The cultural red king effect occurs when discriminatory bargaining practices emerge because of a disparity in learning speed between members of a minority and a majority. This effect has been shown to occur in some Nash Demand Game models and has been proposed as a tool for shedding light on the origins of sexist and racist discrimination in academic collaborations. This article argues that none of the three main strategies used in the literature to support the epistemic value of these models—structural similarity, empirical confirmation, and how-possibly explanations—provide strong support for this modeling practice in its present form.

Forber and Smead (2014) analyze how increasing the fitness benefits associated with prosocial behavior can increase the fitness of spiteful individuals relative to their prosocial counterparts, so that selection favors spite over prosociality. This poses a problem for the evolution of prosocial behavior: As the benefits of prosocial behavior increase, it becomes more likely that spite, not prosocial behavior, will evolve in any given population. In this article, I develop two game-theoretic models that, taken together, illustrate how synergistic costs and benefits may provide partial solutions to Forber and Smead’s paradox.

Mixed-methods research (MMR)—the combination of qualitative and quantitative data within the same design to strengthen causal inference—is gaining prominence in the social sciences but its benefits are contested. There remains confusion over which methods to mix and what is the point of mixing them. We argue that variety of evidence is what matters, not of data or methods, and that distinct epistemic principles underlie its added value for causal inference. The centrality of evidential variety also implies that strong causal pluralism is untenable as a foundation for MMR.

Like Austin’s “performatives,” some models are used not merely to represent but also to change their targets in various ways. This article argues that Austin’s analysis can inform model evaluation: If models are evaluated with respect to their adequacy-for-purpose, and if performativity can in some cases be regarded as a model purpose (a proposition that is defended, using mechanism design as an example), it follows that these models can be evaluated with respect to their “felicity,” that is whether their use has achieved this purpose. Finally, I respond to epistemic and ethical concerns that might block this conclusion.

How should one discount utility across time? The conventional wisdom in social science is that one should use an exponential discount function. Such a function is a representation of the axioms that provide a well-defined utility function plus a condition known as stationarity. Yet stationarity doesn’t really have much intuitive normative pull on its own. Here I try to cast it in a normative glow by deriving stationarity from two explicitly normative premises, both suggested by the philosophical thesis of temporal neutralism. Putting the argument in this form helps us better understand exponential discounting and challenges to it.

Recent advocates of “field philosophy” make the case that philosophy “needs to get outside more often”; alongside disciplinary modes of practice we should cultivate philosophical work that is consequential in real-world, practical terms. This takes a number of different forms, many of them captured by a framework for analyzing engaged philosophy of science proposed by Plaisance and Elliott. I draw on three examples of field-engaged philosophy of science that address the legacies of settler-colonialism archaeology to illustrate the promise of field philosophy.