This article discusses the challenges of today’s centralized identity management and investigates current developments regarding verifiable credentials and digital wallets.
This article analyzes the strategic use of public policy as a tool for reshaping public opinion. Though progressive revisionists in the 1990s argued that reforming welfare could produce a public more willing to invest in anti-poverty efforts, welfare reform in the 1990s did little to shift public opinion. This study investigates the general conditions under which mass feedback effects should be viewed as more or less likely.
This article examines how administrative burdens in U.S. social safety net programs have changed over the past 30 years, showing that while average burdens have declined, inequality in who faces these burdens has grown.
The ANNALS of the American Academy of Political and Social Science
This study examines the adoption and implementation of AI chatbots in U.S. state governments, identifying key drivers, challenges, and best practices for public sector chatbot deployment.
This article examines how the decentralization of safety net programs after welfare reform has led to growing inequality in benefit generosity and access across U.S. states.
The Better Government Lab at the McCourt School of Public Policy at Georgetown University has developed a new scale for measuring the experience of burden when accessing public benefits. They offer both a three-item scale and a single-item scale, which can be utilized for any public benefit program. The shorter scales provide a less burdensome way to measure by requiring less information from users.
This study investigates how administrative burdens influence differential receipt of income transfers after a family member loses a job, looking at Unemployment Insurance, Temporary Assistance for Needy Families, and the Supplemental Nutrition Assistance Program.
Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. This academic study presents an approach to evaluate bias present in automated facial analysis algorithms and datasets.
A recent study challenges the common belief that income support programs like SNAP reduce employment, finding that for individuals with a work history, receiving SNAP benefits can actually increase long-term employment.
Errors in administrative processes are costly and burdensome for clients but are understudied. Using U.S. Unemployment Insurance data, this study finds that while automation improves accuracy in simpler programs, it can increase errors in more complex ones.
