Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-23T00:33:52.119Z Has data issue: false hasContentIssue false
  • English
  • Français

The Epistemic Division of Labor Revisited

Published online by Cambridge University Press:  01 January 2022

Johanna Thoma
Get access Rights & Permissions [Opens in a new window]

Abstract

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.

Type
Research Article
Information
Philosophy of Science , Volume 82 , Issue 3 , July 2015 , pp. 454 - 472
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

†

I owe special thanks to Conor Mayo-Wilson for helpful feedback and encouragement at all stages of this paper. Ryan Muldoon, Kevin Zollman, and Stephan Hartmann, as well as audiences at the Canadian Society for Epistemology’s Symposium on Social Epistemology in Sherbrooke and at the Munich Center for Mathematical Philosophy, also provided valuable comments. This work was supported by the University of Toronto Germany/Europe Fund.

References

Blaug, Mark. 1997. Economic Theory in Retrospect. 5th ed. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
De Langhe, Rogier. 2014. “A Unified Model of the Division of Cognitive Labor.” Philosophy of Science 81 (3): 444–59.CrossRefGoogle Scholar
Fox, Mary Frank. 1983. “Publication Productivity among Scientists: A Critical Review.” Social Studies of Science 13 (2): 285–305.CrossRefGoogle Scholar
Hong, Luo, and Page, Scott E.. 2004. “Groups of Diverse Problem Solvers Can Outperform Groups of High-Ability Problem Solvers.” Proceedings of the National Academy of Sciences of the United States of America 101 (46): 16385–89.Google ScholarPubMed
Keynes, John Maynard. 1936. The General Theory of Employment, Interest and Money. London: Macmillan.Google Scholar
Kitcher, Philip. 1990. “The Division of Cognitive Labor.” Journal of Philosophy 87 (1): 5–22.CrossRefGoogle Scholar
Kitcher, Philip 1993. The Advancement of Science. New York: Oxford University Press.Google Scholar
Levin, Sharon G., and Stephan, Paula E.. 1991. “Research Productivity over the Life Cycle: Evidence for Academic Scientists.” American Economic Review 81 (1): 114–32.Google Scholar
Mankiw, N. Gregory. 2006. “The Macroeconomist as Scientist and Engineer.” Journal of Economic Perspectives 20 (4): 29–46.CrossRefGoogle Scholar
Muldoon, Ryan. 2013. “Diversity and the Cognitive Division of Labor.” Philosophy Compass 8 (2): 117–25.CrossRefGoogle Scholar
Muldoon, Ryan, and Weisberg, Michael, 2011. “Robustness and Idealization in Models of Cognitive Labor.” Synthese 183 (2): 161–74.CrossRefGoogle Scholar
Strevens, Michael. 2003. “The Role of the Priority Rule in Science.” Journal of Philosophy 100 (2): 55–79.CrossRefGoogle Scholar
Weisberg, Michael, and Muldoon, Ryan. 2009. “Epistemic Landscapes and the Division of Cognitive Labor.” Philosophy of Science 76 (2): 225–52.CrossRefGoogle Scholar
Wilensky, Uri. 1999. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. http://ccl.northwestern.edu/netlogo/.Google Scholar
Zollman, Kevin. 2010. “The Epistemic Benefit of Transient Diversity.” Erkenntnis 72 (1): 17–35.CrossRefGoogle Scholar