Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T04:17:46.846Z Has data issue: false hasContentIssue false
  • English
  • Français

Epistemic Landscapes and the Division of Cognitive Labor

Published online by Cambridge University Press:  01 January 2022

Michael Weisberg  and
Ryan Muldoon
Get access Rights & Permissions [Opens in a new window]

Abstract

Because contemporary scientific research is conducted by groups of scientists, understanding scientific progress requires understanding this division of cognitive labor. 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 find the most epistemically significant research approaches. We consider three different search strategies that scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community influence their actions. This is compared with two social research strategies: Followers are biased toward 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 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.

Type
Research Article
Information
Philosophy of Science , Volume 76 , Issue 2 , April 2009 , pp. 225 - 252
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

‡

We are grateful for the research assistance of Daniel Singer and Anna Tuchman. Many thanks to Michael Dickson, Tania Lombrozo, Edouard Machery, Brian Skyrms, Michael Strevens, J. D. Trout, and Deena Skolnick Weisberg for helpful comments on earlier versions of this article.

References

Benner, S. A. (2003), “Synthetic Biology: Act Natural”, Synthetic Biology: Act Natural 421: 118.Google ScholarPubMed
Gao, J., Liu, H., and Kool, E. T. (2005), “Assembly of the Complete Eight-Base Artificial Genetic Helix, xDNA, and Its Interaction with the Natural Genetic System”, Assembly of the Complete Eight-Base Artificial Genetic Helix, xDNA, and Its Interaction with the Natural Genetic System 44:3118–3122.Google ScholarPubMed
Gerson, E. M. (2008), “Reach, Bracket, and the Limits of Rationalized Coordination: Some Challenges for CSCW”, in Ackerman, M. S. et al. (eds.), Resources, Co-evolution, and Artifacts: Theory in CSCW. Dordrecht: Springer-Verlag, 193–220.CrossRefGoogle Scholar
Giere, R. N. (1988), Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Hull, D. L. (1988), Science as a Process: An Evolutionary Account of the Social and Conceptual Development of Science. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Kitcher, P. (1990), “The Division of Cognitive Labor”, The Division of Cognitive Labor 87:5–22.Google Scholar
Kitcher, P. (1993), The Advancement of Science. Oxford: Oxford University Press.Google Scholar
Kuhn, T. S. (1962), The Structure of Scientific Revolutions. Chicago: University of Chicago Press.Google Scholar
Liu, H., et al. (2003), “A Four-Base Paired Genetic Helix with Expanded Size”, A Four-Base Paired Genetic Helix with Expanded Size 302:868–871.Google ScholarPubMed
Maynard Smith, J. (1982), Evolution and the Theory of Games. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
McConnell, T. L., and Wetmore, S. D. (2007), “How Do Size-Expanded DNA Nucleobases Enhance Duplex Stability? Computational Analysis of the Hydrogen-Bonding and Stacking Ability of xDNA Bases”, How Do Size-Expanded DNA Nucleobases Enhance Duplex Stability? Computational Analysis of the Hydrogen-Bonding and Stacking Ability of xDNA Bases 111 (11): 2999–3009..Google ScholarPubMed
Merton, R. K. (1957), “Priorities in Scientific Discovery”, Priorities in Scientific Discovery 22:635–659.Google Scholar
Muldoon, R., and Weisberg, M. (2008), “Robustness and Idealization in Models of Cognitive Labor”, manuscript.Google Scholar
Russell, S. J., and Norvig, P. (1995), Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Solomon, M. (1992), “Scientific Rationality and Human Reasoning”, Scientific Rationality and Human Reasoning 59:439–455.Google Scholar
Solomon, M. (2001), Social Empiricism. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Strevens, M. (2003), “The Role of the Priority Rule in Science”, The Role of the Priority Rule in Science 100:55–79.Google Scholar
Thagard, P. (1993), “Societies of Minds: Science as Distributed Computing”, Societies of Minds: Science as Distributed Computing 24:49–67.Google Scholar
Wilensky, U. (1999), “Netlogo”, Center for Connected Learning and Computer-Based Modeling. Evanston, IL: Northwestern University, http://ccl.northwestern.edu/netlogo/.Google Scholar