Analysis of two key ways of characterizing genes—as causes of phenotypic effects and as genomic DNA sequences—has yielded widespread pessimism that they can be united in a coherent gene concept. This raises important questions about the epistemology of genomic research: If analysis of a genome sequence cannot yield information about genes defined both in terms of their products and their DNA sequence, then what could we learn from it? I investigate basic tools of genomic analysis, argue that they do not reflect the application of either gene concept, and clarify how we learn from genomic research.

The problem of how to make optimal choices in the face of risk (or uncertainty) arises in both economics/decision theory and also evolutionary biology; in the former, ‘optimal’ means utility maximizing, while in the latter it means fitness maximizing. This article explores the links, thematic and formal, between the economic and evolutionary theories of optimal choice in risky situations, with particular reference to the relationship between utility and fitness. It is argued that the link is strongest between evolution and ‘nonexpected’ utility theory, rather than traditional expected utility theory.

In a previous article, we have demonstrated by a general phase space argument that a Maxwellian Demon is compatible with statistical mechanics. In this article, we show how this idea can be put to work in the prevalent model of the Demon, namely, a particle-in-a-box, used, for example, by Szilard and Bennett. In the literature, this model is used in order to show that a Demon is incompatible with statistical mechanics, either classical or quantum. However, we show that a detailed phase space analysis of this model illustrates that a Maxwellian Demon is compatible with statistical mechanics.

Cosmologists often use certain global properties to exclude “physically unreasonable” cosmological models from serious consideration. But, on what grounds should these properties be regarded as physically unreasonable if we cannot rule out, even with a robust type of inductive reasoning, the possibility of the properties obtaining in our own universe?

Why do gases reach equilibrium when left to themselves? The canonical answer, originally proffered by Boltzmann, is that the systems have to be ergodic. This answer is now widely regarded as flawed. We argue that some of the main objections in particular arguments based on the Kolmogorov-Arnold-Moser theorem and the Markus-Meyer theorem are beside the point. We then argue that something close to Boltzmann’s proposal is true: gases behave thermodynamic-like if they are epsilon-ergodic, that is, ergodic on the phase space except for a small region of measure epsilon. This answer is promising because there is evidence that relevant systems are epsilon-ergodic.

The received view in philosophy of biology is that there is a well-understood, philosophically rigorous account of information—causal information. I argue that this view is mistaken. Causal information is fatally undermined by misinterpretations and conflations between distinct independent accounts of information. As a result, philosophical arguments based on causal information are deeply flawed. I end by briefly considering what a correct application of the relevant accounts of information would look like in the biological context.

Several philosophers of science have argued that epistemically rational individuals might form epistemically irrational groups and that, conversely, rational groups might be composed of irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they entail that methodological prescriptions for scientific communities and those for individual scientists are logically independent. We defend the inconsistency thesis by characterizing four criteria for epistemic rationality and then proving that, under said criteria, individuals will be judged rational when groups are not and vice versa. We then explain the implications of our results for descriptive history of science and normative epistemology.

This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, we briefly describe some promising future projects inspired by our account.

The theory of mind (ToM) deficit associated with autism spectrum disorder has been a central topic in the debate about the modularity of the mind. In a series of papers, Philip Gerrans and Valerie Stone argue that positing a ToM module does not best explain the deficits exhibited by individuals with autism. In this article, I first criticize Gerrans and Stone's account. Second, I discuss various studies of individuals with autism and argue that they are best explained by positing a higher-level, domain-specific ToM module.

I offer an explanation of why inertial and gravitational mass are equal in Newtonian gravitation. I then argue that this is an example of a kind of explanation that is not captured by standard philosophical accounts of scientific explanation. Moreover, this form of explanation is particularly important, at least in physics, because demands for this kind of explanation are used to motivate and shape research into the next generation of physical theories. I suggest that explanations of the sort I describe reveal something important about one way in which physical theories may be related diachronically.

The phenomenon of broken spacetime symmetry in the quantum theory of infinite systems seems to point toward an unorthodox ontology. The standard conception of the physical meaning of these symmetries, as changes in coordinates, conflicts with the apparent physical inequivalence of symmetry-related states. I argue that this apparent conflict is an artifact of a subtle error in the extant account of physical equivalence due to Halvorson and Clifton.

This article presents and argues for modal structuralism, which is loosely derived from a position described by Wilfrid Sellars. Modal structuralism holds that a fundamental property is identified by the role it plays in the structure of possibilities. It implies necessitarianism about laws, which holds that at least some laws of nature are metaphysically necessary. The argument for these positions derives from the following assumptions: the principle of the identity of indiscernible properties and a modest antiquidditism. These assumptions are weaker than those of causal structuralism, which is a closely related view.

In practice, scientists must convey data in a “representational style” (e.g., as a numerical array or visual representation). Various authors seek to explain the epistemic role of scientific visual representation in terms of formal conventions (e.g., Goodman, Perini, and Kulvicki). Goodman also tends to dismiss the epistemic relevance of human cognition. My position is that visual conventions are nonarbitrary, in that they play to scientists’ cognitive abilities and limitations. My account draws on Perini's formal analysis, scientific case studies, and empirical literature on global pattern detection in neurotypicals, autistics, and dyslexics.

I argue that a phenotypic trait can be an adaptation to a particular environmental condition, as against others, only if the environmental condition and the phenotype interactively cause fitness. Models of interactive environmental causes of fitness generally require that environments be individuated by explicit representation rather than by measures of environmental quality, although the latter understanding of ‘environment’ is more prominent in the philosophy of biology. Hence, talk of adaptations to some but not other environmental conditions relies on conceptions of ‘environment’ importantly different from that commonly presupposed in philosophy of biology.

Although many philosophers have employed the distinction between “direct” and “indirect” roles for values in science, I argue that it merits further clarification. The distinction can be formulated in several ways: as a logical point, as a distinction between epistemic attitudes, or as a clarification of different consequences associated with accepting scientific claims. Moreover, it can serve either as part of a normative ideal or as a tool for policing how values influence science. While various formulations of the distinction may (with further clarification) contribute to a normative ideal, they have limited effectiveness for regulating how values influence science.

Leuridan argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and he advocates Mitchell's pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong among mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain.

Is there anything more to temperature than the ordering of things from colder to hotter? Are there also facts, for example, about how much hotter (twice as hot, three times as hot, etc.) one thing is than another? There certainly are, but the only strong justification for this claim comes from statistical mechanics. What we knew about temperature before the advent of statistical mechanics (what we knew about it from thermodynamics) provided only weak reasons to believe it.

Recently Albert and Hemmo and Shenker have argued that, contrary to what is sometimes suggested, Liouville's theorem does not prohibit a Maxwellian demon from operating but merely places certain restrictions on its ability to operate. There are two main claims made in this article. First, that the restrictions Liouville's theorem places on Maxwell's demon's ability to operate depend on which notion of entropy one adopts. Second, that when one operates with the definition of entropy that is usual in this debate, the restrictions put on Maxwell's demon are not even as severe as Albert and Hemmo and Shenker argue.

This article encourages the use of explicit methods in linguistics by attempting to estimate the size of a linguistic data set. Such estimations are difficult because redundant data can easily pad the data set. To address this, I offer some explicit operationalizations of the data and their features. For linguistic data, negative associations do not indicate true redundancy, and yet for many measures they can be mathematically impossible to ignore. It is proven that this troublesome phenomenon has positive Lebesgue measure and is monotonically increasing and that these two features hold robustly in four different ways.