IDWSDS 2025 - S114: Quantitative Approaches to Safeguarding Child Welfare

Описание: Safeguarding child welfare requires collaboration across government, public health, and community organizations. To understand how we can best serve the needs of youth across the globe, policy-makers often rely on insight coming from data. Thus, data analysts and (bio)statisticians are essential contributors to child welfare advocacy, as they can provide quantitative evidence to guide policy development.
In this session, sponsored by the Caucus for Women in Statistics, the speakers will discuss their work with linked data and big data in the child welfare policy space. First, Dr. Rameela Raman will describe examples of real-world policy-relevant work with a US child welfare system that highlights the advantages and challenges of using linked data. Dr. Svetlana Yampolskaya will then discuss the usage of big data and sub-group analysis to explore trajectories of substance use among youth in the child welfare system. Both of these speakers utilize data to drive positive changes in child welfare policy and ensure that all children have the support needed to thrive in their environment.

ORGANIZER: Ashley Mullan, Vanderbilt University
CHAIR: Catherine Chalikian, Johns Hopkins Applied Physics Lab
TALK TITLES AND SPEAKERS:
Informing policy and implementation in the child welfare system using integrated administrative data, Rameela Raman, Vanderbilt University School of Medicine
Big Data and Sub-Group Analysis: How Child Welfare Involvement Impacts Trajectories of Substance Use among Child Welfare Involved Youth, Svetlana Yampolskaya, University of South Florida