The examples in this guide describe how peer-to-peer training and updated interview scripts can help connect residents to the benefits they are eligible for.
This guide highlights approachable ideas for state and local public benefits agencies to improve applications, renewals, and correspondence. As outlined in this resource, even small improvements can be transformative for residents and caseworkers alike.
This paper analyzes the unique challenges of conducting participatory design in large-scale public projects, focusing on stakeholder management, fostering engagement, and integrating participatory methods into institutional transformation.
This toolkit provides practical guidance for agencies, researchers, and community partners to embed racial equity throughout every stage of data integration and use.
Delve into our exploration of the executive orders, legislation, and administrative rules and guidance that shape government digital transformation across states and territories with our database and visualization tools.
Medicaid and SNAP have reduced racial and ethnic disparities in healthcare access and food security, but some administrative and eligibility policies continue to create inequitable barriers.
This resource describes how different agencies have updated their systems to increase online and mobile access to benefits information and applications, including using text messages to share benefits information with residents.
Based on state agency survey responses, this report summarizes key findings from the first calendar year of pandemic response and provides policy considerations for the future of SNAP.
American Public Human Services Association (APHSA)
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
