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How Organization Explains

  • Jaakko KuorikoskiEmail author
  • Petri Ylikoski
Conference paper
Part of the The European Philosophy of Science Association Proceedings book series (EPSP, volume 2)

Abstract

Constitutive mechanistic explanations explain a property of a whole with the properties of its parts and their organization. Carl Craver’s mutual manipulability criterion for constitutive relevance only captures the explanatory relevance of causal properties of parts and leaves the organization side of mechanistic explanation unaccounted for. We use the contrastive counterfactual theory of explanation and an account of the dimensions of organization to build a typology of organizational dependence. We analyse organizational explanations in terms of such dependencies and emphasize the importance of modular organizational motifs. We apply this framework to two cases from social science and systems biology, both fields in which organization plays a crucial explanatory role: agent-based simulations of residential segregation and the recent work on network motifs in transcription regulation networks.

Keywords

Organizational Dependence Explanatory Relevance Network Motifs Mutual Manipulability Constitutive Dependence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

We thank Caterina Marchionni and the audience at EPSA 2011 for their valuable comments. This research has been financially supported by the Academy of Finland.

References

  1. Alon, U. (2007). Network motifs: Theory and experimental approaches. Nature Reviews Genetics, 8(6), 450–461.CrossRefGoogle Scholar
  2. Aydinonat, E. (2008). The invisible hand in economics: How economists explain unintended social consequences. London: Routledge.CrossRefGoogle Scholar
  3. Benard, S., & Willer, R. (2007). A wealth and status-based model of residential segregation. The Journal of Mathematical Sociology, 31(2), 149–174.CrossRefGoogle Scholar
  4. Clark, W. A. V., & Fossett, M. (2008). Understanding the social context of the Schelling segregation model. Proceedings of the National Academy of Sciences, 105(11), 4109.CrossRefGoogle Scholar
  5. Craver, C. (2007). Explaining the brain: Mechanisms and the mosaic unity of neuroscience. New York/Oxford: Clarendon.CrossRefGoogle Scholar
  6. Fossett, M. (2006). Ethnic preferences, social distance dynamics, and residential segregation: Theoretical explorations using simulation analysis. The Journal of Mathematical Sociology, 30(3–4), 185–273.Google Scholar
  7. Fossett, M., & Warren, W. (2005). Overlooked implications of ethnic preferences for residential segregation in agent-based models. Urban Studies, 42, 1893–1917.CrossRefGoogle Scholar
  8. Glennan, S. (2002). Rethinking mechanistic explanation. Philosophy of Science, 69, S342–S353.CrossRefGoogle Scholar
  9. Hedström, P., & Ylikoski, P. (2010). Causal mechanisms in the social sciences. Annual Review of Sociology, 36, 49–67.CrossRefGoogle Scholar
  10. Keil, F. C. (2003). Folkscience: Coarse interpretations of a complex reality. Trends in Cognitive Sciences, 7, 368–373.CrossRefGoogle Scholar
  11. Mangan, S., & Alon, U. (2003). Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences, 100(21), 11980–11985.CrossRefGoogle Scholar
  12. Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1, 143–186.CrossRefGoogle Scholar
  13. Schelling, T. C. (1978). Micromotives and macrobehavior. London/New York: W. W. Norton.Google Scholar
  14. Vinković, D., & Kirman, A. (2006). A physical analogue of the Schelling model. Proceedings of the National Academy of Sciences, 103(51), 19261–19265.CrossRefGoogle Scholar
  15. Watts, D. J. (2004). The “new” science of networks. Annual Review of Sociology, 30(1), 243–270.CrossRefGoogle Scholar
  16. Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Cambridge: Harvard University Press.Google Scholar
  17. Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.Google Scholar
  18. Ylikoski, P. (2009). The illusion of depth of understanding in science. In H. De Regt, S. Leonelli, & K. Eigner (Eds.), Scientific understanding: Philosophical perspectives (pp.100–119). Pittsburgh: Pittsburgh University Press.Google Scholar
  19. Ylikoski, P., & Kuorikoski, J. (2010). Dissecting explanatory power. Philosophical Studies, 148, 201–219.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Social and Moral Philosophy/Department of Political and Economic StudiesUniversity of HelsinkiHelsinkiFinland
  2. 2.Department of Social ResearchUniversity of HelsinkiHelsinkiFinland

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