The Contexts of “Significant Disproportionality”: Looking at State Implementation

• In Event: Context and Special Education Disproportionality: A Look at Racial Equity Policies in Special Education

Abstract

Objectives and Framework
We identify where Federal and State policies are being implemented to remediate special education disproportionality to surface potential misalignments between policies meant to reduce inequities in special education outcomes.

Under IDEA, States can mandate districts to allocate funds for Coordinated Early Intervention Services (CEIS) to address issues of overrepresentation of racial and ethnic groups in special education (i.e., “significant disproportionality”). However, policies for identifying districts as having significant disproportionality vary between states (GAO, 2013; Strassfeld, 2019; Sullivan & Osher, 2019). There is also a disconnect between measures of disproportionality and policies related to reducing disproportionality, such that current policy structures might mask locally occurring inequities (Albrecht et al., 2012; Sullivan & Osher, 2019; Voulgarides, 2018; Voulgarides et al., 2021).

We know that Federal and state policies and regulations related to special education classifications are interpreted across state and local jurisdictions (Harry & Klingner, 2014; Tefera & Voulgarides, 2016; Voulgarides, 2018) and vary significantly between states and districts (GAO, 2019; Kidder-Ashley et al., 2000; Reschly & Hosp, 2004; Singer et al., 1989). Moreover, racialized special education outcomes are related to various contextual factors (Elder et al., 2019; Fish, 2019; Shifrer & Fish, 2020; Sullivan & Artiles, 2011). Based on this and recent local studies, we posit that context is also critical to understanding how federal special education policy is implemented to reduce disproportionality (Aylward et al., 2021; Tefera & Fischman, 2020; Voulgarides & Aylward, 2023).

Methods
We use descriptive analysis to examine the proportion of districts within each state with significant disproportionality. Subsequently, we use a logistic multilevel model to determine the extent to which district and state characteristics predict significant disproportionality.

Data
CEIS data for the 2020-21 school year, retrieved from IDEA Section 618 Data, provide an indicator of which districts have significant disproportionality. We merged the CEIS data with district-level contextual characteristics (e.g., locale, district size, percent minoritized students) from the Common Core of Data (CCD), district-level poverty estimates from US Census Small Area Income Poverty Estimates (SAIPE), and state-level data (e.g., region, racial demographics, index of rurality) from the 2020 US Census.

Results
During the 2020-21 school year, 825 districts (5.54%) were identified as having significant disproportionality. Despite updated federal regulations requiring a standard, quantitative methodology for determining significant disproportionality, there is considerable variation across the United States in the proportion of districts identified with significant disproportionality (see Figure 1).

Preliminary results indicate substantial variation within and between states and that both the context of the district and the state contribute to the likelihood that a district is required to use CEIS funds to address significant disproportionality. States characterized by rurality and in the western region of the nation were less likely to identify districts with significant disproportionality. Additionally, more segregated districts, as measured by the index of dissimilarity, and districts in suburban locales were more likely to be identified with significant disproportionality.

Significance
This study is a critical step to providing a clear roadmap that links current IDEA racial equity policy remedies and empirical findings related to disproportionality.

Authors

• Roey Ahram, Grow Your Own Illinois

• Alexandra Aylward, University of Nevada - Reno