Different why-questions emerge under different contexts and require different information in order to be addressed. Hence a relevance relation can hardly be invariant across contexts. However, what is indeed common under any possible context is that all explananda require scientific information in order to be explained. So no scientific information is in principle explanatorily irrelevant, it only becomes so under certain contexts. In view of this, scientific thought experiments can offer explanations, should we analyze their representational strategies. Their representations involve (...) empirical as well as hypothetical statements. I call this the “representational mingling” which bears scientific information that can explain events. Buchanan’s thought experiment from constitutional economics is examined to show how mingled representations explain. (shrink)

Many philosophers are baffled by necessity. Humeans, in particular, are deeply disturbed by the idea of necessary laws of nature. In this paper I offer a systematic yet down to earth explanation of necessity and laws in terms of invariance. The type of invariance I employ for this purpose generalizes an invariance used in meta-logic. The main idea is that properties and relations in general have certain degrees of invariance, and some properties/relations have a stronger degree of invariance than others. (...) The degrees of invariance of highly-invariant properties are associated with high degrees of necessity of laws governing/describing these properties, and this explains the necessity of such laws both in logic and in science. This non-mysterious explanation has rich ramifications for both fields, including the formality of logic and mathematics, the apparent conflict between the contingency of science and the necessity of its laws, the difference between logical-mathematical, physical, and biological laws/principles, the abstract character of laws, the applicability of logic and mathematics to science, scientific realism, and logical-mathematical realism. (shrink)

The central motivation behind the scientific realism debate is explaining the impressive success of scientific theories. The debate has been dominated by two rival types of explanations: the first relies on some sort of static, referentially transparent relationship between the theory and the unobservable world, such as truthlikeness, representation, or structural similarity; the second relies on no robust relationship between the theory and unobservable reality at all, and instead draws on predictive similarity and the stringent methodology of science to explain (...) success. I argue that this is a false dichotomy, at least insofar as dynamical theories are concerned. The best explanation of the success of dynamical theories, I argue, must appeal to a robust but referentially opaque theory–world relation. The dynamical notion of ‘tracking’ fulfills this promise. I formulate a modified no miracles argument that is liberated from the false dichotomy and show how tracking responds to the modified argument. (shrink)

Biological and cognitive sciences rely heavily on the idea of information transmitted between natural events or processes. This paper critically assesses some current philosophical views of natural information and defends a view of natural information as Nomic and Factive. Dretske offered a Factive view of information, and recent work on the topic has tended to reject this aspect of his view in favor of a non-Factive, probabilistic approach. This paper argues that the reasoning behind this move to non-Factivity is flawed (...) and mixes up different problems with Dretske’s original view. I show that one of these problems—strictness—has to do with Nomicity rather than Factivity. The other problem—reference class ambiguity—is not solvable just in terms of a theory of natural information. On the Dretske-inspired view I defend, natural information is Factive and Nomic but is insufficient to determine the cognitive or biological content of a natural process. In sum I present an examination what natural information is and what role it can play in our understanding of living and thinking things. (shrink)

Non‐Humean theories of natural necessity invoke modally‐laden primitives to explain why nature exhibits lawlike regularities. However, they vary in the primitives they posit and in their subsequent accounts of laws of nature and related phenomena (including natural properties, natural kinds, causation, counterfactuals, and the like). This article provides a taxonomy of non‐Humean theories, discusses influential arguments for and against them, and describes some ways in which differences in goals and methods can motivate different versions of non‐Humeanism (and, for that matter, (...) Humeanism). In short, this article provides an introduction to non‐Humeanism concerning the metaphysics of laws of nature and natural necessity. (shrink)

This paper discusses some procedures developed in recent work in machine learning for inferring causal direction from observational data. The role of independence and invariance assumptions is emphasized. Several familiar examples including Hempel’s flagpole problem are explored in the light of these ideas. The framework is then applied to problems having to do with explanatory direction in non-causal explanation.