There is growing interest in understanding and eliciting division of labor within groups of scientists. This paper illustrates the need for this division of labor through a historical example, and a formal model is presented to better analyze situations of this type. Analysis of this model reveals that a division of labor can be maintained in two different ways: by limiting information or by endowing the scientists with extreme beliefs. If both features are present however, cognitive diversity is maintained indefinitely, (...) and as a result agents fail to converge to the truth. Beyond the mechanisms for creating diversity suggested here, this shows that the real epistemic goal is not diversity but transient diversity. (shrink)

This paper discusses the epistemic import of highly abstract and simplified theoretical models using Thomas Schelling’s checkerboard model as an example. We argue that the epistemic contribution of theoretical models can be better understood in the context of a cluster of models relevant to the explanatory task at hand. The central claim of the paper is that theoretical models make better sense in the context of a menu of possible explanations. In order to justify this claim, we introduce a distinction (...) between causal scenarios and causal mechanism schemes. These conceptual tools help us to articulate the basis for modelers’ intuitive confidence that their models make an important epistemic contribution. By focusing on the role of the menu of possible explanations in the evaluation of explanatory hypotheses, it is possible to understand how a causal mechanism scheme can improve our explanatory understanding even in cases where it does not describe the actual cause of a particular phenomenon. (shrink)

David Hull accounts for the success of science in terms of an invisible hand mechanism, arguing that it is difficult to reconcile scientists' self-interestedness or their desire for recognition with traditional philosophical explanations for the success of science. I argue that we have less reason to invoke an invisible hand mechanism to explain the success of science than Hull implies, and that many of the practices and institutions constitutive of science are intentionally designed by scientists with an eye to realizing (...) the very goals that Hull believes need to be explained by reference to an invisible hand mechanism. Thus, I reduce the scope of Hull's invisible hand explanation and supplement it by appealing to a hidden hand explanation. (shrink)

Because of its complexity, contemporary scientific research is almost always tackled by groups of scientists, each of which works in a different part of a given research domain. We believe that understanding scientific progress thus requires understanding this division of cognitive labor. To this end, we present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to climb uphill in this landscape, where elevation represents the significance of the (...) results discovered by employing a research approach. We consider three different search strategies scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community as a whole influence their actions. This is compared with two social research strategies, which we call the follower and maverick strategies. Followers are biased towards what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform both of the other strategies. Finally, we show that in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains. (shrink)

Science's priority rule rewards those who are first to make a discovery, at the expense of all other scientists working towards the same goal, no matter how close they may be to making the same discovery. I propose an explanation of the priority rule that, better than previous explanations, accounts for the distinctive features of the rule. My explanation treats the priority system, and more generally, any scheme of rewards for scientific endeavor, as a device for achieving an allocation of (...) resources among different research programs that provides as much benefit as possible to society. I show that the priority system is especially well suited to finding an efficient allocation of resources in those situations, characteristic of scientific inquiry, in which any success in an endeavor subsequent to the first success brings little additional benefit to society. (shrink)

The system for awarding credit in science—the priority rule—functions, I have proposed elsewhere, to bring about something close to a socially optimal distribution of scientists among scientific research programs. If all goes well, then, potentially fruitful new ideas will be explored, unpromising ideas will be ignored, and fashionable but oversubscribed ideas will be deprived of further resources. Against this optimistic background, the present paper investigates the ways in which things might not go so well, that is, ways in which the (...) priority rule might fail to realize its full potential as an incentive for scientists to work on the right things. Several possible causes of herding—an outcome in which a single research program ends up with a number of researchers well in excess of the optimum—are considered. (shrink)

The somatic mutation theory (SMT) of cancer has been and remains the prevalent theory attempting to explain how neoplasms arise and progress. This theory proposes that cancer is a clonal, cell‐based disease, and implicitly assumes that quiescence is the default state of cells in multicellular organisms. The SMT has not been rigorously tested, and several lines of evidence raise questions that are not addressed by this theory. Herein, we propose experimental strategies that may validate the SMT. We also call attention (...) to an alternative theory of carcinogenesis, the tissue organization field theory (TOFT), which posits that cancer is a tissue‐based disease and that proliferation is the default state of all cells. Based on epistemological and experimental evidence, we argue that the TOFT compellingly explains carcinogenesis, while placing it within an evolutionarily relevant context.magnified imagemagnified imageAna Soto and Carlos Sonnenschein are at Tufts University School of Medicine, Boston, MA, USA. (shrink)

My main aim in this paper is to show that influential antireductionist arguments such as Fodor's, Kitcher's, and Dupré's state stronger conclusions than they actually succeed in establishing. By putting to the fore the role of metaphysical presuppositions in these arguments, I argue that they are convincing only as 'temporally qualified argument', and not as 'generally valid ones'. I also challenge the validity of the strategy consisting in drawing metaphysical lessons from the failure of reductionist programmes. What most of these (...) antireductionist standpoints have in common is a pretension to methodological imports. I conclude by explaining why, in order to remain relevant for scientific practice, antireductionist arguments should stay clear of metaphysics, for the latter, I argue, does not mix well with a taste for methodological prescriptions. (shrink)

Scientific research is almost always conducted by communities of scientists of varying size and complexity. Such communities are effective, in part, because they divide their cognitive labor: not every scientist works on the same project. Philip Kitcher and Michael Strevens have pioneered efforts to understand this division of cognitive labor by proposing models of how scientists make decisions about which project to work on. For such models to be useful, they must be simple enough for us to understand their dynamics, (...) but faithful enough to reality that we can use them to analyze real scientific communities. To satisfy the first requirement, we must employ idealizations to simplify the model. The second requirement demands that these idealizations not be so extreme that we lose the ability to describe real-world phenomena. This paper investigates the status of the assumptions that Kitcher and Strevens make in their models, by first inquiring whether they are reasonable representations of reality, and then by checking the models' robustness against weakenings of these assumptions. To do this, we first argue against the reality of the assumptions, and then develop a series of agent-based simulations to systematically test their effects on model outcomes. We find that the models are not robust against weakenings of these idealizations. In fact we find that under certain conditions, this can lead to the model predicting outcomes that are qualitatively opposite of the original model outcomes. (shrink)

When should a scientific community be cognitively diverse? This article presents a model for studying how the heterogeneity of learning heuristics used by scientist agents affects the epistemic efficiency of a scientific community. By extending the epistemic landscapes modeling approach introduced by Weisberg and Muldoon, the article casts light on the micro-mechanisms mediating cognitive diversity, coordination, and problem-solving efficiency. The results suggest that social learning and cognitive diversity produce epistemic benefits only when the epistemic community is faced with problems of (...) sufficient difficulty. (shrink)

In epistemology and the philosophy of science, there has been an increasing interest in the social aspects of belief acquisition. In particular, there has been a focus on the division of cognitive labor in science. This essay explores several different models of the division of cognitive labor, with particular focus on Kitcher, Strevens, Weisberg and Muldoon, and Zollman. The essay then shows how many of the benefits of the division of cognitive labor flow from leveraging agent diversity. The essay concludes (...) by examining the benefits and burdens of diversity, particularly in the evaluative diversity that can be found in interdisicplinary science. (shrink)

In recent cancer research, strong and apparently conflicting epistemological stances have been advocated by different research teams in a mist of an ever-growing body of knowledge ignited by ever-more perplexing and non-conclusive experimental facts: in the past few years, an 'organicist' approach investigating cancer development at the tissue level has challenged the established and so-called 'reductionist' approach focusing on disentangling the genetic and molecular circuitry of carcinogenesis. This article reviews the ways in which 'organicism' and 'reductionism' are used and opposed (...) in this context, with an aim at clarifying the debate. Methodological, epistemological and ontological implications of both approaches are discussed. We argue that the 'organicist/reductionist' opposition in the present case of carcinogenesis is more a matter of diverging heuristics than a claim about theoretical or ontological (ir)reducibility. As a matter of fact, except for the downward causation claim, which we question, we argue that the organicist arguments are compatible with the reductionist approach. Moreover, we speculate that both approaches, which currently focus on specific entities i.e., genes versus tissues, will need to shift their conceptual frameworks to studying complex arrays of relationships potentially ranging over several levels of entities, as is the case with 'systems biology'. (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)

In this paper, I explore the relationship between epistemic rationality and instrumental rationality, and I attempt to delineate their respective roles in typical instances of theoretical reasoning. My primary concern is with the instrumentalist conception of epistemic rationality: the view that epistemic rationality is simply a species of instrumental rationality, viz. instrumental rationality in the service of one's cognitive or epistemic goals. After sketching the relevance of the instrumentalist conception to debates over naturalism and 'the ethics of belief', I argue (...) that, despite enjoying considerable popularity among both epistemologists and philosophers of science, it is ultimately indefensible. Having thus argued for the distinctness of epistemic and instrumental rationality, I attempt to clarify the role played by each in typical instances of theoretical reasoning. I suggest that being theoretically rational--that is, being proficient with respect to theoretical reasoning--is best construed as a hybrid virtue, inasmuch as it involves manifesting sensitivity to two very different kinds of reasons. (shrink)

Exploratory inquiry has difficulty attracting research funding because funding agencies have little sense of how to detect good science in exploratory contexts. After documenting and explaining the focus on hypothesis testing among a variety of institutions responsible for distinguishing between good and bad science, I analyze the NIH grant review process. I argue that a good explanation for the focus on hypothesis testing—at least at the level of science funding agencies—is the fact that hypothesis-driven research is relatively easy to appraise. (...) I then explore one method by which we might gauge the epistemic merits of different styles of inquiry. (shrink)

Current theories of the division of cognitive labor are confined to the “context of justification,” assuming exogenous theories. But new theories are made from the same labor that is used for developing existing theories, and if none of this labor is ever allocated to create new alternatives, then scientific progress is impossible. A unified model is proposed in which theories are no longer given but a function of the division of labor in the model itself. The interactions of individuals balancing (...) the exploitation of existing theories and the exploration of new theories results in a robust cyclical pattern. (shrink)

Computer simulation of an epistemic landscape model, modified to include explicit representation of a centralized funding body, show the method of funding allocation has significant effects on communal trade-off between exploration and exploitation, with consequences for the community’s ability to generate significant truths. The results show this effect is contextual, and depends on the size of the landscape being explored, with funding that includes explicit random allocation performing significantly better than peer-review on large landscapes. The paper proposes a way of (...) incorporating external institutional factors in formal social epistemology, and offers a way of bringing such investigations to bear on current research policy questions. (shrink)

Computer simulation of an epistemic landscape model, modified to include explicit representation of a centralized funding body, show the method of funding allocation has significant effects on communal trade-off between exploration and exploitation, with consequences for the community’s ability to generate significant truths. The results show this effect is contextual, and depends on the size of the landscape being explored, with funding that includes explicit random allocation performing significantly better than peer review on large landscapes. The article proposes a way (...) of incorporating external institutional factors in formal social epistemology, and offers a way of bringing such investigations to bear on current research policy questions. 1Introduction2Theoretical Background3Model Description4Simulation Details 4.1Simulating the epistemic landscape4.2Simulating agents4.3Simulating communal knowledge4.4Simulating funding strategies4.5Simulating merit dynamics5Results and Discussion 5.1Experiment 1: The winner-takes-it-all mechanism only5.2Experiment 2: All dynamic mechanisms5.3Experiment 3: Adding a new funding mechanism 5.4Experiment 4: Varying the degree of myopia5.5Experiment 5: Variability of individual epistemic gain5.6Experiment 6: Likelihood of renewal6Discussion7Conclusion. (shrink)

This article examines two questions about scientists’ search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, “Epistemic Landscapes and the Division of Cognitive Labor”, that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors that led (...) to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments. (shrink)

Rational drug design is a method for developing new pharmaceuticals that typically involves the elucidation of fundamental physiological mechanisms. It thus combines the quest for a scientific understanding of natural phenomena with the design of useful technology and hence integrates epistemic and practical aims of research and development. Case studies of the rational design of the cardiovascular drugs propranolol, captopril and losartan provide insights into characteristics and conditions of this integration. Rational drug design became possible in the 1950s when theoretical (...) knowledge of drug-target interaction and experimental drug testing could interlock in cycles of mutual advancement. The integration does not, however, diminish the importance of basic research for pharmaceutical development. Rather, it can be shown that still in the 1990s, linear processes of innovation and the close combination of practical and epistemic work were interdependent. (shrink)

Rational drug design is a method for developing new pharmaceuticals that typically involves the elucidation of fundamental physiological mechanisms. It thus combines the quest for a scientific understanding of natural phenomena with the design of useful technology and hence integrates epistemic and practical aims of research and development. Case studies of the rational design of the cardiovascular drugs propranolol, captopril and losartan provide insights into characteristics and conditions of this integration. Rational drug design became possible in the 1950s when theoretical (...) knowledge of drug-target interaction and experimental drug testing could interlock in cycles of mutual advancement. The integration does not, however, diminish the importance of basic research for pharmaceutical development. Rather, it can be shown that still in the 1990s, linear processes of innovation and the close combination of practical and epistemic work were interdependent. (shrink)

Epistemology has historically focused on individual inquirers conducting their private intellectual affairs independently of one another. As a descriptive matter, however, what people believe and know is largely a function of their community and culture, narrowly or broadly construed. Most of what we believe is influenced, directly or indirectly, by the utterances and writings of others. So social epistemology deserves at least equal standing alongside the individual sector of epistemology.

There are now several proposals for introducing random elements into the process of funding allocation for research, and some initial implementation of this policy by funding bodies. The proposals have been supported on efficiency grounds, with models, including social epistemology models, showing random allocation could increase the generation of significant truths in a community of scientists when compared to funding by peer review. The models in the literature are, however, fairly abstract. This paper introduces some of the considerations that are (...) required to build on the modelling work towards a fully-fledged policy proposal, including issues of cost and fairness. (shrink)