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A Conceptual Framework for Using Machine Learning to Support Child Welfare Decisions. (arXiv:2207.05855v1 [cs.CY])
cs.LG updates on arXiv.org arxiv.org
Human services systems make key decisions that impact individuals in the
society. The U.S. child welfare system makes such decisions, from screening-in
hotline reports of suspected abuse or neglect for child protective
investigations, placing children in foster care, to returning children to
permanent home settings. These complex and impactful decisions on children's
lives rely on the judgment of child welfare decisionmakers. Child welfare
agencies have been exploring ways to support these decisions with empirical,
data-informed methods that include machine learning …
arxiv decisions framework learning machine machine learning support