This study explores the causal impacts of income on a rich array of employment outcomes, leveraging an experiment in which 1,000 low-income individuals were randomized into receiving $1,000 per month unconditionally for three years, with a control group of 2,000 participants receiving $50/month.
The article presents the True Cost of Economic Security (TCES) measure, showing that over half of U.S. families struggle to meet the comprehensive costs required to thrive, highlighting significant disparities based on family type, location, and race.
In this webinar, a panel of experts discuss what states can do right now to improve EBT security, how to use data to analyze theft patterns, and how EBT payment technology needs to evolve to ensure efficiency, security, and dignity for beneficiaries.
The "Public Sector AI Playbook" provides public sector officers with practical guidance on adopting and implementing AI technologies to improve government operations, service delivery, and policymaking.
This brief synthesizes the manner in which the political and social service environments affect the intergenerational stability of non-citizen families, offering insights into programmatic supports.
American Public Human Services Association (APHSA)
This playbook outlines the ways Community Action and human services agencies worked together to meet the pandemic challenge—what worked well, obstacles and difficulties, and lessons learned to inform the path forward, partnering to achieve a more equitable recovery. It also explains how communities have leveraged opportunities to partner on approaches that hold the promise of deeper, longer lasting changes for families—work shaped by families’ wishes and strengths and designed to advance both family-level and systems-level change.
American Public Human Services Association (APHSA)
This guide outlines ethical frameworks and best practices for responsibly collecting and using demographic and other sensitive data to build equitable digital products.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
Drawing on the Beeck Center’s research on government, nonprofit, academic, and private sector organizations that are working to improve access to safety net benefits, this report highlights best practices for creating accessible benefits content.
