Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered (...) as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections. (shrink)

The Intergovernmental Panel on Climate Change (IPCC) often qualifies its statements by use of probabilistic “likelihood” language. In this paper, I show that this language is not properly interpreted in either frequentist or Bayesian terms—simply put, the IPCC uses both kinds of statistics to calculate these likelihoods. I then offer a deflationist interpretation: the probabilistic language expresses nothing more than how compatible the evidence is with the given hypothesis according to some method that generates normalized scores. I end by drawing (...) some tentative normative conclusions. (shrink)