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 the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with Kuhn a number (...) of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

It seems obvious that a community of one thousand scientists working together to make discoveries and solve puzzles should arrange itself differently than would one thousand scientist-hermits working independently. Because of limited time, resources, and attention, an independent scientist can explore only some of the possible approaches to a problem. Working alone, each hermit would explore the most promising approaches. They would needlessly duplicate the work of others and would be unlikely to develop approaches which look unpromising but really have (...) tremendous potential. Contrariwise, a large community can more rigorously explore the space of possible approaches. Most scientists should work on the most promising approaches, but a smaller number can be committed to approaches that initially look less promising. Exploratory work can reveal if one of those initially unpromising approaches has unrealized potential, and more scientists can adopt it once its potential becomes more apparent. (shrink)

One approach to science treats science as a cognitive accomplishment of individuals and defines a scientific community as an aggregate of individual inquirers. Another treats science as a fundamentally collective endeavor and defines a scientist as a member of a scientific community. Distributed cognition has been offered as a framework that could be used to reconcile these two approaches. Adam Toon has recently asked if the cognitive and the social can be friends at last. He answers that they probably cannot, (...) posing objections to the would-be rapprochement. We clarify both the animosity and the tonic proposed to resolve it, ultimately arguing that worries raised by Toon and others are uncompelling. (shrink)

Scientific research is based on the division of cognitive labour: every scientist has to trust that other colleagues have checked whether the items that are taken as knowledge, and she cannot check by herself, are reliable enough. I apply ideas from the field known as ‘information economics’ to analyse the scientists’ incentives to produce items of knowledge of an ‘adequate’ quality, under the assumption that a big part of what one observes in her empirical research is not available for the (...) readers of the paper. I also discuss some criticisms to this ‘marketization’ of science studies. (shrink)

Since the publication of Kitcher’s influential paper The Division of Cognitive Labor, some philosophers wondered about these two related issues: (1) which is the optimal distribution of cognitive efforts among rival methods within a scientific community?, and (2) whether and how can a community achieve such an optimal distribution? Though not committing to any specific answer to question (1), I claim that issue (2) does not depend exclusively on an invisible hand like mechanism, since both intra-scientific and extra-scientific institutions may (...) play a major role. Finally, I examine some practical difficulties of reallocating scientists from a method to another, which leads to stress the importance of well-planned training and recruitment. (shrink)