Classifying and Describing Exemplary Data Use in Temporary Assistance for Needy Families (Tanf) Agencies
Dados Bibliográficos
| ID | 6445826 |
|---|---|
| Autores | Emily R Wiegand (National Opinion Research Center), Leah Gjertson (National Opinion Research Center), Emma Kahle Monahan (0000-0001-8301-0332, National Opinion Research Center), Robert M Goerge (National Opinion Research Center) |
| Ano | 2025 |
| Volume | 17 |
| Fascículo | 2 |
| Data de publicação | 2025-06-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Poverty & Public Policy (JOURNAL) |
| Identificadores do periódico | ISSN: 1944-2858 • E-ISSN: 2194-6027 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/pop4.70019 |
| OpenAlex | W4411295120 |
| Idioma | EN |
| Referências citadas | 27 |
State human service agencies often collect a wealth of administrative data, but the extent to which those data are accessed and leveraged for evaluation or program improvement varies greatly across time, states, and agencies. The current study is focused on data use in state agencies administering the Temporary Assistance for Needy Families (TANF) program, a federal cash assistance program for families with low incomes. Using data from a national needs assessment administered to state and territory TANF agencies ( n = 43), we identified three categories of data use: basic (describing 22 state TANF agencies; 51%), advanced (9; 21%), and exemplary (12; 28%). We examined the relationship between data use and agency characteristics and found that a culture of communication, collaboration, and transparency around data, as well as the development of quality external partnerships, are associated with higher quality agency data use. Factors like new data systems, data access tools, or increased financial resources were not consistently associated with higher quality agency data use; in particular, new data systems were inversely correlated with data use in the years immediately after implementation
Economics · Political science · Sociology · demographic modeling and climate adaptation · Financial Literacy, Pension, Retirement Analysis · Geriatric Care and Nursing Homes · Public Administration
Building Capacity for Evidence-Based Public Health
How Can Data Drive Policy and Practice in Child Welfare? Making the Link in Canada
Understanding Vulnerable Families in Multiple Service Systems Understanding Vulnerable Families
Big data analytics
Standing Still or Moving Up? Evidence from Wisconsin on the Long-Term Employment and Earnings of Tanf Participants
Illinois's Longitudinal and Relational Child and Family Research Database
Below the Tip of the Iceberg
Bridging the Gap between Evidence and Policy Makers
Building an Infrastructure to Support the Use of Government Administrative Data for Program Performance and Social Science Research
Child protective services decision-making
State Agencies’ Use of Administrative Data for Improved Practice
When Local Governments Request Access to Data
Automating Inequality
Barriers to Accessing State Data and Approaches to Addressing Them
Impact of South Carolina's Tanf Program on Earnings of New Entrants Before and During the Great Economic Recession
| Velocidade de citação | historical |
|---|---|
| Altamente citado | Não |