The Communication Structure of Epistemic Communities

Abstract

Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its members are less aware of their colleagues’ experimental results. Second, there is a robust tradeoff between the reliability of a community and the speed with which it reaches a correct conclusion.

Unconceived alternatives and conservatism in science: the impact of professionalization, peer-review, and Big Science

“…Prior to such professionalization, science was pursued primarily by what Martin Rudwick (1985) famously called 'gentlemanly specialists' largely supported by their 1 It is worth noting, however, that Godfrey-Smith's "information flow" may not be an especially promising candidate here: as Zollman (2007Zollman ( , 2010 has shown, increasing information flow among the agents in an idealized scientific community increases the speed at which those communities converge on a single view but also increases the chances that such communities will reach premature consensus in favor of a mistaken or suboptimal view by excluding alternatives too quickly. This research is part of a rich literature concerning the social organization of scientific inquiry (including work by David Hull, Philip Kitcher, Michael Strevens, Miriam Solomon, and many others) that I will henceforth largely ignore.…”

The Independence Thesis: When Individual and Social Epistemology Diverge

“…The psychologist's method is an example of what are 1/ (n ϩ 1) called decreasing epsilon greedy methods, and this particular decreasing epsilon greedy strategy is IC; the psychologist will provably converge toward testing the optimal theory with probability one. Interestingly, the method of always testing the best-up-to-now theory is not IC: testing the best-up-to-now theory can lead to abandoning potentially better theories early on, simply because of random chance successes (or failures) by suboptimal (or optimal) theories (Zollman 2007(Zollman , 2010. The previous 13.…”

“…Unreliable individuals might pool their information in such a way as to create reliable groups (Surowiecki 2004;Goodin 2006). Groups in which a significant amount of information is ignored might do better than groups in which information flows freely because an appropriate amount of diversity can be maintained in the absence of information (Zollman 2007(Zollman , 2010. And so on.…”

New Approaches to the Division of Cognitive Labor

“…Scientists attach probabilities to hypotheses using information that they discover for themselves and information that they learn from other members of their community. In new work by Grim (Rosenberger, Grim, Anderson, Rosenfeld, & Eason, ms) and Zollman (2007;forthcoming), lines of communication between scientists are represented by network graphs, such the ones seen in Figure 1. Each node of these graphs represents a scientist and each edge a communication channel.…”