Calibration and the Aggregation of Probabilities
指出Morris提出的乘法规则在聚合决策者与专家概率时，因未考虑两者依赖关系而存在缺陷，并强调正确校准专家信息是解决问题的关键。
In order to avoid the task of assessing a complicated likelihood function, Morris uses an axiomatic approach to develop a multiplicative rule for aggregating a decision maker's and an expert's probabilities. An essential shortcoming of the multiplicative rule is that it does not allow the decision maker to model his beliefs about the dependence between his assessment and the expert's. The root of the problem lies in the fact that the decision maker must calibrate the expert's information. When the calibration is done properly, the decision maker is forced to tackle the task which Morris proposes to avoid.