These theoretical developments may look attractive, but the fact is that they mostly enjoy a cult status among philosophers of statistics and that they have not moved the statistician in the street. On the other hand, standard Bayesian statistics has seen a steep rise in popularity over the past decade or so, owing to the availability of good software and numerical approximation methods. And most of the practical use of Bayesian statistics is more or less insensitive to the potentially subjective aspects of the statistical results, employing uniform priors as a neutral starting point for the analysis and relying on the afore-mentioned convergence results to wash out the remaining subjectivity (cf. Gelman and Shalizi 2013). However, this practical attitude of scientists towards modelling should not be mistaken for a principled answer to the questions raised in the philosophy of statistics (see Morey et al 2013).