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Measuring Causal Specificity

Published online by Cambridge University Press:  01 January 2022


Several authors have argued that causes differ in the degree to which they are ‘specific’ to their effects. Woodward has used this idea to enrich his influential interventionist theory of causal explanation. Here we propose a way to measure causal specificity using tools from information theory. We show that the specificity of a causal variable is not well defined without a probability distribution over the states of that variable. We demonstrate the tractability and interest of our proposed measure by measuring the specificity of coding DNA and other factors in a simple model of the production of mRNA.

Research Article
Copyright © The Philosophy of Science Association

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This publication was made possible through the support of a grant from the Templeton World Charity Foundation. The opinions expressed are those of the author(s) and do not necessarily reflect the views of the Templeton World Charity Foundation. Brett Calcott was supported by Joshua Epstein’s NIH Director’s Pioneer Award DP1OD003874 from the Office of the Director, National Institutes of Health. The article is the result of a workshop held at the University of Colorado, Boulder, with support from Templeton World Charity Foundation. BC, PG, AP, and, KS wrote the manuscript, and all authors agreed on the final content. We would like to thank two anonymous referees for their helpful comments.


Ay, N., and Polani, D.. 2008. “Information Flows in Causal Networks.” Advances in Complex Systems 11 (1): 1741.CrossRefGoogle Scholar
Bonduriansky, R. 2012. “Rethinking Heredity, Again.” Trends in Ecology and Evolution 27 (6): 330–36.CrossRefGoogle Scholar
Burian, R. M. 2004. “Molecular Epigenesis, Molecular Pleiotropy, and Molecular Gene Definitions.” History and Philosophy of the Life Sciences 26 (1): 5980.CrossRefGoogle ScholarPubMed
Cover, T. M., and Thomas, J. A.. 2012. Elements of Information Theory. Hoboken, NJ: Wiley.Google Scholar
Fogle, T. 2000. “The Dissolution of Protein Coding Genes in Molecular Biology.” In The Concept of the Gene in Development and Evolution, ed. Beurton, P. J., Falk, R., and Rheinberger, H.-J., 325. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Garner, W. R., and McGill, W.. 1956. “The Relation between Information and Variance Analyses.” Psychometrika 21 (3): 219–28.CrossRefGoogle Scholar
Griffiths, P. E., Pocheville, A., Calcott, B., Stotz, K., Karola, K., Kim, H., and Knight, R.. 2015. “Measuring Causal Specificity: Supplementary Online Materials.” PhilSci Archive, Scholar
Griffiths, P. E., and Stotz, K.. 2007. “Gene.” In Cambridge Companion to Philosophy of Biology, ed. Ruse, M. and Hull, D., 85102. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hull, D. 2013. Genetics and Philosophy: An introduction. New York: Cambridge University Press.Google Scholar
Jablonka, E., and Lamb, M. J.. 2005. Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge, MA: MIT Press.Google Scholar
Lewis, D. K. 2000. “Causation as Influence.” Journal of Philosophy 97:182–97.CrossRefGoogle Scholar
Lizier, J. T., and Prokopenko, M.. 2010. “Differentiating Information Transfer and Causal Effect.” European Physical Journal B 73 (4): 605–15.. doi:10.1140/epjb/e2010-00034-5.CrossRefGoogle Scholar
Oyama, S. 2000. The Ontogeny of Information: Developmental Systems and Evolution. 2nd rev. ed. Durham, NC: Duke University Press.Google Scholar
Pearl, Judea. 2009. Causality. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Ptashne, M., and Gann, A.. 2002. Genes and Signals. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory.Google Scholar
Reshef, D. N., Reshef, Y. A., Finucane, H. K., Grossman, S. R., McVean, G., Turnbaugh, P. J. et al. 2011. “Detecting Novel Associations in Large Data Sets.” Science 334 (6062): 1518–24.CrossRefGoogle ScholarPubMed
Ross, B. C. 2014. “Mutual Information between Discrete and Continuous Data Sets.” PLoS ONE 9 (2): e87357.CrossRefGoogle ScholarPubMed
Shannon, C. E., and Weaver, W.. 1949. The Mathematical Theory of Communication. Urbana: University of Illinois Press.Google Scholar
Stotz, K. 2006. “Molecular Epigenesis: Distributed Specificity as a Break in the Central Dogma.” History and Philosophy of the Life Sciences 28 (4): 533–48.Google ScholarPubMed
Uller, T. 2012. “Parental Effects in Development and Evolution.” In The Evolution of Parental Care, ed. Royle, N. J., Smiseth, P. T., and Kölliker, M., 247–66. Oxford: Oxford University Press.Google Scholar
Waters, C. K. 2007. “Causes That Make a Difference.” Journal of Philosophy 104 (11): 551–79.CrossRefGoogle Scholar
Weber, M. 2006. “The Central Dogma as a Thesis of Causal Specificity.” History and Philosophy of the Life Sciences 28 (4): 595609.Google ScholarPubMed
Weber, M. 2013. “Causal Selection versus Causal Parity in Biology: Relevant Counterfactuals and Biologically Normal Interventions.” In What If? On the Meaning, Relevance and Epistemology of Counterfactual Claims and Thought Experiments, 144. Konstanz: University of Konstanz.Google Scholar
Woodward, J. 2003. Making Things Happen: A Theory of Causal Explanation. Oxford: Oxford University Press.Google Scholar
Woodward, J. 2010. “Causation in Biology: Stability, Specificity, and the Choice of Levels of Explanation.” Biology and Philosophy 25 (3): 287318.CrossRefGoogle Scholar
Woodward, J. 2012. “Causation and Manipulability.” In The Stanford Encyclopedia of Philosophy, ed. Zalta, Edward N.. Stanford, CA: Stanford University. Scholar