Averaging probability judgments: Monte Carlo analyses of asymptotic diagnostic value

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Desirability bias in foresight: Consequences for decision quality based on Delphi results (2011, background): “Averaging subjective probabilities has proved to obtain better and more objective estimates and thus could eliminate or at least reduce the desirability bias [51,80].”
Using advice from multiple sources to revise and improve judgments (2007, background): “Gains of appreciable size may also obtain where there are low or moderate positive correlations among experts (Johnson et al., 2001).”
Combining probability forecasts (2010, background): “(2000), Wallsten and Diederich (2001) and Johnson et al. (2001). Despite their ubiquity, these issues have frequently been overlooked, with some of our own work (Sloughter et al., 2007) being one such example. Indeed, Fig. 7 of Sloughter et al. (2007) shows the typical S-shaped calibration curve for”
Group performance and decision making. (2004, background): “In addition, Johnson et al. (2001) empirically showed the accuracy of the average probability estimate to be robust over a number of conditions, even when individual estimates were not independent.”