Theories of scientific rationality typically pertain to belief. In this paper, the author argues that we should expand our focus to include motivations as well as belief. An economic model is used to evaluate whether science is best served by scientists motivated only by truth, only by credit, or by both truth and credit. In many, but not all, situations, scientists motivated by both truth and credit should be judged as the most rational scientists.

Some scientists are happy to follow in the footsteps of others; some like to explore novel approaches. It is tempting to think that herein lies an epistemic division of labor conducive to overall scientific progress: the latter point the way to fruitful areas of research, and the former more fully explore those areas. Weisberg and Muldoon’s model, however, suggests that it would be best if all scientists explored novel approaches. I argue that this is due to implausible modeling choices, and (...) I present an alternative ‘epistemic landscape’ model that demonstrates the alleged benefits from division of labor, with one restriction. (shrink)

Scientific realists have suggested that changes in our scientific communities over the course of their history have rendered those communities progressively less vulnerable to the problem of unconcieved alternatives over time. I argue in response not only that the most fundamental historical transformations of the scientific enterprise have generated steadily mounting obstacles to revolutionary, transformative, or unorthodox scientific theorizing, but also that we have substantial independent evidence that the institutional apparatus of contemporary scientific inquiry fosters an exceedingly and increasingly theoretically (...) conservative form of that inquiry. I conclude that contemporary scientific communities are actually more vulnerable to the problem of unconceived alternatives than their historical predecessors, and I briefly suggest how we might seek to pursue scientific inquiry in a less theoretically conservative way. (shrink)

Those who comment on modern scientific institutions are often quick to praise institutional structures that leave scientists to their own devices. These comments reveal an underlying presumption that scientists do best when left alone—when they operate in what we call the ‘scientific state of nature’. Through computer simulation, we challenge this presumption by illustrating an inefficiency that arises in the scientific state of nature. This inefficiency suggests that one cannot simply presume that science is most efficient when institutional control is (...) absent. In some situations, actively encouraging unpopular, risky science would improve scientific outcomes. 1 Introduction2 Scientists and Bandits3 Choosing an ϵ4 Structure of Communication5 Discussion. (shrink)

Industry is a major source of funding for scientific research. There is also a growing concern for how it corrupts researchers faced with conflicts of interest. As such, the debate has focused on whether researchers have maintained their integrity. In this article we draw on both the history of medicine and formal modeling to argue that given methodological diversity and a merit-based system, industry funding can bias a community without corrupting any particular individual. We close by considering a policy solution (...) that may seem to promote unbiased inquiry but that actually exacerbates the problem without additional restrictions. (shrink)

The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? Michael Strevens provides a partial answer to these questions by showing that scientists should be willing to sign a social contract that mandates sharing. However, he also argues that it is not in an individual credit-maximizing scientist's interest to follow this norm. I argue against Strevens that individual scientists can rationally conform to the communist norm, even (...) in the absence of a social contract or other ways of socially enforcing the norm, by proving results to this effect in a game-theoretic model. This shows that the incentives provided to scientists through the priority rule are sufficient to explain both the origins and the persistence of the communist norm, adding to previous results emphasizing the benefits of the incentive structure created by the priority rule. (shrink)

Many scientific models lack an established representation relation to actual targets and instead refer to merely possible processes, background conditions, and results. This article shows how such models can be appraised. On the basis of the discussion of how-possibly explanations, five types of learning opportunities are distinguished. For each of these types, an example—from economics, biology, psychology, and sociology—is discussed. Contexts and purposes are identified in which the use of a model offers a genuine opportunity to learn. These learning opportunities (...) offer novel justifications for modeling practices that fall between the cracks of standard representationalist appraisals of models. (shrink)

The book presents a new way of understanding Darwinism and evolution by natural selection, combining work in biology, philosophy, and other fields.