Departmental Papers (Philosophy)
Document Type
Journal Article
Date of this Version
11-2011
Publication Source
Synthese
Volume
183
Issue
2
Start Page
161
Last Page
174
DOI
10.1007/s11229-010-9757-8
Abstract
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.
Copyright/Permission Statement
The final publication is available at Springer via http://dx.doi.org/10.1007/s11229-010-9757-8
Keywords
Robustness analysis, agent-based simulation, division of cognitive labor, models, idealization, constrained maximation
Recommended Citation
Muldoon, Ryan and Weisberg, Michael, "Robustness and Idealization in Models of Cognitive Labor" (2011). Departmental Papers (Philosophy). 17.
https://repository.upenn.edu/philosophy_papers/17
Date Posted: 04 December 2017
This document has been peer reviewed.