What counts? quantification, worker judgment, and divergence in child welfare decision making

Abstract

In an effort to manage risk under chronic resource constraints, information uncertainty, and accountability pressures, U.S. child welfare organizations have embraced the structured decision-making (SDM) model, which combines actuarial-based risk assessment with clinical decision making. Although 33 states have adopted the SDM to impose greater rationality and precision to child welfare decision making, little is yet known about how actuarial-based risk assessment interacts with child welfare workers’ own judgment in implementation, and to what effect. Drawing on original data from a case study of four child welfare agencies in one state, this article examines the nature of this interplay, and its implications for the quality of worker decision-making, child welfare, and worker job satisfaction.