Search
On-Site Program Calendar
Browse By Day
Browse By Time
Browse By Person
Browse By Room
Browse By Unit
Browse By Session Type
Search Tips
Change Preferences / Time Zone
Sign In
Bluesky
Threads
X (Twitter)
YouTube
This study investigates equitable access to Early Intervention (EI) by examining how children’s home language(s) and broader social contexts shape patterns of service exit. It also critiques a data system shaped by long-standing, unquestioned practices that fail to capture accurate demographic data, limiting understanding of who receives, and who loses, support. Using state-level data, the study explores disparities in EI exit reasons through QuantCrit, DisCrit, and Intersectionality frameworks. Infants and toddlers from English-only households were more likely to exit as “Not Eligible,” a pattern that may reflect differences in referral pathways or initial concerns. To support more accurate and equity-minded data practices across early childhood education systems, this study proposes a new data guideline: GUIDE-EI.