The first paper discusses the development of a risk stratification model using administrative data and machine learning techniques to predict future CPS involvement. This presentation includes an overview of collaborative efforts to develop, test, and implement this model.
Given historical racial disproportionality in families involved with the child protection system, the importance of ensuring the fairness of the model through a racial equity lens cannot be overstated. As such, the next paper in this symposium describes fairness and equity analyses conducted to understand the implications for the model on racial equity, including tests for calibration, predictive parity, and error rate balance.
The third paper discusses a collaborative effort to understand and describe the landscape of contracted and community-based service programs that build on family strengths and protective factors to reduce maltreatment risk. The paper finds that service referrals and completion have been expanding, and discusses differences in service referral, engagement, and completion by geography and demographics.
Finally, in the fourth paper, we document how the application of the risk stratification model can be used to describe the current distribution of referrals to community-based services within risk categories and differences by racial/ethnic and gender subpopulations.
Each of these papers draws on routinely collected administrative data to advance understanding of the population served by Los Angeles DCFS, their needs and strengths, and their access to services, supports, and resources. These papers are particularly timely in light of the opportunities presented by the Family First Prevention Services Act (FFPSA) and resulting shifts toward keeping children in their home-of-origin by providing supportive services to families in need. This symposium has implications for service- and equity-related policy and practice in other jurisdictions.