In this research review, Dr. Bart Klika, our Chief Research and Strategy Officer, goes over the topic of predictive analytics and the various techniques that are being used in child abuse prevention efforts in certain cities and regions across the United States. Please note that this review is not intended to be an endorsement of any of these techniques. Instead, this review is intended to be a simple introduction into the topic of predictive analytics, risk-terrain modeling, as well as some examples of the challenges and opportunities of these techniques. Click the video below to watch the research review and then follow the links at the bottom to review the research into predictive analytics yourself.
References
- Can an Algorithm Tell When Kids are in Danger?—New York Times
- Automating Inequality: using algorithms to create a modern “digital poor-house”—Book Review
- Allegheny County Report—Book Review
- Risk assessment and decision making in child protective services: Predictive risk modeling in context—Cuccaro-Alamin et al., 2017
- In Search of a Silver Bullet: Child Welfare’s Embrace of Predictive Analytics—Church & Fairchild, 2017
- Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the ‘Black Box’ of Machine Learning—Gillingham, 2016
- Injury and Mortality Among Children Identified as at High Risk of Maltreatment—Vaithianthan et al., 2018
- Risk terrain modeling predicts child maltreatment—Daley et al., 2016
- Risk Terrain Modeling for Spatial Risk Assessment—Caplan et al., 2015