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- Primary and secondary data collection
- Training and technical assistance
- Performance management
- Parental well-being and self-sufficiency
- Workforce development
- Employment and training
- Human Services
- Family Support
- Training and Re-employment
Kara Conroy is a human services research analyst who specializes in evaluating and providing technical assistance to programs that aim to improve the economic mobility of families. Her research covers a wide range of policy areas affecting people and families with low income, including workforce development, adult education, two-generation programs, and social service coordination.
Conroy currently explores opportunities for federal agencies to better support cross-sector collaboration at the local level for the Models of Coordination and Technical Assistance to Achieve Outcomes in Communities project, commissioned by the Office of the Assistant Secretary for Planning and Evaluation in the U.S. Department of Health and Human Services.
She also provides program technical assistance to grantees of the Strengthening Working Families Initiative that supports parents facing barriers to training for middle- or high-skilled jobs.
In other projects, Conroy has studied adult reengagement in higher education, performance measurement in programs promoting economic independence, professional labor shortages, maternal and infant home visiting programs, and longitudinal outcomes for Harlem Children’s Zone students.
Conroy, who joined Mathematica in 2014, holds an M.S. in applied economics from Johns Hopkins University.
Models of Coordination and Technical Assistance to Achieve Outcomes in Communities
For the Models of Coordination and Technical Assistance to Achieve Outcomes in Communities project, Mathematica will partner with ASPE to explore several dimensions of federal-to-local efforts for cross-sector social service coordination.
Aligning Federal Performance Measures Across Programs Promoting Self-Sufficiency
A new study sheds light on how human services and workforce agencies can align indicators of program performance in ways that might increase coordination and improve services to people with low incomes.