Two powerful arguments have famously dominated the realism debate in philosophy of science: The No Miracles Argument (NMA) and the Pessimistic Meta-Induction (PMI). A standard response to the PMI is selective scientific realism (SSR), wherein only the working posits of a theory are considered worthy of doxastic commitment. Building on the recent debate over the NMA and the connections between the NMA and the PMI, I here consider a stronger inductive argument that poses a direct challenge for SSR: Because it (...) is sometimes exactly the working posits which contradict each other, i.e., that which is directly responsible for empirical success, SSR cannot deliver a general explanation of scientific success. (shrink)

This paper argues that there is an important connection between Inference to the Best Explanation and Bayesianism, in the medical context of the interplay between mechanisms and population studies. It is argued that the criteria for evaluating mechanistic evidence can be used in Inference to the Best Explanation and such use thereby increases the resilience of probabilities in a Bayesian framework. This point grows out of the emerging literature on evidence-based medicine and naturally strengthens McCain and Poston's proposal that explanatory (...) information is evidentially relevant. (shrink)

We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with unidentified statistical models. We end by (...) discussing the philosophical and methodological import of our result. (shrink)

:While Bayesian methods are widely used in economics and finance, the foundations of this approach remain controversial. In the contemporary statistical literature Bayesian Ockham’s razor refers to the observation that the Bayesian approach to scientific inference will automatically assign greater likelihood to a simpler hypothesis if the data are compatible with both a simpler and a more complex hypothesis. In this paper I will discuss a problem that results when Bayesian Ockham’s razor is applied to nested economic models. I will (...) argue that previous responses to the problem found in the philosophical literature are unsatisfactory and develop a novel reply to the problem. (shrink)