Spatial othering: Examining residential areas, school attendance zones, and school discipline in an urbanizing school district Journal website: http://epaa.asu.edu/ojs/ Manuscript received: 10/31/2019 Facebook: /EPAAA Revisions received: 3/5/2020 Twitter: @epaa_aape Accepted: 3/6/2020 education policy analysis archives A peer-reviewed, independent, open access, multilingual journal Arizona State University Volume 28 Number 91 June 15, 2020 ISSN 1068-2341 Spatial Othering: Examining Residential Areas, School Attendance Zones, and School Discipline in an Urbanizing School District Dian Mawene & Aydin Bal University of Wisconsin-Madison United States Citation: Mawene, D., & Bal, A. (2020). Spatial othering: Examining residential areas, school attendance zones, and school discipline in an urbanizing school district. Education Policy Analysis Archives, 28(91). https://doi.org/10.14507/epaa.28.4676 Abstract: Drawn from interdisciplinary perspectives of special education, critical geography, and education policy, in this study, we examined the spatial patterns of residential areas, school attendance zones, and school discipline rates of an urbanizing school district in Wisconsin to understand the construction of spatial “Other.” We measured the city’s dissimilarity index to examine racial and economic segregation between neighborhoods and elementary schools. We also measured the school district suspension rates to examine racial disproportionality in school discipline. We then analyzed to what extent the redrawing of elementary school attendance zones in the 2007-2008 school year was able to reduce the spatial concentration of racially and economically minoritized students in one elementary public school. We found that despite the well -intentioned efforts of the rezoning committee to lower the percentage of students from low-income families, spatial othering at the neighborhood level continued to funnel students from racially and minoritized backgrounds into the school, due to the concentration of low - http://epaa.asu.edu/ojs/ https://doi.org/10.14507/epaa.28.4676 Education Policy Analysis Archives Vol. 28 No. 91 2 income housing in the neighborhood of the school. Keywords: racial disproportionality; school attendance rezoning; school discipline; critical geography; index of dissimilarity; education policy; spatial other; spatial othering; othering; space 'Otrando' espacialmente: Examinando zonas residenciales, zonas de las escuelas, y la disciplina escolar en un distrito escolar en el progreso de urbanizarse Resumen: Basándose en perspectivas interdisciplinarias de la educación espacial, la geografía crítica, y la política educativa, en este estudio examinamos configuraciones espaciles de zonas residenciales, las zonas de asistencia a la escuela, y tazas de disciplina en las escuelas de un distrito escolar en el proceso de urbanización en Wisconsin para entender la construcción del “Otro” espacial. Medimos el índice de desemejanza de la ciudad para examinar la segregación racial y económica entre barrios y escuelas primarias. También medimos tazas de suspensión para examinar desproporciones en la disciplina de la escuela. Luego analizamos hasta qué punto la redistribución de zonas de asistencia de la escuela primaria en el año escolar 2007-8 era capaz de reducir la concentración especial de estudiantes marginalizados racialmente o económicamente en una escuela primaria pública. Encontramos que a pesar de los bien intencionados esfuerzos por parte del comité de recalicación para reducir el porcentaje de estudiantes de familias de bajos ingresos, ‘otrando’ espacialmente al nivel del barrio continuaba enviandoles a estudiantes de entornos racialmente marginalizados a la escuela, debido a la densidad de viviendas para personas de bajos recursos. Palabras-clave: desproporcionalidad racial; recalicación por asistencia a las escuelas; disciplina escolar; geografía crítica; índice de desemejanza; política educativa; otro especial; ‘otrando’; espacio Alteridade espacial: A análise de áreas residencias, regiões escolares, e disciplina escolar em um distrito escolar em processo de urbanização Resumo: A partir de uma perspectiva interdisciplinar da educação especial, geografia crítica e política da educação, este estudo investigou arranjos espaciais de áreas residencias, regiões escolares, e índices de disciplina escolar de uma cidade de Wisconsin em processo de urbanização para compreender a produção de alteridade espacial. O índice de dissimilaridade da cidade foi mensurado para examinar segregação racial e econômica entre bairros e escolas de ensino fundamental. Analisamos desproporcionalidade racial em suspensões escolares no distrito escolar da cidade. Em seguida, analisamos até que ponto a redemarcação das regiões escolares de ensino fundamental no ano escolar de 2007-2008 foi capaz de reduzir a concentração espacial de alunos das minorias raciais e econômicas em uma escola pública de ensino fundamental. Nossa análise revela que apesar de esforços do comitê de redemarcação em reduzir a porcentagem de alunos de baixa-renda, produção de alteridade espacial no bairro continuou a afluir alunos das minorias para uma escola devido a concentração de moradias populares nos arredores desta. Palavras-chave: desproporcionalidade racial; política da educação; disciplina escolar; redemarcação de regiões escolares; geografia crítica; índice de dissimilaridade; espaço; alteridade espacial Spatial Othering 3 Spatial Othering: Examining Residential Areas, School Attendance Zones, and School Discipline in an Urbanizing School District Racial disproportionality in special education and school discipline is a complex and persistent educational problem (Artiles, Kozleski, Trent, Osher, & Ortiz, 2010; Children’s Defense Funds, 1975; Gage, Whitford, Katsiyannis, Adams, & Jasper, 2019; Harry & Klingner, 2006; Skiba et al., 2008). It is situated in a complex nexus of larger structural forces beyond schools, such as funding, student assignment policy, the education market, and the housing market. These structural forces are deeply engrained in historically racialized systems and tools such as discriminatory mortgages (e.g., redlining), racially divided neighborhoods, and public-school funding based on property tax. Such forces are inextricably interwoven with disparities in economic investments and maldistribution of educational resources such as funding, robust curricula, and qualified teachers (Tate, 2008). This study investigates these structural forces of racial disproportionality in special education and school discipline and their impact on minoritized students. The complexity of racial disproportionality is evident in decades of studies that have continuously captured the overrepresentation of African American, Latinx, and Native American students in school disciplinary actions (Children’s Defense Funds, 1975; Gage et al., 2019; Losen, 2018; Skiba et al, 2011). Students from racially minoritized communities receive disciplinary punishment more frequently for subjective reasons such as dress code violation, insubordination, and disrespect compared to their White peers (Skiba et al., 2011). Minoritized students are also disproportionally represented in special education placement, particularly for high incidence disability categories such as emotional/behavioral disturbance (E/BD), specific learning disability (SLD), and intellectual disability (ID; Dunn, 1968; U.S. Department of Education, 2018). Racial disproportionality has detrimental impacts on students because it further marginalizes minoritized students and exacerbates behavioral problems. It may cause the students to lose instruction time, stigmatize students as inferior, set lower expectations, eventually cause students to drop out of school, and involve in the juvenile justice system (Donovan & Cross, 2002; Losen, 2018; Skiba et al., 2011). Racial disproportionality becomes even more complex and consequential in demographically changing communities that are highly segregated, such as rural communities and urbanizing cities. In such racialized spaces, disproportionality has material root causes and significant social and structural consequences. Kramarczuk Voulgarides (2018), for instance, documented such racialized spaces and structural consequences. In her study, two of the three schools cited for racial disproportionality are located in deeply segregated neighborhoods. The author identified institutional biases through spatial and social arrangements of a locality that is arranged and fragmented based on color lines, often delimited by “natural” dividers such as a street or a highway. Such racial divisions are then materialized through educational services to minoritized students living in the school districts. That is, students of color in the overwhelmingly White and affluent community received sub-standard educational services and interventions and were often subject to negative stigma that had an impact on staff-student interactions. The structure of the community made segregation seem to be such a natural part of everyday life that people, including local education agencies and practitioners in those schools, were not bothered by its detrimental effects. Educators and school and district leadership extended the “naturalness” of this structural segregation through adhering to race-neutral principles when examining and addressing racial disproportionality, which affected the educational opportunities of the minoritized students (Kramarczuk Voulgarides, 2018). In an ethnographic study from two high schools and a prison, Casella (2003) depicted similar racialized school disciplinary practices at structural and interactional levels. Casella concluded that Education Policy Analysis Archives Vol. 28 No. 91 4 the school, which was overwhelmingly African American and Latinx, utilized disciplinary exclusions as preemptive actions, resulting from the negative stigma and perceptions of school practitioners. Students who were suspended or at risk of being suspended were excluded from the school without the presence of objective dangerous or disruptive behaviors but simply because of assumptions from adults in authority. Racial disproportionality requires a multifaceted and situated understanding at the intersection of social, historical, and spatial factors (Bal, 2017). Only a few empirical studies have examined the contextual factors concurrently. Artiles (2003), Tefera, Aguilar, Artiles, Kramarczuk Voulgarides, and Velez (2017), and Waitoller and Annamma (2017) have provided theoretical foundations to probe into issues of racial disproportionality concurrent with social, historical, and spatial structures of the communities where schools are located. However, there is a paucity of empirical studies that investigate how structural issues such as school attendance zones and neighborhood compositions function as a pipeline to racialization in school discipline. The present study addresses this limitation. Informed by critical geography, we aim to unpack structural forces of racial disproportionality in school discipline that exist in the larger society and play crucial roles in creating systemic disparities in educational opportunities and outcomes that impacts the learning and development of minoritized students. We concurrently examined three units of analysis: residential patterns, school attendance zones, and school discipline. In the following section, we provide an explanation of the conceptual framework guiding this study. We focus on the significance of space as an ontology in understanding racial disproportionality, while also introducing the concept of “spatial Other.” Conceptual Framework In this study we conceptualize racial disproportionality not as an individual problem in the body and mind of students or teachers, but as a systemic and contextual issue mediated by social, historical, and spatial factors. This study is concerned with minoritized students who disproportionately receive disciplinary actions, but it does not take those students as the sole unit of analysis. Rather, the unit of analysis of the present study is the spatial, temporal, and societal contexts through which disproportionality is re-produced in everyday practices of individuals and institutions. The Spatial Turn in Understanding Racial Disproportionality Drawing from multidisciplinary perspectives of special education, education policy, and geography, this study is centered around critical geography to examine racial disproportionality. The notion of critical geography in this study transcends the dominant conceptualization of space in classical geography as a mere container of human actions. Rather, in critical geography, space refers to a mental and physical realm of everyday life that is filled with ideology and power (Lefebvre, 1991; Soja, 2010). Critical geography focuses on socio-spatial relationships and processes that re- produce inequality (Hubbard, Kitchin, Bartley, & Fuller, 2002). Critical considerations of space should be utilized to understand potential root causes of complex, adaptive and situated inequities in educational opportunities and outcomes such as racial disproportionality. Critical spatial analysis requires a paradigm shift regarding human-context relationship: “Human and context are not discrete entities, but they are interwoven on a continuum—human- context—in which activities as forces affect human-context and in turn are affected by it. Power is a property of human-context geometry. Out of the activities comes power. The structure of human context is curved by the distribution of power not unlike gravity in space-time. As a result, human- context warps and expands incessantly.” (Bal, 2016, p. 423). Therefore, a critical spatial analysis of Spatial Othering 5 racial disproportionality includes the social and historical dimensions of a space, and also simultaneously examines race, class, disability, and other factors with social significance. In this this study, we used critical geography to understand the structures through which minoritized families and students are “spatially othered”—that is, systemically concentrated in physical and social isolation from the rest of the community. We also aimed to understand the extent to which social control takes place in and through regulated spaces (e.g., administrative boundaries, land use, self- contained special education classrooms, and detention rooms; Soja, 2010). Spatial othering. The concept of the Other has been used to identify students who are historically marginalized in society based on race, class, gender, language, and immigration status (Borrero, Yeh, Cruz, & Suda, 2012; Kumashiro, 2000). Othering is the discursive process of (re)defining the Other, through which a dominant in-group (“Us”, the self) defines out-groups (“them”, the Other) and stigmatizes a difference that is presented as a negation of identity and thus a motive for potential discrimination (Staszak, 2009). Therefore, othering is an iterative process of doing rather than being (Butler, 1993), by which certain differences such as race, class, language, behaviors, and the norms of minoritized groups are made visible and consequential (Bal, 2017). Geography is an effective manifestation of Otherness (Staszak, 2009). The way space is organized carries a great deal of information about human relationships. In this study, we define a spatial Other as any group of people who, because of diverging social substances in language, race, class, income, or behavior that do not fit the model of the majority of a community, are placed in a physical location, enclave an “island” separated from the rest of the community. Space becomes both a tool and a materialization of otherness. The projects, public housing in the South side of Chicago, for example, are not only spaces, they embody and establish mental images of what these places are and represent vis-à-vis the rest of the city. In other words, humans (re)produce space and in turn space produces images about humans. Space is a product as well as the process itself (Lefebvre, 1991). Images of the Other and the place they occupy work together to form socio-spatial landscapes of exclusion (Sibley, 1995). Engaging with the spatial structures of an urbanizing city and its school district in this study is to understand how the community (re)constructs a racialized Other and materializes and maintains the (re)construction through multiple scales of spatial exclusions. Spatial othering at the school and neighborhood levels reinforce each other and are interconnected by design (García, 2018). Examining spatial othering connects structural forces that exist within and beyond the walls of the school and play significant roles in creating certain differences as deficits through institutionalized acts of inclusion/exclusion. Residential areas, school attendance zones, and school disciplinary actions in and of themselves create regulated spaces and serve as sites of social control (Soja, 2010). Studying racial disproportionality through policy studies and critical geography provides ample room to explore structural forces such as the spatial organization of a locality that have shaped material and ideal cultural tools, norms, and rules in a community. The majority of public schools in the US traditionally assign students to attend schools based on residential locations (Richards & Stroub, 2015; Wang, Rathbun & Musu, 2019). School attendance boundaries (e.g., maps of distance, location, and terrain) are drawn based on neighborhoods. The drawing of school attendance boundaries is the key to perpetuating or altering the status quo. School attendance boundaries may trap the children of parents who cannot afford to live in a perceived good neighborhood and therefore remain stuck in impoverished neighborhood schools. The boundaries have substantial and different meanings to many people, ranging from families to the local school district and to real estate agencies. To some families, new attendance zones could signify who their children associate with or what kinds of educational opportunities they might get in the new school. The drawing of school attendance zones also affects the distribution of Education Policy Analysis Archives Vol. 28 No. 91 6 school funding, which comes from property taxes. Therefore, a change in attendance zones might bring a challenge to the local school district in handling the distribution of resources. Lastly, changes in attendance zones impact values of the properties assigned to the new school. Therefore, studies about space cannot be limited only to aspects of mapped distance. Space is not a void but is filled with social drama, ideology, and power: it is nuanced (Soja, 2010). Context: Critical Socio-Spatial-Historicity of Wells Wells1 is a demographically fast-growing urbanizing community in the state of Wisconsin. The city has changed from being a nearly all-White rural area to a growing mixed-racial suburban city. Between 2000 to 2010, the percentage of the White population in the city decreased from 92% to 85% (U.S. Census Bureau, n.d.). The city remains predominantly White and affluent. However, the number of low-income families tripled between 2000 and 2009, an increase from about 300 to 1000 families according to the city’s assessment report (City of Wells, 2011). Indeed, the 2009 comprehensive plan of the city recognized that one-third of the county’s total low-rent public housing placed in suburban areas are located in Wells. The rest of this section explains the socio-spatial and historical contexts of Wells including the enactment of two important policies reinforcing division of spatial arrangements. We proceed with history of racial discrimination of minoritized youth in Wells School District (WSD) as well as the politics of school attendance rezoning in the school district. Shifting Demographic and Spatial Arrangements In Wells, as in many other urbanizing areas, increasing racial and economic diversity means that the spatial arrangements of the city have gradually changed as well-off (and primarily White) residents avoid the old downtown area of Wells and as the city developments expand to the outer ring of the city constructing high-end housings away from the old downtown areas. Highway development opened up new housing subdivisions to the north, northwest, and eastside of the city and gradually divided the city to two physical and social parts: the new and the old Wells, or the affluent and less affluent (see Figure 1 for subdivision developments). As the housing market expands toward the new Wells, housing prices in older buildings of the old Wells declined. The old Wells progressed into a housing market catering to residents with lower income. The changing demographic make-up of old Wells caused business such as grocery stores, restaurants, and coffee shops to close or move to the new Wells, leaving the old Wells with minimal amenities. This resulted in an image of this area as less desirable for property investment and economic development. The old part of Wells has increasingly become dense with a hodge-podge of businesses such as fast food restaurants, construction offices, gas stations, and financial institutions, as well as low- income housing complexes and homeless shelters. This old Wells is where the majority of those living below the poverty line reside, with many from African American and Latinx backgrounds, and many single-mother families. Meanwhile, the new Wells is facilitated with high-end retail stores, restaurants, coffee shops, and entertainments. These facilities appear adjacent to but vigorously disconnected from old Wells. In addition, highways and arterial streets play a role as “natural” dividers of neighborhoods. The old Wells is bordered by a highway on the west and north sides and arterial streets on the south side. Transportation systems allow residents to access shopping centers in the northwest and east sides without ever passing through the central part of the city, leaving the area in isolation. 1 We used pseudonyms for all city and school names, including documents indicating name of places, to avoid deductive breaching of confidentiality of the people involved in the large study. Spatial Othering 7 Figure 1: Map of subdivision developments in Wells Data from the city of Wells (2018) Housing discrimination ordinance. In 2007, the city passed its housing discrimination ordinance that aimed to assure the housing rights of the “protected class.” While the aim of the ordinance is to ban housing discrimination, it simultaneously discriminates against those who rely on the federal housing choice voucher, also known as Section 8 voucher. The housing discrimination ordinance explicitly states that discrimination in housing practices is illegal when it is based on race, religion, sex, or national origin. However, it allows room for and even encourages the owners of rental properties to not rent to or control the number of Section 8 tenants. The ordinance also allows landlords to decline rental applications based on potential tenants’ criminal history, including instances of causing public nuisances as well as failures to provide government issued ID or social security information for the purpose of credit screening and criminal history information. Another discriminatory tool against those who utilize Section 8 housing vouchers is their exclusion from the definition of protected class. According to the city’s 2007 housing discrimination ordinance: “Protected Class” includes persons of a specific race, color, religion, ancestry, national origin, sex, handicap, sexual preference, marital status of person maintaining a household, lawful source of income, place of birth, age or other Federal or State designated protected classes for purposes of Fair Housing. Protected classes do not include persons with a criminal background (arrest or conviction record) related to safety or property offenses, persons who refuse to submit to a criminal background check or credit check, persons who refuse to produce a valid social security number or ITIN or persons who refuse to produce a federal or state government issued identification sufficient to confirm Education Policy Analysis Archives Vol. 28 No. 91 8 one’s identity, or persons utilizing Section 8 housing vouchers. (Wells, Wisconsin, Municipal Code 342, § 1, 11-6-2007) Based on this definition of protected class, people who are from low-income backgrounds utilizing Section 8 vouchers have no protections or rights if rental property owners decline their application on the basis of their Section 8 status. Although the definition of protected class includes persons with lawful sources of income, in the state of Wisconsin, Section 8 vouchers are not within the state’s definition of a lawful federal source of income (Knapp v. Eagle Property Management, 1995; State of Wisconsin Fair Housing Plan, n.d). Wells’s 2007 ordinance explicitly states that: No provision in this ordinance shall require owners or landlords to accept Section 8 housing vouchers except where required by state or federal law. For purposes of this ordinance the refusal of a landlord to accept Section 8 as a legal source of income and the denial of an application shall not be considered discriminatory. (Wells, Wisconsin, Municipal Code 342, § 1, 11-6-2007) The ordinance allows landlords to turn down any potential tenants participating in the federal government's housing choice program. Landlords have the right not to rent to low-income tenants relying on Section 8 vouchers as a source of income. While the ordinance brought changes in perspectives toward welcoming residents from minoritized gender identities, dis/abilities and ages, it remained exclusive of certain classes and potentially races. One of the (un)intended consequences of the ordinance is the concentration of people from low-income backgrounds, as those who use housing choice vouchers can only live in residential areas that cater toward residents with Section 8 vouchers. Given that the racial make-up of tenants living in the designated low-income rental areas is overwhelmingly African American, such spatial concentration evidently becomes racial concentration. Chronic nuisances ordinance. Along with the housing discrimination ordinance, the city also passed a chronic nuisance ordinance that holds landlords accountable for any nuisances caused by tenants in their rental property. This means that the landlord will be fined based on the number of times the police responds to the premises of the landlord. Such an ordinance directly or indirectly pushes landlords to screen any potential tenants and possibly avoid people who are stereotypically perceived as badly behaved in order to avoid the city’s sanctions. This ordinance pairs well with the housing discrimination ordinance in that both ordinances discourage rental management from renting to people from low-income and minority backgrounds—people who are Others. The screening of residents perceived as badly behaved implies a subjective construction of behavioral norms dominated by how the community, especially the long-term residents, imagine orderliness and propriety. While such an ordinance might be beneficial to ensure “everything is in place”, the chronic nuisance ordinance may have (un)intentionally provided a strong reason to block minoritized residents from moving into the city. A local newspaper reported several police calls pertaining to chronic nuisances coming from long-term residents living in single-family housing adjacent to apartment properties. By 2008, the fear of impropriety and growth led some city council members in 2008 to call for a moratorium to stop the development of apartment buildings in the city while still allowing the development of single-family housing on the west side of the city (the new Wells) to continue. Both the chronic nuisance and housing discrimination ordinances demonstrate that housing choice is an illusion for disfranchised residents in Wells. Freedom in choosing where to live does not really apply to people from low-income backgrounds or people who use Section 8 vouchers, as their income and possibly race have limited their options to the designated low-income housing only. The Spatial Othering 9 screening of badly-behaved residents became a social screening of who can live where (Lipsitz, 2011). Because racial discrimination is illegal, both the chronic nuisance and housing discrimination ordinances become new bases through which discrimination against those from low-income and racially minoritized backgrounds is acceptable. Minoritized Youth in Wells School District Changing residential demography changes the demography of a school’s student body, particularly by increasing the number of students from low-income and non-White backgrounds. In early 2006, a total of 19 % of students in WSD qualified for free and reduced-priced lunch (FRL) (Wisconsin Department of Public Instruction, n.d). In 2018, the percentage of students with FRL status increased to 32% (Wisconsin Department of Public Instruction [WDPI], n.d). The percentage of African American, Latinx, and Asian students was 11%, 4.5%, and 4.4% respectively in 2006. In 2018, the percentage increased to 9% for Latinx, 10% for Asian, and 8% for students identified as having two or more races. African American students were the only group whose percentage decreased, to 10% (WDPI, n.d). African American students in Wells have long experienced racial disparities in special education, particularly in the identification of E/BD, in discipline, and in academic achievement. In 2006, African American students made up 11% of the students enrolled in elementary schools (WDPI, n.d), but were 66 of the 405 students (16%) in special education (WDPI, n.d). Data further shows over-representation in the ED category. African American students were 14 of the 42 students (33%), identified as emotionally disturbed. In 2007, the ratio of African American students with ED label increased to 55% or 17 out of 31 students with E/BD. Racial overrepresentation in E/BD persists and in 2013 it captured federal attention through the Office of Civil Rights (OCR). In 2013, the OCR released a citation to WSD for racial discrimination against African American students, and the district remained under the scrutiny of the OCR until 2016. African American students made up only 10% of the total district population in 2013, yet they constituted one fourth of the total students in special education. That means that one out of four African American students had a risk of being placed in special education, particularly under subjective disability categories such as E/BD, SLD, ID, and Other Health Impairments, with the majority of the referral cases occurring at the elementary school level (WDPI, n.d.). African American students have also been overrepresented in school disciplinary actions in WSD. WDPI (n.d) reported that in 2006-2010, African American students were 13 to 17 times more likely to be suspended than their White counterparts in WSD. The consequences of discriminatory educational services are visible in African American students’ low academic achievement and low graduation rates compared to White students in the district. Data from the OCR highlighted that African American students in WSD cumulatively missed 483 school days due to out of school suspensions in 2015. This is more than twice the number of suspensions received by White students (210 days). Almost half of the number of instructional days missed by students of WSD are missed by African American students. In 20017-18 academic year the graduation rate for African American students is 82%. This means one in five African American students have a risk of dropping out. Politics of School Attendance Rezoning in Wells School District The city has been wrestling with a booming population and increasing racial and economic diversity. Growth has led to overcrowding in elementary schools and therefore a new school, Meadow Elementary School, was built in 2008. WSD utilizes the concept of traditional public schools that assign students to attend school based on residential areas. One benefit of neighborhood schools is how they avoid creating “islands” and disintegrating neighborhoods. However, neighborhood schools might also create disparities in educational opportunities as well as Education Policy Analysis Archives Vol. 28 No. 91 10 racial/ethnic and class segregation rooted in neighborhood compositions and the ways through which public schools are funded. Upon deciding on which neighborhoods are assigned to Meadow Elementary, the district had to redraw its boundaries for all elementary schools. The district faced the challenge of avoiding the unintentional creation of a spatial concentration of students who live in neighborhoods highly segregated by race and income. The rezoning committee members acknowledged the historical spatial concentration of students in one of the existing elementary schools, Cole Elementary, and urged the rezoning committee to reduce the spatial concentration at Cole by redistributing the number of students from minoritized racial and economic backgrounds to other elementary schools. Cole Elementary has historically served students from low-income and racially minoritized backgrounds. As of 2007, the district’s average enrollment of students with FRL status was 21%, while the average in Cole Elementary was 47% (WDPI, n.d). In addition, the percentage of Latinx students (13.5%) and African American students (23.1%) in Cole was twice as high as the district’s average (5% and 11.7%, respectively; WDPI, n.d). On the other hand, Woodside Elementary—a school whose neighborhood is only separated from Cole by a highway—only serve 8% of students with FRL and consequently only 7% of African American students in the school district (WDPI, n.d.). As the rezoning progressed, the conversation about redistributing the percentage of students eligible for FRL and avoiding spatial concentration based on race and class became inevitable. Acknowledging the economic and racial discrepancy in student enrollment between Cole Elementary and other elementary schools, the rezoning committee proceeded with the rezoning by carefully distributing the number of students with FRL eligibility across all elementary schools in the district, specifically to reduce the percentage of students eligible for FRL at Cole Elementary. The demographic information that guided the process was students’ family income and the projections of schools’ growth. Although race was not explicitly mentioned in the rezoning discourse, in the context of WSD students with FRL are typically students from racially minoritized backgrounds. The rezoning meetings and day-to-day discourse were contentious, with residents concerned about daily practical issues, from changes in family schedules to political and financial concerns such as the association of schools with certain neighborhoods and property values. The Present Study and Research Questions The aim of this study is to examine the construction of the spatial Other by examining a macro to micro pattern of residential areas, distribution of students, as well as suspension rate at the elementary school level. Based on the unique spatiotemporal context of WSD, we answered the following research questions: 1) What was the pattern of residential segregation in Wells between 2006 and 2010? 2) To what extent did the 2008 elementary school rezoning distribute students based on race and free and reduced-price lunch status? 3) What was the pattern of elementary school suspensions in Wells School District between 2006 and 2010, and to what extent did it relate to the pattern of residential and school segregation? Method This study is a portion of a larger longitudinal research project examining the intersection of place, race, class, and disability in a suburban community. Particularly, the larger research will investigate school rezoning from 2006/07 to 2017/18 in order to understand the social, historical, and spatial processes of school attendance rezoning, how these processes relate to the construction Spatial Othering 11 of spatial Other, and how the othering of minoritized students and families influences the identification of disability, particularly E/BD. This present paper focuses on the quantitative analysis, centering on the 2007/08 school rezoning as a pilot case. Both of the authors are familiar with the school district and Cole Elementary School from previous research that was conducted in the 2012-13 academic year (Bal, Kozleski, Schrader, Rodriguez & Pelton, 2014). Interviews with school personnel from Cole Elementary pertaining to racial disproportionality germinated the idea of spatialized Other and of how this concept impacts teaching resources and the prevalence of office discipline referrals. In summer of 2017, we decided to study in more depth the spatial and historical data of Wells and WSD. The first author has been actively involved in Cole Elementary since 2017 as a tutor on a volunteer basis to provide literacy assistance for students with or at risk for disabilities. Data Sources We generated both neighborhood-level data and district-level data. Block group data as small geographic units in a locality were used to approximate neighborhoods. Block group data are often used by the government and researchers to measure segregation (Bischoff, 2008; Siegel-Hawley, 2013). It would be more ideal, however, to use blocks data instead of block groups data since blocks are the smallest unit that represents a community in a block. Unfortunately, such data is not publicly available in the U.S. census. We utilized the 2010 five-year summary data released by the American Community Survey (ACS; conducted by the U.S. Census Bureau, n.d). The data contains demographic information from 2006 to 2010. Although we focused on the 2007/08 rezoning, we expanded our study to include data from two years before and after the rezoning to provide information about the student body in each elementary school. For district-level data, we relied on the state’ education agency (WDPI) to obtain public school-level data from five consecutive academic years (2006-2010), which provides information two years before and after the rezoning in 2008. The 2008 moment is critical because, as previously mentioned, there was then a strong debate about redistributing student enrollment in order to reduce the pockets of students of color and students from low-income backgrounds in Cole Elementary School. We also utilized publicly available information about students’ race, free and reduced-price lunch status, as well as the suspension rate for each elementary school in WSD. We used this data to measure how evenly students were distributed across elementary schools. We do need to point out that elementary school-age children in WSD attend not only public schools but also private schools (three religious-based private schools) not included in this study. Data Analysis Dissimilarity index. The dissimilarity index is a commonly used tool to measure segregation. It measures the degree to which two different groups are distributed among units in an area (Massey & Denton, 1988). The dissimilarity index between two groups is defined by the following equation: 𝐷 (𝑅, 𝑆) = 1 2 ∑ | 𝑟𝑖 𝑅𝑇 − 𝑠𝑖 𝑆𝑇 | 𝑛 𝑖=1 where n is the number of spatial units (i.e. schools and block groups), ri and si are the population of two groups r and s in tract i, while 𝑅𝑇 and 𝑆𝑇 are their total population in the district or city. The value of D ranges from 0 to 1, where 0 means perfect integration and 1 means complete segregation. D scores of 0.60 and above indicate high segregation, scores between 0.30 and 0.60 indicate medium segregation, and scores below 0.30 indicate low segregation (Frankenberg, 2012; Siegel-Hawley, Education Policy Analysis Archives Vol. 28 No. 91 12 Bridges, & Shields, 2017). The index indicates the proportion of either group of population in each unit that needs to change their school attendance zone and/or area of residence in order to achieve an even distribution of a category (e.g. race and income). Suspension rate. The suspension rate (SR) tells us the risk for one racial group being disciplined by suspension (Bal, Sullivan, & Harper, 2014). The SR for each racial group is calculated using the following equation: 𝑆𝑅 = 𝑁𝑜. 𝑜𝑓 𝑠𝑡𝑢𝑑𝑒𝑛𝑡𝑠 𝑖𝑛 𝑔𝑟𝑜𝑢𝑝 𝑋 𝑖𝑑𝑒𝑛𝑡𝑖𝑓𝑖𝑒𝑑 𝑖𝑛 𝑠𝑢𝑠𝑝𝑒𝑛𝑠𝑖𝑜𝑛 𝑁𝑜. 𝑜𝑓 𝑠𝑡𝑢𝑑𝑒𝑛𝑡𝑠 𝑜𝑓 𝑋 𝑔𝑟𝑜𝑢𝑝 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑡𝑢𝑑𝑒𝑛𝑡 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 The SR has been calculated by WDPI and provided in the publicly available dataset. We decided to double-check the percentage using the above equation. We excluded data about expulsion since the school district only had one case of expulsion during those five years. Below we will present the results of our analyses. Results We organized the findings according to 1) the pattern of residential segregation in Wells; 2) the extent of distribution of students from low-income and racially minoritized backgrounds in WSD per 2007/08 rezoning; and 3) the extent to which the residential and school segregation is reflected in school discipline. We will connect the findings with the concept of the spatial Other in the discussion section. Residential Patterns Based on Racial and Income Groups As previously mentioned, the city of Wells is changing from being an overwhelmingly White middle-upper class community to a heterogeneous one with a mixture of racial and income groups. However, as the community struggles with its changing demography, the remnants of its homogeneity remain visible. Utilizing the dissimilarity index, we found a high level of racial segregation and a moderate level of economic segregation at the neighborhood level. Table 1 Dissimilarity Index of Race in the City of Wells White African American Asian Latinx White African American 0.49 Asian 0.51 0.64 Latinx 0.56 0.54 0.46 Two or more race 0.34 0.52 0.48 0.57 Note: The darker the color, the higher the value. Race. The D scores indicate that the neighborhoods in Wells between 2006 to 2010 were moderate to highly segregated by race (see Table 1). Amongst all racial groups, African American is the most segregated group. Particularly concerning is the very high level of segregation between Spatial Othering 13 African American and Asians. Latinx are also at the verge of high segregation although not as high as African American. The level of racial segregation for each pair will only be reduced if either of the two groups (e.g., Asian and African American) change neighborhoods. Figure 2 presents where African Americans and Latinx, as well residents living in poverty, live in the city by block groups, for the purpose of visual comparison. Figure 2. Distribution of race and income in Wells. Source: U.S. Census Bureau (2010) Income Groups. We used ACS’s measurement of the ratio of income to poverty to measure the level of poverty in which a family lives. The ratio of income to poverty is the total family income divided by the poverty threshold (U.S. Census Bureau, n.d). The ACS categorizes the ratios of income to poverty as follows: doing poorly (<1.00), struggling (1.00-1.99), poor or struggling (<2.00) and, doing ok (>2.00). A ratio below 1 signifies an income level below the poverty Education Policy Analysis Archives Vol. 28 No. 91 14 level. A ratio of 1 signifies an income at the same level as the poverty level, while a ratio that is greater than 1 signifies an income higher than the poverty level (U.S. Census Bureau., n.d). The dissimilarity index (See Table 2) shows that the level of segregation based on income is not as severe as it is for race. Income segregation in Wells is moderate to low. Findings show that at the neighborhood level, people who live in deep poverty were moderately segregated from those who are struggling (𝐷=0.37; See Table 2), which means that about 37% of people who are in deep poverty or in struggling circumstances need to change neighborhoods in order to achieve economic integration between these two groups. Similarly, the findings also show that people in deep poverty were moderately segregated from people who are well-off (𝐷=0.39). See also Figure 2 (bottom map) to see the spatial distribution of income in Wells. Table 2 Dissimilarity Index of Poverty in Wells Deep poor (<1.00) Struggling (1.00-1.99) Poor or struggling (<2.00) Doing ok (>2.00) Deep Poor Struggling 0.37 Poor or Struggling 0.26 0.11 Doing ok 0.39 0.22 0.23 Note: The darker the color, the higher the value. School District Patterns of Racial and Economic Distribution Race and income distribution at the district level showed a contrasting result at the neighborhood level. Though the neighborhoods showed a high and moderate level of segregation on the basis of race and income respectively, the district showed relatively low segregation. Race. The steady low value of the dissimilarity index D in Table 3 implies that racial segregation at the school level in the five years was relatively low. However, the distribution of Latinx and Asian students in 2006 was at a medium level of segregation (=0.30). When we looked closely at the disaggregated data, we found that the large value of 𝐷 for the Latinx-Asian students was because Cole Elementary had the majority of Latinx students (37.5%), nearly three times higher than other schools. In the same year, only 8% of Asian students enrolled at Cole Elementary School, the lowest percentage in the district. The D values indicated a fluctuating level of segregation for Latinx-Asian students in the years after the 2008 rezoning. However, despite the fluctuation, the imbalance in proportion for these two racial groups remained stable. Income groups. The low value of the dissimilarity index for FRL-NonFRL students in those five years suggests a low segregation of students based on income or economic status (see Table 3). However, the years 2006 and 2007 were slightly closer to the threshold of a medium level of segregation (D=0.28). The community of Wells critically examined the economic imbalance between schools and pushed the boundary task force committee to carefully distribute the percentage of students with FRL status across all elementary schools. As a result, the application in 2008 of the new attendance zones was able to reduce economic segregation from 28% to 21%. The percentage Spatial Othering 15 remained low until 2010. The dissimilarity index suggested that segregation based on family income did not show a stark difference at either the school or the neighborhood level. This result should be interpreted with the caution given that this study only analyzed public school data, which may be a limitation to this study. In addition to the public elementary schools, elementary school-aged children also have the option to attend three religious-based private schools that served more than 400 students each year in total (WDPI, n.d.). Excluding the private school enrollment data may have decreased the value of the dissimilarity index, since not all elementary school-aged children in the neighborhoods were counted. Table 3 Dissimilarity Index of Race and Class in WSD 2006-2010 Race/Class Pairs Year 2006 2007 2008 2009 2010 White-African American 0.24 0.26 0.19 0.17 0.23 White-Asian 0.11 0.11 0.15 0.18 0.24 White-Latinx 0.25 0.28 0.18 0.23 0.22 African American-Asian 0.25 0.18 0.11 0.13 0.13 African American-Latinx 0.17 0.16 0.2 0.2 0.16 Latinx-Asian 0.3 0.25 0.27 0.28 0.26 FRL-Non FRL 0.28 0.28 0.21 0.21 0.22 Note: The darker the color, the higher the value Distribution of Students in the 2007/08 School Rezoning Aggregated data implied that the rezoning was able to reduce segregation on the basis of class. However, when we looked at disaggregated data, we found a persistent economic segregation despite the rezoning. That is, Cole Elementary School still had the highest number of students from low-income backgrounds despite their decreasing proportion. Thus, the rezoning did not have a meaningful impact on Cole Elementary. The school’s economic and racial composition remained distinct from other schools. In fact, Cole continued to serve the majority of low-income and Latinx and African American students in the district. There was still a stark difference between the percentage of students with FRL status in Cole compared to the rest of the elementary schools even after the rezoning (see Figure 3). Blue Ridge maintained its enrollment of the highest percentage of non-FRL students in the district, whereas Woodside Elementary continued to have the lowest number of students with FRL status for the five consecutive years despite the changes in school attendance zones that had been intended to evenly distribute students based on economic status. Education Policy Analysis Archives Vol. 28 No. 91 16 Figure 3. Percentage of students eligible for FRL in WSD District Patterns of School Discipline To find out the pattern of elementary school suspensions in WSD between 2006 and 2010, we looked at disaggregated data in order to compare the suspension rates between schools and within a single school. The rates of suspension between schools, as shown in Figure 4, suggested that African American and Latinx students are far more likely to be suspended compared to students from other racial groups. In 2006, African American students received the highest suspension rate in the district. The pattern remains the same five years later. Latinx students also experienced overrepresentation in suspensions, although the magnitude was not as high as it was for African American students. Schools with African American student enrollment rates below the district average tended to suspend more students from these racial groups. For example, the risk of suspension for African American students in Blue Ridge Elementary School was 5% to 13%. A similar pattern was true for Woodside Elementary School. In 2010 alone, African American students at Woodside were 22 times more likely to be suspended than students from any other racial groups—that is, five out of only 23 African American students enrolled in the school that year. Interestingly, Cole Elementary School showed a different pattern of suspensions. Cole is the only school that serves a majority of racially and economically minority students. Yet, the suspension rate in those five years showed that Cole had the lowest overall suspension rate compared to all elementary schools. However, the within-school suspension pattern showed that despite Cole's comparatively low suspension rate, African American and Latinx students in Cole received out of school suspensions at a higher rate than students from other racial groups, in all years except 2007. Spatial Othering 17 Figure 4. Suspension rates of elementary schools by race in WSD 2006-2010 Discussion What do the patterns of residential segregation, school attendance zones, and suspension rates tell us about spatial othering? All three units of analysis in this study—residential areas, school attendance zones, and school discipline—explicate a “doing” or historical and continuous process of othering rather than a “being” (Butler, 1993). The construction of the Other is visible in seemingly discrete yet related structural spatial arrangements of the city and school boundaries. A high to moderate level of neighborhood segregations, particularly concerning for African American and Latinx, resemble of how physical space (designs of the city including policy making) re-produce and reinforce social relations. Such racially segregated neighborhoods produce racially segregated schools reinforced by neighborhood school concept in which parents and community members of Wells prioritize keeping the neighborhoods intact. The racially segregated neighborhood is (re)produced at the school level evidenced by comparatively high enrollment of African American and Latinx students in certain school such as Cole Elementary. The spatial context of segregations is further visible in hyper overrepresentation of African American and Latinx in school discipline. The spatial- historical design of the city lays as a background for the racially disproportionate school discipline rate. Such continuous spatial othering at these two scales is not a surprise given that the Wells community is experiencing growing pains. The city is grappling with its changing identity, moving away from being an almost all-White middle-class community to a more racially and economically diverse one (Fry, 2009). Cole Elementary School is more vulnerable than all other elementary schools in Wells because the majority of low-income apartments are located within Cole’s school boundaries. Racially Education Policy Analysis Archives Vol. 28 No. 91 18 and economically segregated neighborhoods, when linked to neighborhood schools, trap the children who live in affordable housing apartment complexes from moving upward. Therefore, despite the good intentions and efforts from the rezoning committee to redistribute the percentage of students with FRL status, Cole continued to serve the majority of the city’s low-income students. The rezoning was able to reduce the percentage of students from low-income backgrounds at Cole, but it was not able to change the persistent concentration of low-income and consequently racially minoritized students there. Spatial othering extends to day-to-day schooling practices through school discipline. The disproportionate representation of minoritized students in school suspensions demonstrated that African American and Latinx students in overwhelmingly White schools and neighborhoods (e.g., Woodside) are more likely to receive school suspensions. Even Cole Elementary, which serves a majority of minoritized students in the district, disproportionately suspended African American students at a comparatively high level. The findings highlight that African American and Latinx students experienced multiple scales of racial segregation. At the neighborhood level, they experienced economic and racial enclavements; at the school level, they were mostly concentrated in Cole Elementary School; and, within Cole Elementary, they were further excluded through disciplinary practices. In other words, racial segregation of African American and Latinx students became a highly naturalized and inevitable process in the city of Wells spanning from neighborhoods into classrooms (Kramarczuk Voulgarides, 2018). The interlocking spatial concentration, which was and is still visible in Wells, is a product of the city's spatial history and reinforced by city policies such as the housing discrimination ordinance and the chronic nuisance ordinance. Such policies control who can live where (Lipsitz, 2011) and therefore attend which school. The zoning allowed low-income apartments to be in certain areas only. Meanwhile, the ordinances functioned as a gatekeeper to prevent racially and economically minoritized residents from living in Wells, let alone living outside of the designated low-income housing complex. These two factors may have greatly contributed to the high level of racial segregation at the neighborhood level. One may argue that spatial segregation is an unintended result of freedom to choose (e.g., to choose where to live, with whom to live and associate). Yet, those so- called individual freedoms do not happen in a vacuum. Rather, they are structurally supported by government and private institutions such as apartment management companies, which often practice racial steering to screen who can live in their premises. We do need to mention that the government of Wells through the mayor and the city council is aware of the negative impacts of the old city planning to the concentration of people on the basis of race and income. In its renewed comprehensive plan, the government plans to implement a concept of balanced neighborhoods consisting of a combination of housing types ranging from apartments and townhouses to single family housing in new subdivisions. It is hoped that the new plans will deconcentrate racial and economic segregation at the neighborhood level and consequently the school level. In our attempts to unpack the multiple structural forces that reproduce disproportionality in school discipline in Wells, we found that spatial othering through concentrating racially and economically minoritized residents depicts a socio-spatial process of abjectifiying and stigmatizing the differences of students who are from minoritized backgrounds (Kristeva, 1982). Such abjectifying at the city and neighborhood levels serves as a background to unconscious norms about how discipline operates in its perception of the behaviors of students from low-income and racially minoritized backgrounds as unacceptable, out of control, and improper (Lawrence, 1987). The over- representation of African American students in exclusionary school discipline is a symptom of larger structural inequities along the intermingling lines of race and class in the United States (Bal, 2017). In everyday function of schools, it might be based on a belief that school discipline is the space for Spatial Othering 19 African American and Native American students, whose behaviors are constructed as different from the dominant culture, enhancing the stigma that students of color are behaviorally aberrant. School discipline as a mechanism to re-segregate students of color and students from low-income backgrounds accentuates differences and naturalizes exclusionary discipline as the natural place for students of color. Assigning the majority of students of color and students from low-income backgrounds to Cole Elementary School is also an action of accentuating differences, stigmatizing Cole Elementary as a space for those who do not belong in the city or in other schools. Positionality through school discipline such as well-behaved or disrupting students are societal forces and norms that intertwine to construct an identity for children who are perceived as troubled students. Limitations and Future Studies First limitation of the study is that we did not include other structural and interactional contexts within schools, such as teacher demographic data and how teacher identity might play a role in how teachers refer students for school disciplinary actions. Also, we did not interview teachers at the schools. We acknowledge that inquiry about how, when, and under what circumstance students' different identity markers are made consequential under a school discipline system might be best examined through qualitative inquiry such as observations and interviews. The scope of this study limits us to focusing on the qualitative process of the construction of differences that occur through and in day-to-day activities in school. We will present such analyses in future publications. Second, we also did not include interviews with the rezoning committee to gain their perspectives about discourses during the rezoning. Future studies can delve more into this topic. Third, the analytical method of the dissimilarity index has limitations with regard to capturing school and neighborhood segregation. The dissimilarity index is a broad way to look at segregation patterns that can only look at the segregation trend between two groups at a time (Orfield, Kucsera, & Siegel- Hawley, 2012). Lastly, this study utilized data from a single school district and only public-school data. Therefore, the results could not be generalized to other districts. Future research can focus on the qualitative analysis of mundane processes of othering that exist within and across city planning and decision-making activities in the school district and in specific schools. Studies can also examine how neighborhood and school attendance zones function as spaces of social control. Implications The findings have two important policy implications. First, education policy alone, meaning in this case the revision of school attendance zones, though carried out with the best of intentions, was not able to disrupt the racial and class segregation that had become strongly ingrained in the city. In other words, efforts to reduce the racial and class disparities cannot result in effective change if the approach is simply to redistribute the number of students. Such situations need inclusive, sustained, and transformative coalition-building activities and boundary-crossing practices from the city and district officials to interrupt the status quo that perpetuates multilayered racial and economic segregation. Policies pertaining to schooling need to be juxtaposed with the larger social policies such as housing developments and land use, to name a few, since these policies directly affect school policies. However, institutions working on these important policies often work in “separate silos,” disconnected from each other (Frankenberg & Orfield, 2012). Second, housing segregation is a part of the chain of discrimination affecting schools. Therefore, studies on disproportionality should also address one of its strongest links: housing segregation. Spatial exclusion should be included in the examination of disproportionality, because the way space is organized tells us a great deal about how some groups are excluded, simply for being perceived as outside of the mainstream. Education Policy Analysis Archives Vol. 28 No. 91 20 Given the role of school as a microcosm of its community, it is imperative for school disciplinary systems to consider where behavioral norms come from and if the norms represent the cultures in the school. In addition, schools need to build institutional capacity for collectively and critically examining their own disciplinary systems and what larger cultural norms lie behind school level norms with all staff, families, students, and community members, especially those from historically marginalized backgrounds (Bal, 2016; Bal et al., 2014). Systemic transformation at the city and neighborhood level is as critical as efforts on the everyday within-school level to reduce behavioral referrals. If the larger societal context operates on othering and abjectifying residents who are racially and economically minoritized, it might be hard -if not impossible- to witness equity within the school space, particularly the racialization of behavioral problems. Conclusion Disproportionality is a multifaceted and adaptive socially, historically, and spatially constructed phenomenon (Bal, 2017). This study provides a situated spatial analysis in a demographically changing suburban community. Neighborhood and school play interconnected roles that shape how minoritized students in Wells experience their education. Despite the well- intentioned efforts of the rezoning committee to lower the percentage of students eligible for FRL in Cole Elementary School, spatial othering at the neighborhood level continues to funnel students eligible for FRL into the school, due to the concentration of low-income housing in the neighborhood where the school is located. From the case of Wells City, we can see that residential segregation made it difficult to break the barriers of the concentration of minoritized students in certain areas. The efforts of the district’s school rezoning committee were limited by the fact that the city is segregated and the children in Wells will continue to attend schools based on where they live. Structural inequities such as ongoing spatial concentration of people from economically and racially minoritized backgrounds in impoverished areas function as the background of naturality for behavioral tracking of minoritized youth in schools. The school rezoning policy cannot be seen separately as an independent entity. It takes enormous of effort, coordination, and strategies to keep an increasingly diverse city segregated. If a city is segregated, its schools will be segregated and hence unequal. References Administrator for the Division of Housing. (n.d.). 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Retrieved December 2019 from https://nces.ed.gov/pubsearch. Wisconsin Department of Public Instruction. (n.d.). Wisconsin Information System for Education Data Dashboard. Author. https://doi.org/10.2307/2579183 https://doi.org/10.17763/haer.83.4.k385375245677131 https://doi.org/10.1177/0013161X16659346 https://doi.org/10.1177/001440290807400301 https://doi.org/10.5749/minnesota/9780816666676.001.0001 https://doi.org/10.1016/B978-008044910-4.00980-9 https://doi.org/10.3102/0013189X08326409 https://doi.org/10.1007/978-94-6300-977-5_12 https://doi.org/10.1007/978-94-6300-977-5_12 https://factfinder.census.gov/ https://nces.ed.gov/pubsearch Spatial Othering 23 About the Authors Dian Mawene University of Wisconsin-Madison mawene@wisc.edu Dian Mawene is a Ph.D. candidate in Special Education at the University of Wisconsin-Madison. Dian's research interest includes the intersection of race, class, space, and disability through which she examines how social structures including space shape educational opportunities of minoritized students. Aydin Bal University of Wisconsin-Madison abal@wisc.edu Aydin Bal is an associate professor of education at the University of Wisconsin—Madison. His research focuses on the interplay between culture and behavioral problems across local and global education systems. Dr. Bal examines the racial disparities in special education and school discipline, family-school-community-university collaboration, refugee education, expansive learning, and systemic transformation. education policy analysis archives Volume 28 Number 91 June 15, 2020 ISSN 1068-2341 Readers are free to copy, display, distribute, and adapt this article, as long as the work is attributed to the author(s) and Education Policy Analysis Archives, the changes are identified, and the same license applies to the derivative work. More details of this Creative Commons license are available at https://creativecommons.org/licenses/by-sa/4.0/. EPAA is published by the Mary Lou Fulton Institute and Graduate School of Education at Arizona State University Articles are indexed in CIRC (Clasificación Integrada de Revistas Científicas, Spain), DIALNET (Spain), Directory of Open Access Journals, EBSCO Education Research Complete, ERIC, Education Full Text (H.W. Wilson), QUALIS A1 (Brazil), SCImago Journal Rank, SCOPUS, SOCOLAR (China). Please send errata notes to Audrey Amrein-Beardsley at audrey.beardsley@asu.edu Join EPAA’s Facebook community at https://www.facebook.com/EPAAAAPE and Twitter feed @epaa_aape. mailto:mawene@wisc.edu mailto:abal@wisc.edu https://creativecommons.org/licenses/by-sa/4.0/ http://www.doaj.org/ mailto:audrey.beardsley@asu.edu https://www.facebook.com/EPAAAAPE Education Policy Analysis Archives Vol. 28 No. 91 24 education policy analysis archives editorial board Lead Editor: Audrey Amrein-Beardsley (Arizona State University) Editor Consultor: Gustavo E. Fischman (Arizona State University) Associate Editors: Melanie Bertrand, David Carlson, Lauren Harris, Eugene Judson, Mirka Koro-Ljungberg, Daniel Liou, Scott Marley, Molly Ott, Iveta Silova (Arizona State University) Madelaine Adelman Arizona State University Amy Garrett Dikkers University of North Carolina, Wilmington Gloria M. Rodriguez University of California, Davis Cristina Alfaro San Diego State University Gene V Glass Arizona State University R. Anthony Rolle University of Houston Gary Anderson New York University Ronald Glass University of California, Santa Cruz A. G. Rud Washington State University Michael W. Apple University of Wisconsin, Madison Jacob P. K. Gross University of Louisville Patricia Sánchez University of University of Texas, San Antonio Jeff Bale University of Toronto, Canada Eric M. Haas WestEd Janelle Scott University of California, Berkeley Aaron Benavot SUNY Albany Julian Vasquez Heilig California State University, Sacramento Jack Schneider University of Massachusetts Lowell David C. Berliner Arizona State University Henry Braun Boston College Kimberly Kappler Hewitt University of North Carolina Greensboro Noah Sobe Loyola University Casey Cobb University of Connecticut Aimee Howley Ohio University Nelly P. Stromquist University of Maryland Arnold Danzig San Jose State University Steve Klees University of Maryland Jaekyung Lee SUNY Buffalo Benjamin Superfine University of Illinois, Chicago Linda Darling-Hammond Stanford University Jessica Nina Lester Indiana University Adai Tefera Virginia Commonwealth University Elizabeth H. DeBray University of Georgia Amanda E. Lewis University of Illinois, Chicago A. Chris Torres Michigan State University David E. DeMatthews University of Texas at Austin Chad R. Lochmiller Indiana University Tina Trujillo University of California, Berkeley Chad d'Entremont Rennie Center for Education Research & Policy Christopher Lubienski Indiana University Federico R. Waitoller University of Illinois, Chicago John Diamond University of Wisconsin, Madison Sarah Lubienski Indiana University Larisa Warhol University of Connecticut Matthew Di Carlo Albert Shanker Institute William J. Mathis University of Colorado, Boulder John Weathers University of Colorado, Colorado Springs Sherman Dorn Arizona State University Michele S. Moses University of Colorado, Boulder Kevin Welner University of Colorado, Boulder Michael J. Dumas University of California, Berkeley Julianne Moss Deakin University, Australia Terrence G. Wiley Center for Applied Linguistics Kathy Escamilla University of Colorado, Boulder Sharon Nichols University of Texas, San Antonio John Willinsky Stanford University Yariv Feniger Ben-Gurion University of the Negev Eric Parsons University of Missouri-Columbia Jennifer R. Wolgemuth University of South Florida Melissa Lynn Freeman Adams State College Amanda U. Potterton University of Kentucky Kyo Yamashiro Claremont Graduate University Rachael Gabriel University of Connecticut Susan L. Robertson Bristol University Miri Yemini Tel Aviv University, Israel Spatial Othering 25 archivos analíticos de políticas educativas consejo editorial Editores Asociados: Felicitas Acosta (Universidad Nacional de General Sarmiento), Armando Alcántara Santuario (Universidad Nacional Autónoma de México), Ignacio Barrenechea, Jason Beech ( Universidad de San Andrés), Angelica Buendia, (Metropolitan Autonomous University), Alejandra Falabella (Universidad Alberto Hurtado, Chile), Carmuca Gómez-Bueno (Universidad de Granada), Veronica Gottau (Universidad Torcuato Di Tella), Carolina Guzmán-Valenzuela (Universidade de Chile), Antonia Lozano-Díaz (University of Almería), Antonio Luzon, (Universidad de Granada), María Teresa Martín Palomo (University of Almería), María Fernández Mellizo- Soto (Universidad Complutense de Madrid), Tiburcio Moreno (Autonomous Metropolitan University-Cuajimalpa Unit), José Luis Ramírez, (Universidad de Sonora), Axel Rivas (Universidad de San Andrés), César Lorenzo Rodríguez Uribe (Universidad Marista de Guadalajara), Maria Veronica Santelices (Pontificia Universidad Católica de Chile) Claudio Almonacid Universidad Metropolitana de Ciencias de la Educación, Chile Ana María García de Fanelli Centro de Estudios de Estado y Sociedad (CEDES) CONICET, Argentina Miriam Rodríguez Vargas Universidad Autónoma de Tamaulipas, México Miguel Ángel Arias Ortega Universidad Autónoma de la Ciudad de México Juan Carlos González Faraco Universidad de Huelva, España José Gregorio Rodríguez Universidad Nacional de Colombia, Colombia Xavier Besalú Costa Universitat de Girona, España María Clemente Linuesa Universidad de Salamanca, España Mario Rueda Beltrán Instituto de Investigaciones sobre la Universidad y la Educación, UNAM, México Xavier Bonal Sarro Universidad Autónoma de Barcelona, España Jaume Martínez Bonafé Universitat de València, España José Luis San Fabián Maroto Universidad de Oviedo, España Antonio Bolívar Boitia Universidad de Granada, España Alejandro Márquez Jiménez Instituto de Investigaciones sobre la Universidad y la Educación, UNAM, México Jurjo Torres Santomé, Universidad de la Coruña, España José Joaquín Brunner Universidad Diego Portales, Chile María Guadalupe Olivier Tellez, Universidad Pedagógica Nacional, México Yengny Marisol Silva Laya Universidad Iberoamericana, México Damián Canales Sánchez Instituto Nacional para la Evaluación de la Educación, México Miguel Pereyra Universidad de Granada, España Ernesto Treviño Ronzón Universidad Veracruzana, México Gabriela de la Cruz Flores Universidad Nacional Autónoma de México Mónica Pini Universidad Nacional de San Martín, Argentina Ernesto Treviño Villarreal Universidad Diego Portales Santiago, Chile Marco Antonio Delgado Fuentes Universidad Iberoamericana, México Omar Orlando Pulido Chaves Instituto para la Investigación Educativa y el Desarrollo Pedagógico (IDEP) Antoni Verger Planells Universidad Autónoma de Barcelona, España Inés Dussel, DIE-CINVESTAV, México José Ignacio Rivas Flores Universidad de Málaga, España Catalina Wainerman Universidad de San Andrés, Argentina Pedro Flores Crespo Universidad Iberoamericana, México Juan Carlos Yáñez Velazco Universidad de Colima, México javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/819') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/820') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/4276') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/1609') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/825') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/797') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/823') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/798') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/555') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/814') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/2703') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/801') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/826') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/802') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/3264') javascript:openRTWindow('http://epaa.asu.edu/ojs/about/editorialTeamBio/804') Education Policy Analysis Archives Vol. 28 No. 91 26 arquivos analíticos de políticas educativas conselho editorial Editor Consultor: Gustavo E. Fischman (Arizona State University) Editoras Associadas: Andréa Barbosa Gouveia (Universidade Federal do Paraná), Kaizo Iwakami Beltrao, (Brazilian School of Public and Private Management - EBAPE/FGVl), Sheizi Calheira de Freitas (Federal University of Bahia), Maria Margarida Machado, (Federal University of Goiás / Universidade Federal de Goiás), Gilberto José Miranda, (Universidade Federal de Uberlândia, Brazil), Marcia Pletsch (Universidade Federal Rural do Rio de Janeiro), Maria Lúcia Rodrigues Muller (Universidade Federal de Mato Grosso e Science), Sandra Regina Sales (Universidade Federal Rural do Rio de Janeiro) Almerindo Afonso Universidade do Minho Portugal Alexandre Fernandez Vaz Universidade Federal de Santa Catarina, Brasil José Augusto Pacheco Universidade do Minho, Portugal Rosanna Maria Barros Sá Universidade do Algarve Portugal Regina Célia Linhares Hostins Universidade do Vale do Itajaí, Brasil Jane Paiva Universidade do Estado do Rio de Janeiro, Brasil Maria Helena Bonilla Universidade Federal da Bahia Brasil Alfredo Macedo Gomes Universidade Federal de Pernambuco Brasil Paulo Alberto Santos Vieira Universidade do Estado de Mato Grosso, Brasil Rosa Maria Bueno Fischer Universidade Federal do Rio Grande do Sul, Brasil Jefferson Mainardes Universidade Estadual de Ponta Grossa, Brasil Fabiany de Cássia Tavares Silva Universidade Federal do Mato Grosso do Sul, Brasil Alice Casimiro Lopes Universidade do Estado do Rio de Janeiro, Brasil Jader Janer Moreira Lopes Universidade Federal Fluminense e Universidade Federal de Juiz de Fora, Brasil António Teodoro Universidade Lusófona Portugal Suzana Feldens Schwertner Centro Universitário Univates Brasil Debora Nunes Universidade Federal do Rio Grande do Norte, Brasil Lílian do Valle Universidade do Estado do Rio de Janeiro, Brasil Geovana Mendonça Lunardi Mendes Universidade do Estado de Santa Catarina Alda Junqueira Marin Pontifícia Universidade Católica de São Paulo, Brasil Alfredo Veiga-Neto Universidade Federal do Rio Grande do Sul, Brasil Flávia Miller Naethe Motta Universidade Federal Rural do Rio de Janeiro, Brasil Dalila Andrade Oliveira Universidade Federal de Minas Gerais, Brasil