| Abstract: | The volume and complexity of information in child protection cases means that there can be an overwhelming number of factors which seem pertinent to decision-making but which obscure any pattern within it. This paper examines the applicability of a technique known as computer learning to the area of risk assessment in order to extract any underlying patterns. The paper proposes first that there are a few key interrelated, broad-level concepts used to assess and thereby classify risk. These can be used as the basis for producing a set of rules under which a social work team operates. The classification of risk made by one social work team on 20 child protection cases was analysed to find underlying patterns of their decision-making. These patterns are presented in the form of ‘decision trees’, as a way of illustrating the group's past experience in assessing risk. The results are evaluated in terms of the complexity and plausibility of the decision tree produced. © 1998 John Wiley & Sons, Ltd. |
