 On the other hand, there is another sense in which Bayesian modelling has been regarded as too nuanced. It seems to be psychologically unrealistic to portray humans (rather than ideally rational agents) as having degrees of belief that are infinitely precise real numbers. Thus, there have been various attempts to ‘humanize’ Bayesianism, and this line of research is gaining momentum. For example, there has been a flourishing study of imprecise probability and imprecise decision theory, in which credences need not be precise numbers—for example, they could be sets of numbers, or intervals. See http://www.sipta.org/ for up-to-date research in this area. This resonates with recent work on whether imprecise probabilities are rationally required—Hájek and Smithson (2012) on the pro side, Schoenfield (2017) on the con side. The debate continues. 