx Elem. Middle High Elem. Middle High School School School School suspchange -7.26*** -2.919* -11.7*** -1.67 -3.45* 3.15 (2.12) (1.517) (4.24) (2.178) (1.908) (4.993) increase 7.95*** 7.198*** 7.949*** 8.22*** 4.965** 4.82** (1.926) (2.32) (2.301) (1.53) (1.484) * (2.403) enrshare .032 .043 -.082 -.062 -.008 -.05 (.059) (.044) (.056) (.064) (.06) (.094) exclusion 3.303* -.676 -1.11 -.726 1.009 -3.267* (1.804) (1.243) (1.68) (1.491) (1.251) (1.735) ela -.121 .243*** -.075 -.064 -.009 .109 (.121) (.087) (.072) (.096) (.079) (.07) math .135 -.136 .095 -.019 .006 -.29*** (.11) (.09) (.109) (.089) (.07) (.086) police 2.112 -.27 -.902 -1.518 -.226 .622 (2.039) (1.356) (1.679) (1.809) (1.338) (1.613) teachratio .071 .174 .158 -.394** -.238 -.042 (.242) (.174) (.098) (.193) (.171) (.115) sprtratio .001 .001 -.016** 0 0 .007 (.001) (.001) (.007) (.001) (.001) (.008) schoolsize .191 -.006 .304*** .338 -.121 -.105 (.407) (.26) (.113) (.343) (.19) (.113) percELL -.019 -.075 .011 -.021 -.073* -.082** (.054) (.046) (.038) (.038) (.041) (.037) percFRL -.052 .061 .146** .062 -.025 .031 (.06) (.055) (.056) (.049) (.044) (.057) increase * enrshare .093 -.014 .081 -.031 .003 -.003 (.098) (.129) (.102) (.062) (.06) (.091) Observations 434 136 102 1156 325 221 R-squared .064 .209 .248 .042 .067 .118 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 As a final observation about the results, the R2 values indicate that while statistically significant and substantively meaningful relationships between the outcome and some of the predictors, the models explain relatively little of the variation in the outcome in both elementary school samples. The models have more explanatory power when applied to the middle and high school samples, particularly in the Black samples. The weak- to moderate- explanatory ability of 65 the model suggests that there exist omitted variables that explain more of the variation in the outcome. As mentioned, these variables may be related to factors that are difficult to quantify. The Discussion will consider potential omitted variables, including normative and political factors, that may affect the outcome variable. 66 CHAPTER 5: Discussion Considering research documenting the demographic transformation of American suburbs, I examined the relationship between enrollment change and student discipline in suburban, California schools. I measured the change in shares of students suspended by race, and its relative association with increasing proportions of Black and Lanitx students, the initial racial makeup of the school, and schools’ demonstrated practices of exclusionary discipline. I found that schools with increasing proportions of Black and Latinx students had a greater increase in the share of Black in Latinx students suspended over time than did schools without increasing proportions of Non-White students. Regarding initial share of students enrolled, I did not find evidence to suggests that lower proportions of Black and Latinx students of color enrolled at the beginning of the study were related to a change in student suspension shares over time. Exclusionary discipline had mixed results with respect to change in suspension share among Black and Latinx students. Schools that were persistently exclusionary at the beginning of the study were associated with a greater increase in suspension shares over time in the Black elementary sample. There was no relationship with exclusionary discipline practices among the middle schools in the sample, nor in the Black high school sample. Surprisingly, among Lanitx high schools, persistently exclusionary discipline was associated with a decrease in suspension shares over time. The primary finding, therefore, is a strong relationship between whether or not schools experienced an increase in the proportion of Black and Latinx students over time and the rise of suspension shares among those student groups. 67 Unexpected Demographic Change in California The literature that informed the central questions of this analysis found abundant evidence for patterns of rapidly growing proportions of Black and Latinx students in suburban schools nationwide. However, this study’s context differed from previous research on suburban demographic change in its specificity of location and its analysis of population trends within the past ten years. I found that in contrast to the nationwide trends reported for the period between 2000 and 2010, enrollment in public schools is declining statewide in California, though at a slower rate in the suburbs than in cities. Indeed, the broader population of the state has declined between 2018 and the present day the first time in history (Hussar, 2018). While I expected to observe universal growth in shares of students of color in suburban California schools, I argue that the current trends in suburban student enrollment require the same examination. Student enrollment in suburban public schools is decreasing, and the majority of students exiting these schools are White students. Meanwhile, Latinx student enrollment has remained stable. The changes that occurred in suburban schools, therefore, are less about an influx of students of color, and more about White disenrollment. As White students leave suburban schools, students of color increasingly make up the majority of children served, which results in the same cultural transformation described in previous studies. The population of White students made up a third of California’s suburban students at the beginning of the study, dropped to 23% in 2018. Perhaps more revealing, 86% of suburban California schools experienced a decrease in the share of White students enrolled over the study period. Assuming that historically, suburban schools were predominantly White, 86% of California’s suburban schools experienced some amount of ethnic, cultural, academic, or 68 linguistic transition between 2011 and 2018. The foundational inquiry of this study therefore remains: With respect to student discipline, how are educators responding to changing schools? While trends in California’s suburban demographic change may depart from nationwide patterns, this study’s findings are relevant to other states and the country as a whole. California has served as an innovator in progressive school discipline; the rate of student suspension has dropped considerably over the past decade. This is due in part to statewide restrictions on willful defiance suspensions and, in some districts, the implementation of alternatives to exclusionary discipline. Still, the racial discipline gap remains a problem in California, and is greatest, this study finds, in suburban schools with rising shares of students of color. If national enrollment trends have remained consistent since the publication of research on suburban demographic change, schools in many other states are managing an analogous change their historical populations and an increase in students with different needs and backgrounds. School Change and the Mythos of the American Suburb American suburbs in general, and suburban schools in particular, were created in large part with the intention of separating White families from families of color in order to consolidate opportunity and resources. Suburban schools have therefore developed a reputation as blanketly better—higher achieving, safer, and capable of providing students with an advantage in their future academic and professional pursuits. As the literature suggests, White flight in the mid- twentieth century, along with redlining, restrictive covenants, and other policy tools, laid the groundwork for the suburban demographic composition that would remain consistent through the 1990’s. Housing developers and popular media reinforced ideas about suburbia in the American imagination as idyllic havens with a specific culture built on homogeneity and, implicitly or otherwise, exclusivity. 69 The concurrent trends of urban gentrification and suburban demographic change, therefore, are a disruption of the cultural status quo. As some White families leave suburbs and some families of color move in, historical assumptions of suburban culture and identity are challenged. Qualitative research has captured the suspicion, reluctance to accept change, and fear of chaos that some educators feel as the racial and socioeconomic makeup of their student population transforms. Likewise, studies on parents’ perception of the racial makeup of schools suggests that many White parents feel comfortable enrolling their children in schools only when there is a critical mass of families from similar backgrounds doing the same. White parents’ preference to be among the racial majority is related to the desire to maintain control of school and the opportunities afforded to their children. Just as White entitlement to power over suburban culture and access to suburban schools is embedded in American culture, Black or Latinx presence is often portrayed as threatening. Exemplified by the perpetuation of the “super predator” myth in the 1990’s, young people of color are often associated with criminality. The association between Black and Latinx criminality is supported by the descriptive data in this study among suburban elementary schools in particular. While 88% of suburban elementary schools in the Black sample employed a full-time police officer, 84% of schools in the White sample had police on staff. Likewise, 53% of schools in the Black elementary sample were classified as persistently exclusionary, in contrast to just 32% of schools in the White elementary sample. Middle and high schools, too, had higher rates of persistent exclusion among the Black and Latinx samples, which suggests that zero-tolerance policies are more prevalent among schools that serve primarily students of color. While the model in this study is not capable of capturing the effect of police presence and much of the impact of zero-tolerance policies on student discipline, their relatively low usage in schools that 70 primary serve White students signals that the behavior Black and Latinx students is more likely to require punitive or legal intervention. In addition to the portrayal of Black and Latinx students as criminally threatening, the literature suggests that students of color may be perceived as threatening to White students’ access to resources and opportunity. The descriptive findings in this study lend support to this idea. There was a clear disparity in resources between the Black, Latinx, and White samples in the study. Schools in the White samples across all grade levels had the lowest teacher-to-student ratios. Similarly, schools in the Black and Latinx samples had fewer counselors and psychologists per student than did schools in the White samples. In the context of previous literature that describes opportunity hoarding among suburban parents, it is plausible that parents in predominantly White schools would seek to protect exclusive access to these advantages. As previously discussed, some White parents’ expectations of opportunity and resources contributes to their seeking a critical mass of similar families to maintain preferential status in schools. American suburbs in general have been characterized historically by White exclusivity, opportunity hoarding, and protection from perceived criminal behavior. Integrating the theoretical framework with this historical backdrop aids in the interpretation of the study’s empirical findings. Considering Technical, Normative, and Political Responses to Racial Change and School Discipline The empirical findings in this study suggest a strong relationship between suburban schools that experienced an increase in proportions of Black and Latinx students, and rising rates of disproportionate suspension of those students. Considering the negative impact of suspension 71 on students’ lifelong outcomes, and the concerted policy efforts to address this racial discipline gap, the findings are disconcerting. Concrete policy decisions sometimes exert lasting and meaningful change. For example, the share of Latinx elementary students suspended decreased as the number of teachers per student increased in this study. However, as argued in the theory, technical approaches are often insufficient when not supported with intentional efforts to address the normative and political aspects of racial equity in schools. The results of the study offer some clues as to the sources of normative and political influence on demographic change and student discipline in Suburban California schools. For example, normative assumptions about student achievement among educators and parents may inhibit efforts to address the source of behavior problems. In this case, the model estimates a relationship between schools with higher average English Language achievement and greater changes in the disproportionate suspension of Black middle school students. Higher rates of Black student suspension in schools with a culture of academic superiority may indicate the tendency of educators to readily exclude Black students rather than using resources to meet their needs out of pressure from parents and administrators to focus solely on student achievement. Conversely, the influence of normative factors may have contributed to the improvement in Latinx middle and high school suspension rates. The findings suggest that schools with higher proportions of English Language Learners had lower rates of Latinx students suspended over time. One potential explanation for this relationship is the level of experience and understanding among educators in schools with high shares of ELLs. If schools have served large numbers of Latinx students, and ELLs in particular, as the norm for years, it is likely that teachers received training to address the specific needs and strengths of these students. Teachers’ assumptions 72 about student behaviors and abilities may have evolved as the Latinx student population came to make up a large proportion of a schools’ student body. On the other hand, unaddressed normative challenges may also explain the relationship between suspension share change and persistently exclusionary schools within the elementary Black school sample. While all samples contained a substantive number of persistently exclusionary schools, a statistically significant relationship was only predicted for Black elementary schools. This may be attributable to teachers’ beliefs about the efficacy of suspensions for curtailing misbehavior, or to assumptions about the severity of Black students’ behavior compared to other students. Despite a 2014 law that banned willful defiance suspensions for students in grades K-3, the share of Black elementary students suspended increased between 2011 and 2018. Therefore, the technical response to school discipline was insufficient in addressing the racial discipline gap among Black students, suggesting that normative or political factors have some influence on teachers’ disciplinary decisions. Political responses to student discipline may have also played a role in the increase in suspension shares among Black elementary students in persistently exclusionary schools. As school enrollment declines statewide in California, schools compete for students to maintain sufficient levels of funding. Based on the literature that suggests that White parents choose schools they perceive as safe, and in which they can exert political influence, schools and districts may feel pressure to use zero-tolerance policies to communicate a culture of order. Prior studies have found that zero-tolerance policies have a disproportionate impact on Black students, which could explain, in part, the rise in suspension share among Black elementary students in persistently exclusionary schools. 73 Political factors may have contributed to the overall rise in Black and Latinx suspension share in schools with increasing proportions of students of color. As suggested in the literature, White families are often valued as elite members of a school community. Administrators may therefore be incentivized to comply with any opposition White parents may have to the policies that would support students of color. The literature argues that the elite have an interest in obstructing potentially supportive policies that would threaten their own status or their children’s share of opportunity. Prior studies have document White parents’ resistance to racial integration efforts, and their involvement in drawing catchment boundaries that exclude undesirable neighborhoods. Suburban Black students are concentrated in relatively few schools statewide. It is within reason, then, that racial tension and the relative power of White residents to influence integration and zoning policy, may contribute to the exclusion of, or disproportionate punishment of Black students in suburban schools. Heterogeneity: Context Matters While the findings about rising suspension rates in schools with increasing shares of Black and Latinx students were consistent across all samples, each sample had a unique constellation of other statistically significant explanatory variables. It is therefore evident that student race and grade level matters a great deal with respect to demographic change and discipline practices in suburban schools. Given the wide variety of suburban school types, it is also likely that the outcome in this study varies based on the geographic location, history, and cultural context of particular schools. Student discipline and responses to demographic change likely vary between schools, districts, even states. As discussed, enrollment trends in suburban California diverge from nationwide findings. Likewise, because of the decentralized nature of the American educational 74 system, policy varies at all levels of government. Normative beliefs about race and discipline certainly depend on geographic and cultural background, and sources of political influence are particular to each school’s context. Thus, this study’s contribution is an analysis of discipline trends among changing suburban schools in one state. It is my hope that it provokes curiosity and encourages further study of the subject in a variety of other contexts so that a deeper understanding of the relationship between race and school discipline can inform context-specific policy and address the obstacles to equitable school discipline practices. Limitations The analysis of the research questions was restricted by several limitations. First, the data available was school-level, which limited the degree to which the study could address questions of within-school variation in both segregation and school discipline practices. Student- or classroom-level data would also allow further exploration of the relationship between teacher- student racial incongruity and racial disproportionality in suspension rates. Further, while much of the literature on demographic change in suburban schools documented major population shifts between 2000 and 2010, this sample was restricted to the years between 2011 and 2018. School discipline data has been collected systematically since 2011, but no reliable data exists for previous years. A long-term analysis of discipline patterns, along with the document population trends in suburbs would have been beneficial to the analysis, particularly because of the migration prompted by the global recession in the years immediately after 2008. Finally, information distinguishing suburban types from one another was unavailable, as were the simple urbanicity variables in many observations in the Common Core Data. Because 75 suburbs vary widely in culture, history, and economic context, the analysis presented here provides a somewhat oversimplified view of suburban change and school discipline. Implications for Policy The overarching implication for policymakers seeking to address racially inequitable school discipline in changing suburbs is that policy alone is insufficient. While technical approaches to ameliorating inequality in school discipline are an essential component of change, attendance to the more challenging normative and political factors that obstruct the implementation of well-crafted policy is a prerequisite to their success. Normative change requires that educators challenge underlying biases and assumptions that inform their responses to the presence and behavior of students of color. This work can begin with strong leadership committed to reshaping school culture with respect to race and discipline. Because this specific skill set and genuine commitment may vary among leaders at the school and district level, the findings in this study suggest the development of county, state, or even federal professional development courses, as well as incentives for implementing these trainings with fidelity. Toward the goal of common cultural understanding, the recruitment of racially diverse teachers is also advisable. Teachers of color are less likely to suspend students of color for minor misbehaviors, and may have more experience with considering students’ varying backgrounds than White educators, who have likely lived as members of the dominant cultural group. The racial and ethnic makeup of teachers in California has grown more diverse in recent years. However, concerted effort to hire teachers that are representative of the students they serve would expedite this process, and alternate certification programs, grow-your-own initiatives are methods that policymakers and school leaders should consider employing. 76 Future Research The findings and limitations of this study reveal several areas of research that will contribute to a more developed body of literature on demographic change and school discipline. First, a replication of this study in the context of urban and rural schools is warranted. The findings on racially disproportionate school discipline in changing suburban schools will be enhanced by an analysis of the same relationship in locales with substantially different normative and political influences. Second, the literature suggests that teacher-student racial incongruity contributes to adverse student outcomes. Likewise, other studies have documented the variation in discipline practices within schools, in addition to between schools. Future studies should consider using student- or classroom-level data and employ a multilevel model to determine a potential relationship between teacher-student racial match, within-school variation in the use of exclusionary discipline, and the between-school variation examined in this study. Third, based on the more detailed suburban typology described in the literature, future research should consider coding schools or districts with these new definitions. Such a study would provide a more thorough understanding of the types of suburban schools most likely to struggle to integrate new student populations, and which are most successful in using discipline equitably and minimally. Fourth, given the 2014 implementation of the ban on suspensions for disruption/defiance in K-3 classrooms in California, future research should attempt to isolate the impact of the law on racially disproportionate school discipline in elementary schools. Prior research has suggested that students of color are disciplined more harshly for low-level infractions. Therefore, an 77 examination of infraction type, combined with an analysis of suspension trends pre- and post- policy intervention would provide an update the scholarship on such findings. Finally, future studies should examine the relationship between suburban demographic change and exclusionary discipline in other states, and perhaps nationwide. Much of the literature that documents the influx of racial minorities to the suburbs was published nearly a decade ago, and enrollment trends in California are no longer wholly consistent with the trends previously described. Likewise, due to the high cost of living and overall decline in population growth, California may be anomalous when compared to suburbs in other parts of the country. Perhaps most pressing is the need for studies on suburban change and school discipline that are up-to-date and more geographically broad in scope. This study precedes the recent prominence of the Black Lives Matter protests, the emergence of overt, organized White supremacy efforts such as the January 6 attack on the United States Capital, and the disruption and tragedy of the global pandemic. Like the White Flight in the wake of Brown v. Board, and the abruptly changing cultural landscape in the 1960’s and 1970’s, the events of 2020 and 2021 will likely have a dramatic and lasting impact on American Schools. It is likely that urban and suburban residential patterns, collective and individual racial bias, and policy efforts to address systemic inequities will transform many aspects of central questions addressed in this study. The examination of race, discipline, change, and equity in schools should therefore be an ongoing effort. 78 APPENDIX 79 APPENDIX Table 13: Suburban, Urban, and Total Enrollment by Race, by Year Average Total Average Total % Change Enrollment 2011-13 Enrollment 2016-18 Suburban Black 106,420 84,064 -21% Latinx 773,893 770,717 0% White 395,257 333,771 -16% Total 1,483,549 1,418,785 -4% Urban Black 149,352 114,846 -23% Latinx 918,221 880,479 -4% White 341,692 295,883 -13% Total 1,730,634 1,619,841 -6% Total Black 293,599 231,451 -21% Latinx 1,943,879 1,917,733 -1% White 909,966 779,307 -14% Total 3,758,584 3,579,681 -5% 80 Table 14: Full Regression Results, Black Elementary School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change change change suspchange -3.7** -3.6*** -4.5*** -4.3*** -5.4** -7.1*** -7.3*** (.78) (.78) (1.09) (1.11) (1.79) (2.11) (2.12) increase 7.68** 7.43** 7.52** 7.35** 7.21** 8.24** 7.95*** * (1.655) * (1.656) * (1.656) * (1.682) * (1.693) * (1.902) (1.926) enrshare .029 .024 .034 .035 .054 .032 (.035) (.035) (.039) (.039) (.055) (.059) exclusion 1.724 2.019 2.046 3.318* 3.303* (1.387) (1.506) (1.507) (1.803) (1.804) ela -.112 -.11 -.113 -.121 (.102) (.102) (.12) (.121) math .134 .137 .127 .135 (.096) (.096) (.11) (.11) police 1.425 1.964 2.112 (1.798) (2.033) (2.039) teachratio .035 .071 (.239) (.242) sprtratio .001 .001 (.001) (.001) schoolsize .192 .191 (.407) (.407) percELL -.024 -.019 (.054) (.054) percFRL -.052 -.052 (.06) (.06) increase*enrshare .093 (.098) Observations 536 535 535 529 529 434 434 R-squared .039 .039 .042 .044 .045 .062 .064 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 81 Table 15: Full Regression Results, Black Middle School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change chang change e suspchange -2.8*** -2.7*** -2.5*** -2.6*** -2.1* -2.9* -2.9* (.582) (.5) (.81) (.80) (1.18) (1.51) (1.51) increase 6.68** 7.13*** 7.27*** 7.42*** 7.51** 7.2** 7.2*** (2.076) (2.05) (2.08) (2.04) (2.05) * (2.11) (2.32) enrshare .062** .064** .083** .08** .043 .043 (.028) (.029) (.034) (.034) (.044) (.044) exclusion -.607 -.056 -.052 -.663 -.676 (1.126) (1.166) (1.169) (1.233 (1.243) ela .24*** .23*** ) .24** .24*** (.078) (.078) * (.087) (.087) math -.159* -.162* -.135 -.136 (.084) (.084) (.089) (.09) police -.733 -.262 -.27 (1.264) (1.349 (1.356) teachratio ) .174 .174 (.173) (.174) sprtratio .001 .001 (.001) (.001) schoolsize -.009 -.006 (.258) (.26) percELL -.075 -.075 (.045) (.046) percFRL .061 .061 (.055) (.055) increase*enrshare -.014 (.129) Observations 140 140 140 140 140 136 136 R-squared .07 .102 .104 .166 .168 .208 .209 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 82 Table 16: Full Regression Results, Black High School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change change change suspchange -4.2*** -4.3*** -2.6 -2.2* -1.65 -11.1*** -11.7*** (1.55) (1.59) (2.37) (1.348 (1.69) (4.15) (4.24) increase 7.01 7.34* 7.0 ) 6.5** 6.4** 7.9*** 7.9*** (4.24) (4.40) (4.41) (2.56) (2.57) (2.29) (2.30) enrshare -.013 -.001 .042 .04 -.063 -.082 (.069) (.07) (.044) (.045) (.051) (.056) exclusion -2.81 -1.36 -1.59 -1.23 -1.11 (2.99) (1.84) (1.85) (1.67) (1.68) ela -.014 -.019 -.09 -.075 (.072) (.073) (.07) (.072) math .052 .051 .12 .095 (.105) (.106) (.104) (.109) police -1.139 -.917 -.902 (1.763 (1.676) (1.679) teachratio ) .15 .158 (.098) (.098) sprtratio -.015** -.016** (.007) (.007) schoolsize .28** .30*** (.11) (.113) percELL .01 .011 (.038) (.038) percFRL .146** .146** (.056) (.056) increase*enrshare .081 (.102) Observations 120 119 119 108 108 102 102 R-squared .023 .024 .031 .077 .081 .243 .248 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 83 Table 17: Full Regression Results, Latinx Elementary School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change change change suspchange -4.8*** -4.7*** -5.3*** -3.9*** -3.9** -1.7 -1.7 (1.14) (1.15) (1.22) (1.26) (1.89) (2.17) (2.17) increase 8.8*** 8.8*** 8.6*** 7.8*** 7.8*** 8.3*** 8.2*** (1.327) (1.334) (1.339) (1.344) (1.345) (1.525) (1.53) enrshare .011 .002 -.041 -.041 -.085* -.062 (.025) (.025) (.03) (.03) (.044) (.064) exclusion 1.902 .528 .528 -.724 -.726 (1.226) (1.317) (1.317) (1.49) (1.491) ela -.071 -.071 -.068 -.064 (.084) (.084) (.096) (.096) math -.028 -.028 -.017 -.019 (.08) (.08) (.088) (.089) police -.052 -1.516 -1.518 (1.618) (1.808) (1.809) teachratio -.39** -.39** (.193) (.193) sprtratio 0 0 (.001) (.001) schoolsize .338 .338 (.342) (.343) percELL -.02 -.021 (.038) (.038) percFRL .062 .062 (.049) (.049) increase*enrshare -.031 (.062) Observations 1440 1429 1429 1410 1410 1156 1156 R-squared .03 .029 .031 .033 .033 .042 .042 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 84 Table 18: Full Regression Results, Latinx Middle School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change change change suspchange -4.8*** -3.92** -4.1*** -4.3*** -3.8** -3.4* -3.5* (1.41) (1.36) (1.42) (1.33) (1.73) (1.89) (1.91) increase 6.50*** 5.56*** 5.52*** 5.69*** 5.67*** 4.95*** 4.96*** (1.55) (1.48) (1.48) (1.38) (1.38) (1.45) (1.48) enrshare -.036 -.039 -.017 -.018 -.006 -.008 (.024) (.026) (.029) (.029) (.036) (.06) exclusion .468 1.279 1.278 1.009 1.009 (1.201) (1.184) (1.185) (1.249) (1.251) ela .027 .028 -.008 -.009 (.07) (.07) (.077) (.079) math .003 .002 .006 .006 (.067) (.068) (.069) (.07) police -.555 -.224 -.226 (1.285) (1.336) (1.338) teachratio -.239 -.238 (.167) (.171) sprtratio 0 0 (.001) (.001) schoolsize -.12 -.121 (.189) (.19) percELL -.073* -.073* (.041) (.041) percFRL -.025 -.025 (.044) (.044) increase*enrshare .003 (.06) Observations 346 340 340 336 336 325 325 R-squared .048 .045 .046 .056 .056 .067 .067 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 85 Table 19: Full Regression Results, Latinx High School Sample (1) (2) (3) (4) (5) (6) (7) susp susp susp susp susp susp susp change change change change change change change suspchange -6.9*** -6.02** -5.33** -1.68 -1.36 3.13 3.15 (2.29) (2.39) (2.51) (2.28) (2.43) (4.96) (4.99) increase 10.8*** 9.83*** 9.85*** 5.36** 5.43** 4.85** 4.82** (2.498) (2.591) (2.592) (2.382) (2.394) (2.261) (2.403) enrshare -.019 -.015 -.043 -.046 -.052 -.05 (.04) (.04) (.041) (.042) (.049) (.094) exclusion -1.787 -1.513 -1.609 -3.27* -3.267* (1.89) (1.922) (1.94) (1.729) (1.735) ela .069 .066 .109 .109 (.07) (.071) (.07) (.07) math -.184** -.186** -.29*** -.29*** (.091) (.092) (.086) (.086) police -.685 .62 .622 (1.721) (1.607) (1.613) teachratio -.042 -.042 (.115) (.115) sprtratio .007 .007 (.008) (.008) schoolsize -.105 -.105 (.113) (.113) percELL -.082** -.082** (.037) (.037) percFRL .032 .031 (.057) (.057) increase*enrshare -.003 (.091) Observations 257 250 250 231 231 221 221 R-squared 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