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State and local agencies that provide services to low income families to achieve self-sufficiency are increasingly looking to incorporate better data into decision-making around policies, programs, and practices in an effort to improve outcomes and make efficient use of scarce taxpayer dollars. High quality data will support research to build evidence around what works to improve self-sufficiency. The Family Self-Sufficiency Data Center (FSSDC) was established to support states to better use data and to increase the amount and quality of data available for research related to family self-sufficiency. The relevant programs include, but are not limited to, Temporary Assistance to Need Families, Supplemental Nutritional Assistance Program and other food assistance programs, workforce development and training programs, early care and education, and health insurance.
体育盘口_足球比分网The FSSDC is a partnership with Harris Public Policy, , , and . The principal investigator is and the co-PI is , both recognized experts in family self-sufficiency research. Collectively, the team has expertise in executing data sharing agreements, data management (including cleaning, linking, and visualizing data), data analysis, and communicating and applying findings from data. Together with funding and leadership from the and input from Administration for Children and Family (ACF) at the US Department of Health and Human Services (DHHS), we are creating a Data Center that will become a hub for research and resources around the promotion, use, and dissemination of family self-sufficiency data in a five-year project, funded from 2013–18.
The FSSDC partners with researchers, policymakers and administrators to answer fundamental policy and program questions and build knowledge that will ultimately be translated into better policy and practice. The FSSDC seeks to achieve this mission through a number of core projects and functions, including data support and technical assistance, outreach and collaboration, research, and dissemination of Data Center work through written products.
Data support and technical assistance: 体育盘口_足球比分网The Data Center provides modeling, analytic resources and technical support to both data providers and users, targeted at issues of family self-sufficiency. We partner directly with a set of pilot states to assess data quality, restructure data, examine caseload dynamics and churn, and explore specific policy questions around issues such as employment mandates for food stamp recipients. We also generate publicly available resources including cross-state comparative analyses and data models and code to build the capacity to use data at the state level.
Outreach and collaboration: 体育盘口_足球比分网The Data Center works to engage a broad community of state partners and researchers, fostering connections and spurring innovation in self-sufficiency data analysis and research. We work directly with states hosting workshops that bring together state agency staff from around the country for sessions focused on administrative data usage and sample analyses with TANF, SNAP, employment, and child care data sources. We support a network of state agency staff using social media to build a community of practice in the family self-sufficiency data space.
The Data Center also disseminates work through conference presentations and collaborates with federal agencies and other stakeholders nationally via participation in OPRE’s Family Self-Sufficiency and Stability Research Consortium, which includes the and the (Project AWESOME).
Research: We have developed, and continue to develop, new research products that are intended to be resources for a broad community of state partners and researchers with regards to data models, structuring data, analyses, tools, and data sharing. Current areas of research include: caseload size and characteristics, including spell length and churn; common metrics used by states to consider program performance and outcomes and ways to accurately compare populations and policies across states; cross-state analyses with TANF data regarding caseload dynamics and employment trajectories; and specific policy questions around issues such as criminal history as a barrier to employment for benefit recipients.