This resource offers practical strategies for early childhood programs to create inclusive, affirming environments for LGBTQIA2S+ families and their children.
U.S. Department of Health and Human Services (HHS)
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.
Companies have been developing and using artificial intelligence (AI) for decades. But we've seen exponential growth since OpenAI released their version of a large language model (LLM), ChatGPT, in 2022. Open-source versions of these tools can help agencies optimize their processes and surpass current levels of data analysis, all in a secure environment that won’t risk exposing sensitive information.
Building on our February 2022 report Benefit Eligibility Rules as Code: Reducing the Gap Between Policy and Service Delivery for the Safety Net, the Beeck Center’s Digital Benefits Network (DBN) recently held a convening to share progress and potential in digitizing benefits eligibility and to begin addressing how a national approach could be started.
On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP) applications, and unemployment insurance applications.
This primer introduces two foundational software types that can support organizations that are committed to accessible benefits information: content management systems (CMS) and application program interfaces (APIs).
This is a monorepo managing the web components of the Government of Canada's Design System, facilitating the creation of consistent and accessible digital services.
As a next step in Iowa's modernization effort, the MEME project released a video describing Iowa's proposed approach and next steps for the purpose of engaging with vendors. The video linked here provides additional information on the project's learnings so far.
