This article examines how applying a Racial Equity Framework reveals systemic inequities in the Earned Income Tax Credit (EITC) program, offering insights into barriers faced by marginalized communities and potential solutions.
The Improving Service Delivery in EITC for New Yorkers initiative explores ways to enhance access to the Earned Income Tax Credit (EITC) through improved outreach, application processes, and service delivery.
GetYourRefund.org is an online portal by Code for America that helps low-income individuals claim thousands of dollars in tax credits, even after the traditional tax deadline has passed.
This Code for America article discusses how tax filing can be a powerful tool for economic justice, highlighting efforts to make the tax system more accessible and equitable for low-income individuals.
The NYC Benefits Screening API provides machine-readable calculations and criteria for benefits screening that power the ACCESS NYC screening questionnaire.
This report examines how the U.S. federal government can enhance the efficiency and equity of benefit delivery by simplifying eligibility rules and using a Rules as Code approach for digital systems.
ACCESS NYC is an online public screening tool that residents can use to determine the City, State, and Federal health and human service benefit programs for which they are eligible.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
This resource provides guidance on streamlining enrollment across public benefit programs to improve efficiency, reduce administrative burdens, and enhance access for eligible individuals and families.
Data provided by the NYC Mayor’s Office for Economic Opportunity regarding benefit, program, and resource information for over 80 health and human services available to NYC residents in all eleven local law languages.
