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Philosophers of science and metascientists alike typically model scientists’ behavior as driven by credit maximization. In this article I argue that this modeling assumption cannot account for how scientists have a default level of trust in each other’s assertions. The normative implication of this is that science policy should not focus solely on incentive reform.

Scholars belong to multiple communities of credit simultaneously. When these communities disagree about a scholarly achievement’s credit assignment, this raises a puzzle for decision and game theoretic models of credit seeking in science. The reference class problem for credit valuation in science is the problem of determining to which of an agent’s communities—which reference class—credit determinations should be indexed for an act under some state of nature. Solving this problem requires developing rich, mutually informed theories of community and credit that are sensitive to the structure and status systems of complex, heterogeneous scholarly networks.

Kitcher has proposed an ideal-theory account—well-ordered science (WOS)—of the collective good that science’s research agenda should promote. Against criticism regarding WOS’s action guidance, Kitcher has advised critics not to confuse substantive ideals and the ways to arrive at them, and he has defended WOS as a necessary and useful ideal for science policy. I provide a distinction between two types of ideal theories that helps clarifying WOS’s elusive nature. I use this distinction to argue that the action-guidance problem that WOS faces remains even under the aims/means distinction because the WOS’s failure is more basic than critics have suggested.

In a recent paper, Inmaculada de Melo-Martin and Kristen Intemann consider several ways in which, from the perspective of the argument from inductive risk, ethical and political values might "sometimes [be] necessary in decisions at the core of scientific reasoning." Specifically, they consider whether these kinds of values are logically, epistemically, pragmatically, or ethically necessary; and argue that there are significant conceptual problems in each case. In this comment, using regulatory uses of high-throughput toxicology at the US Environmental Protection Agency [EPA] as a case study, I suggest some clarifications and corrections to some of their claims about pragmatic necessity. I conclude that, while an inductive risk framework has some significant limitations, it is still conceptually and rhetorically valuable.

The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? I argue on the basis of a game-theoretic model that rational credit-maximizing scientists will in many cases conform to the norm. This means that the origins and persistence of the communist norm can be explained even in the absence of a social contract or enforcement, contrary to recent work by Michael Strevens but adding to previous work emphasizing the benefits of the incentive structure created by the priority rule.

On many science-related policy questions, the public is unable to make informed decisions, because of its inability to make use of knowledge obtained by scientists. Philip Kitcher and James Fishkin have both suggested therefore that on certain science-related issues, public policy should not be decided on by actual democratic vote, but should instead conform to the public’s counterfactual informed democratic decision (CIDD). Indeed, this suggestion underlies Kitcher’s specification of an ideal of a well-ordered science. This article argues that this suggestion misconstrues the normative significance of CIDDs. At most, CIDDs might have epistemic significance, but no authority or legitimizing force.

Recent efforts to argue that nonepistemic values have a legitimate role to play in assessing scientific models, theories, and hypotheses typically either reject the distinction between epistemic and nonepistemic values or incorporate nonepistemic values only as a secondary consideration for resolving epistemic uncertainty. Given that scientific representations can legitimately be evaluated not only based on their fit with the world but also with respect to their fit with the needs of their users, we show in two case studies that nonepistemic values can play a legitimate role as factors that override epistemic considerations in assessing scientific representations for practical purposes.

We argue that the analysis of cognitive attitudes should play a central role in developing more sophisticated accounts of the proper roles for values in science. First, we show that the major recent efforts to delineate appropriate roles for values in science would be strengthened by making clearer distinctions among cognitive attitudes. Next, we turn to a specific example and argue that a more careful account of the distinction between the attitudes of belief and acceptance can contribute to a better understanding of the proper roles for values in a case study from paleoanthropology.