This study found that using state-specific names for Medicaid programs increased confusion and reduced both positive and negative opinions about the program.
This paper examines three key questions in participatory HCI: who initiates, directs, and benefits from user participation; in what forms it occurs; and how control is shared with users, while addressing conceptual, ethical, and pragmatic challenges, and suggesting future research directions.
This foundational article develops the concept of administrative burden, defining it as the learning, psychological, and compliance costs individuals face when interacting with government, and argues that these burdens are often shaped by political choices.
Journal of Public Administration Research and Theory
The OECD report explores the concept of "Rules as Code" (RaC), proposing a transformation in government rulemaking by developing machine-consumable regulations alongside human-readable versions.
Organisation for Economic Co-operation and Development (OECD)
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.
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 research explores how software engineers are able to work with generative machine learning models. The results explore the benefits of generative code models and the challenges software engineers face when working with their outputs. The authors also argue for the need for intelligent user interfaces that help software engineers effectively work with generative code models.
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.
This study examines public attitudes toward balancing equity and efficiency in algorithmic resource allocation, using online advertising for SNAP enrollment as a case study.
This resource is a research paper examining the role of the public safety net in insuring job losers against income loss, analyzing which government programs provide financial support and how benefits vary based on pre-job loss income levels.
