In this article, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa.

Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial to any satisfactory account of explanation.

The concept of levels of organization is prominent in science and central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of universal and discrete hierarchical levels, and these undermine implications commonly ascribed to hierarchical organization. We suggest the concept of scale as a promising alternative. Investigating causal processes at different scales allows for a notion of quasi levels that avoids the difficulties inherent in the classic concept of levels. Our primary focus is ecology, but we suggest how the results generalize to other invocations of hierarchy in science and philosophy of science.

A common argument against explanatory reductionism is that higher-level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher-level explanations are more general than their lower-level alternatives or that higher-level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation.

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, optimality and game-theoretic models best explain some central types of evolutionary phenomena.