In evolutionary medicine, researchers characterize some outcomes as evolutionary mismatch. Mismatch problems arise as the result of organisms living in environments to which they are poorly adapted, typically as the result of some rapid environmental change. Depression, anxiety, obesity, myopia, insomnia, breast cancer, dental problems, and numerous other negative health outcomes have all been characterized as mismatch problems. The exact nature of evolutionary mismatch itself is unclear, however. This leads to a lack of clarity about the sorts of problems that (...) evolutionary mismatch can actually explain. Resolving this challenge is important not only for the evolutionary health literature, but also because the notion of evolutionary mismatch involves central concepts in evolutionary biology: fitness, evolution in changing environments, and so forth. In this paper, I examine two characterizations of mismatch currently in the literature. I propose that we conceptualize mismatch as a relation between an optimal environment and an actual environment. Given an organism and its particular physiology, the optimal environment is the environment in which the organism’s fitness is maximized: in other words, the optimal environment is that in which the organism’s fitness is as high as it can possibly be. The actual environment is the environment in which the organism actually finds itself. To the extent that there is a discordance between the organism’s actual and optimal environments, there is an evolutionary mismatch. In the paper, I show that this account of mismatch gives us the right result when other accounts fail, and provides useful targets for investigation. (shrink)

Consequentialism has been challenged on the grounds that it is too demanding. I will respond to the problem of demandingness differently from previous accounts. In the first part of the paper, I argue that consequentialism requires us to distinguish the justification of an act \ from the justification of an act \, where \ is an act of praise or blame. In the second part of the paper, I confront the problem of demandingness. I do not attempt to rule out (...) the objection; instead, I argue that if certain plausible empirical claims about moral motivation are true, we morally ought not to blame people for failing to meet certain very demanding obligations. With this theory, we create a space in consequentialism for intuitions questioning the plausibility of demanding obligations. I conclude the paper by showing that separate justifications for \ and \ may also give us a theoretical niche for intuitions about supererogation. (shrink)

The Computational History of Philosophy of Science Dataset aims to be a comprehensive set of article and book chapter metadata for philosophy of science. The dataset covers the full run of over 40 journals and 3 major book series in the field. An automated author disambiguation script is used to construct canonical names for each author, and a combination of gender attribution methods is used to attribute the gender of each author. The full code used to generate the dataset is (...) available at [URL not allowed]. See the file data_dictionary.txt for data dictionary and additional information. (shrink)