Challenging “Color-Lines” in Special Education via GIS: Anti-Racist Possibilities to Disrupt Zones of Resegregation

• In Event: A Collection of Critical Race Counterstories: Disrupting Resegregation in Special Education Using QuantCrit

Abstract

Objectives
The process of resegregation in special education starts when teachers go on the “hunt for disability” in elementary schools (Baker, 2002, p.138; Ferri & Bacon, 2011). Teachers follow legalized procedures, supported by federal legislation (IDEA Child Find Mandate), to initiate special education referrals, which almost always result in those children being identified (Artilles, 2010; Ferri & Connor, 2005). In this paper, we analyze zones of resegregation for Students of Color in special education and imagine educational spaces when anti-racist actions are put into effect, using Critical Race Spatial Analysis (CRSA), which utilizes GIS to explore, analyze, contextualize, and visualize the socio-spatial relationship between race and educational opportunity, or lack thereof (Author, 2023).

Theoretical Framework
Understanding Zones of Resegregation
CRSA analyzes and visualizes geographic “color-lines” (Du Bois, 1903) to make evident how race and racism have been structurally and systematically deployed to shape educational (in)opportunity. Using GIS (geographic information systems) applications guided by CRSA, this study maps the “hot spots” (measures of racialized injustices) of Students of Color resegregated in special education by school in Delaware, including students being placed in more restrictive, segregated placements. We refer to these as zones of resegregation. In more restrictive zones, students are given placements in segregated settings where they are removed from the general classroom. CRSA and QuantCrit have yet to be applied for understanding zones of (re)segregation in special education.

Data Sources
We used cross-sectional data (2014-2021) from Delaware. In our analyses we explored student demographics, including race, ethnicity, gender, socioeconomic status, and special education enrollment and placement, to investigate different zones of resegregation: full inclusion, limited segregation (less than 45 minutes), part-time segregation (45 minutes to 90 minutes), extreme segregation (90 minutes or more), and IEP diplomas. We used ArcGIS to spatially analyze this data across school districts and zip codes.

Methods
First, we spatially mapped zones of resegregation via latent response variable models, which transform a categorical dependent variable into a continuous latent variable, resulting in substantive interpretations (Lee et al., 2018). School-based data was combined with community-level data to refine these zones, examining the extent to which zones are more commonly found in densely populated low-income Neighborhoods of Color. We examined the propensity of students, based on students’ intersecting identities, in more restrictive zones of resegregation.
Next, we “ground-truthed” these maps with Educational Leaders of Color from the Delaware Department of Education and local school districts, in tandem with prior qualitative research, to develop and advance anti-racist policy, regulations, and teaching practices that eliminate zones of resegregation. The Counter-Cartographic Narrative visualizes “imagined” educational spaces that could result from anti-racist practices, regulations, and policies, when implemented.

Scholarly Significance
Our intention is to share these maps with a variety of stakeholder in Delaware
to increase dialogue about the importance of geospatial configurations that influence academic outcomes for Students of Color. By engaging and contextualizing data within “space” to produce an “antiracist landscape analysis” (Kobayashi and Peake, 2000), CRSA and QuantCrit become standpoints from which to engage social change.

Author

• Verónica Nelly Vélez, Western Washington University