The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
The article highlights the growing issue of SNAP benefit theft through skimming and advocates for permanent security measures and benefit replacements to protect vulnerable households.
An in-depth report that examines how states use automated eligibility algorithms for home and community-based services (HCBS) under Medicaid and assesses their implications for access and fairness.
There were over 25 million Medicaid disenrollments in 2023, but national enrollment remained significantly above pre-pandemic levels at over 56 million, with notable state-level variations and near-recovery of child enrollment.
The team developed an AI solution to assist benefit navigators with in-the-moment program information, finding that while LLMs are useful for summarizing and interpreting text, they are not ideal for implementing strict formulas like benefit calculations, but can accelerate the eligibility process by leveraging their strengths in general tasks.
This report calculates the cumulative impact of major benefit programs on two types of families and how their benefits change as they move into the labor market and climb the ladder of upward mobility.
This is a job description for the role of Poverty Research Technical Fellow from the New York City Mayor's Office for Economic Opportunity (NYC Opportunity).
During the call, we heard from two speakers: April Dunlap, Policy Administrator for Arizona’s Department of Economic Security and Professor Michele Gilman, Venable Professor of Law and Associate Dean for Faculty Research and Development at the University of Baltimore School of Law.
