This toolkit provides guidance to protect participant confidentiality in human services research and evaluation, including legal frameworks, risk assessment strategies, and best practices.
U.S. Department of Health and Human Services (HHS)
A case study documenting how a modular API layer was built to support a state-level paid family and medical leave program, improving interoperability, scalability, and user experience.
This cheat sheet helps job seekers translate private-sector technology roles and skills into equivalent U.S. government job classifications and titles.
This case study describes Nava's work with the state of Montana’s Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) agency to build an API prototype, which is part of Nava's larger work inform a national API standard.
The $600 cash payments provided by the CARES act prevented joblessness from turning into actual income loss for millions of families. It also gave Americans breathing room to wait for better jobs, rather than settling for bad ones out of desperation.
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.
This report provides guidance on building equitable and user-friendly affordable housing portals, highlighting best practices from platforms like Bloom Housing and Housing Navigator MA.
To assist states in closing digital skill gaps and preparing for digital equity planning, this brief offers key questions and resources for state leaders to consider.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
