Journal on Policy & Complex Systems Volume 3, Issue 2 | Page 109

Modeling Complexity in Human Built Systems : New Approaches , New Findings in Foster Care
Fred Wulczyn A , John Halloran B
Policy and Complex Systems - Volume 3 Number 2 - Fall 2017

Modeling Complexity in Human Built Systems : New Approaches , New Findings in Foster Care

Abstract
Foster care is a widely utilized intervention to provide care to children who cannot live with their parents . The substantial portion of contemporary academic work on foster care either uses individual-level analyses , or focuses on linear analysis of aggregate annual statistics . This paper argues that a complexity-based perspective will deepen our understanding of how foster care policy operates . Wulczyn ( 1996 ) argued that a class of population growth models focused on latent resource limitations held great potential to elucidate behavior within aggregate foster care dynamics . Specifically , partial adjustment models propose that population growth rates and limits are dependent on prior resource and capacity states within a system . Recent advancements in data availability , methodology , and computation have made that theory testable . Analyzing data from the Foster Care Data Archive representing 81,142 child entries into out-of-home placements from 2000 through 2014 , we apply Empirical Dynamic Modeling to identify nonlinearity and detect causal relationships in coupled time series ( Sugihara et al ., 2012 ). Findings indicate nonlinear casual relationships in the coupled foster care entry and exit time series data . These findings match expectations of strength and directionality . The empirical findings and the models that they support have the potential to frame child welfare systems differently , ultimately leading to different actionable policy conclusions .
Keywords : child maltreatment , child protection , human-built systems , systems theory
A
Chapin Hall Center for Children at the University of Chicago
B
Lewis University doi : 10.18278 / jpcs . 3.2.7
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