Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the ‘Black Box’ of Machine Learning

@article{Gillingham2016PredictiveRM,
  title={Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the ‘Black Box’ of Machine Learning},
  author={Philip Gillingham},
  journal={British Journal of Social Work},
  year={2016},
  volume={46},
  pages={1044 - 1058}
}
  • P. Gillingham
  • Published 8 April 2015
  • Computer Science, Medicine
  • British Journal of Social Work
Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can ‘learn’, it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and… 
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