This paper sets out to analyze how causation works by focusing on biology, as represented by epidemiology and by scientific information on how the body works (“physiology”). It starts by exploring the specificity of evolved physiological systems, in which evolutionary, developmental and proximal causes all fit together, and the concept of function is meaningful; in contrast, this structure does not apply in epidemiology (or outside biology). Using these two contrasting branches of biology, I examine the role both of mechanism and of difference making in causation. I find that causation necessarily involves both mechanism and difference making, and that they play complementary roles. Both are seen as ontologically necessary, even if the evidence is not always available for both. Influential monist accounts that focus on one of these, at the expense of ignoring the other, are found to be inadequate on these and on other grounds. Recent attempts to combine them are reviewed, notably that of Russo and Williamson (Int Stud Philos Sci 21:157–170, 2007), and it is argued that their epistemic view requires there to be a source of the different types of evidence that a rational agent would consider, and that this source must be ontic. I then analyze how causal relationships work in evolved physiological systems and in those studied by epidemiology, with a particular focus on how mechanism interacts with input. Finally, I consider this concept of causation from the perspective of everyday language, and of its possible generalisability outside biology.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Most obviously, if the component parts of a system link together neatly, an additional causal account of this neatness is required. Evolution or design could achieve that, but his account would then be limited to physiology and to technology in the broadest sense—a limitation that surely needs to be highlighted. He has more recently recognised “ephemeral mechanisms”, e.g. in a chain of historical events (Glennan 2010a), but does not explicitly acknowledge the impact of this realisation on his fundamental conception.
See also Illari and Williamson (2012).
Bechtel also draws on Palmer and Kimchi, who take a more “complex systems” view, which involves decomposition into ever-smaller parts, ending with the simplest components that have a physical embodiment (structure) and a function; they identify the difference making with the transformation of input information to output information at system level. This is similar to my conception of causal systems, that takes the individual causal link as the primary focus, with a bottom-up view of system behaviour as composed of these links.
Time order is thus assumed in this account, rather than explained.
A similar characteristic is found in purposive creations, notably technology—as in the examples of a clock or a lock and key commonly found in the philosophical literature on mechanisms. “Ephemeral mechanisms” (Glennan 2010a) do not have this characteristic. The evolved or designed nature is what has given rise to the idea that mechanisms must be complex, but it is not even true of all technology: the mechanism by which a piano produces its sound is indeed complicated, but the mechanism of a clavichord key depends just on a simple pivot.
It does form part of a system in the sense of a chain of causal links, and a control mechanism, in the apparatus for its synthesis and release. But this is not part of its mechanism of action.
For example, animal experiments have shown that anti-androgens that interfere with testosterone synthesis can impair male development in utero (Fisher et al. 2003). This has been suggested as having caused the large rise in testicular cancer in some populations during the twentieth century. However, the health effects in the animals are small unless exposures are used that are far higher than real human exposures; furthermore, exposures to these substances began too late to explain the start of the rise in cancer (Joffe 2010). The mechanism is plausible but the difference-making evidence shows that something else must be causing (most of) the observed trend.
“… not in the logical relationship between … descriptions but in the causal relationship between the parts of the mechanism …” (Glennan 2002).
In physics, the phenomenal success of mathematics has arguably led to the neglect of causation and especially of mechanism: sometimes it is too obvious to mention, as when one object collides with and moves another. In other cases it is totally obscure, the prime example being Newton’s law of gravitation, which established the difference-making relationship but postulated instantaneous action at a distance, an idea as fanciful as any in quantum theory. In terms of mechanism, then, this theory was deficient until Einstein completed it—not overturned it, as is sometimes thought. Thus, the view arose that the idea of causation adds nothing to the equations and therefore is superfluous (Russell 1913; Norton 2009). This makes it a bad model for other sciences.
Bechtel, W. (2008). Mental mechanisms: Philosophical perspectives on cognitive neuroscience. New York: Routledge.
Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in the History and Philosophy of the Biological and Biomedical Sciences, 36, 421–441.
Brilliant, M. H. (2008). Gene polymorphism and human pigmentation. US Department of Justice Document No. 223980. Retrieved November 13, 2012 from https://www.ncjrs.gov/pdffiles1/nij/grants/223980.pdf.
Broadbent, A. (2011). Inferring causation in epidemiology: Mechanisms, black boxes, and contrasts. In P. McKay Illari, F. Russo, & J. Williamson (Eds.), Causality in the sciences. Oxford: Oxford University Press.
Campaner, R., & Galavotti, M. C. (2007). Plurality in causality. In P. Machamer & G. Wolters (Eds.), Thinking about causes (pp. 178–199). Pittsburgh: Pittsburgh University Press.
Cartwright, N. (1994). Nature’s capacities and their measurement. Oxford: Oxford University Press.
Cartwright, N. (2011). Evidence-based practice: mixing methods makes good practice. Presented at the CaEitS2011 conference: Causality and explanation in the sciences, Ghent, Belgium.
Cartwright, N., & Pemberton J. (2012). Aristotelian powers: Without them, what would modern science do? In J. Greco & R. Groff (Eds.), Powers and capacities in philosophy: The new Aristotelianism (pp. 93–112). Routledge. Retrieved November 13, 2012 from http://personal.lse.ac.uk/PEMBERTO/AP%20v10.0.pdf.
Craver, F. C. (2007). Explaining the brain: Mechanisms and the mosaic unity of neuroscience. Oxford: Clarendon Press.
Dowe, P. (2000). Physical causation. Cambridge: Cambridge University Press.
Fisher, J. S., Macpherson, S., Marchetti, N., & Sharpe, R. M. (2003). Human ‘testicular dysgenesis syndrome’: A possible model using in utero exposure of the rat to dibutyl phthalate. Human Reproduction, 18, 1383–1394.
Glennan, S. (1996). Mechanisms and the nature of causation. Erkenntnis, 44, 49–71.
Glennan, S. (2002). Rethinking mechanistic explanations. Philosophy of Science, 69, S342–S353.
Glennan, S. (2008). Mechanisms. In S. Psillos & M. Curd (Eds.), The Routledge companion to the philosophy of science. London & New York: Routledge.
Glennan, S. (2010a). Ephemeral mechanisms and historical explanation. Erkenntnis, 72, 251–266.
Glennan, S. (2010b). Mechanisms, causes, and the layered model of the world. Scholarship and Professional Work—LAS. Paper 73. Retrieved November 13, 2012 from http://digitalcommons.butler.edu/facsch_papers/73/.
Glennan, S. (2011). Singular and general causal relations: A mechanist perspective. In P. McKay Illari, F. Russo, & J. Williamson (Eds.), Causality in the sciences. Oxford: Oxford University Press.
Hall, N. (2004). Two concepts of causation. In J. Collins, N. Hall, & L. A. Paul (Eds.), Causation and counterfactuals. Cambridge, MA: Bradford Book/MIT Press.
Hill, A. B. (1965). The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58, 295–300.
Illari, P., & Williamson, J. (2012). What is a mechanism? Thinking about mechanisms across the sciences. European Journal for Philosophy of Science, 2, 119–135.
Joffe, M. (2010). What has happened to human fertility? Human Reproduction, 25, 295–307.
Joffe, M. (2011a). Causality and evidence discovery in epidemiology. In D. Dieks, W. J. Gonzalez, S. Hartmann, T. Uebel, & M. Weber (Eds.), Explanation, prediction, and confirmation. New trends and old ones reconsidered (pp. 153–166). Dordrecht: Springer.
Joffe, M. (2011b). The gap between evidence discovery and actual causal relationships. Preventive Medicine, 53, 246–249.
Joffe, M., Gambhir, M., Chadeau-Hyam, M., & Vineis, P. (2012). Causal diagrams in systems epidemiology. Emerging Themes in Epidemiology, 9, 1.
Knowles, J. R. (1970). On the mechanism of action of pepsin. Philosophical transactions of the Royal Society of London Series B, 257, 135–146.
Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67, 1–25.
Neilson, H. K., Friedenreich, C. M., Brockton, N. T., & Millikan, R. C. (2009). Physical activity and postmenopausal breast cancer: Proposed biologic mechanisms and areas for future research. Cancer Epidemiology, Biomarkers and Prevention, 18, 11–27.
Norton, J. D. (2009). Is there an independent principle of causality in physics? British Journal for the Philosophy of Science, 60, 475–486.
Pearl, J. (2000). Causality: Models, reasoning and inference. New York: Cambridge University Press.
Pearl, J. (2002). Causal inference in the health sciences: A conceptual introduction. Health Services and Outcomes Research Methodology, 2, 189–220.
Pemberton, J. (2011). Integrating mechanist and nomological machine ontologies to make sense of what-how-that causal evidence. Retrieved November 13, 2012 from http://personal.lse.ac.uk/pemberto/PNMO%20paper%20v6%200%20pdf.pdf.
Psillos, S. (2004). A glimpse of the secret connexion: Harmonising mechanisms with counterfactuals. Perspectives on Science, 12, 288–319.
Rose, G. (2001). Sick individuals and sick populations. International Journal of Epidemiology, 30, 427–432. [first published 1985].
Ruse, M. (1973). The philosophy of biology (p. 195). London: Hutchinson & Co. Ltd.
Russell, B. (1913). On the notion of cause. Proceedings of the Aristotelian Society, 13, 1–26.
Russo, F. (2012). Correlational data, causal hypotheses, and validity. Journal of the General Philosophy of Science, 42, 85–107.
Russo, F., & Williamson, J. (2007). Interpreting causality in the health sciences. International Studies in the Philosophy of Science, 21, 157–170.
Russo, F., Wunsch, G., & Mouchart, M. (2011). Inferring causality through counterfactuals in observational studies. Some epistemological issues. Bulletin de Méthodologie Sociologique [Bulletin of Sociological Methodology], 111, 43–64.
Strand, A., & Oftedal, G. (2009). Functional stability and systems level causation. Philosophy of Science, 76, 809–820.
Strevens, M. (2007). Review of Woodward “making things happen”. Philosophy and Phenomenological Research, 74, 233–249.
Tabery, J. (2009). Difference mechanisms: Explaining variation within mechanisms. Biology and Philosophy, 24, 645–664.
Vineis, P., & Perera, F. (2007). Molecular epidemiology and biomarkers in etiologic cancer research: The new in light of the old. Cancer Epidemiology, Biomarkers and Prevention, 16, 1954–1965.
Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.
Woodward, J. (2010). Causation in biology: Stability, specificity, and the choice of levels of explanation. Biology and Philosophy, 25, 287–318.
Wouters, A. (2013). Explanation in biology. In W. Dubitzky , O. Wolkenhauer, H. Yokota, & K.-H. Cho (Eds.), Encyclopedia of systems biology. Dordrecht: Springer (in press).
About this article
Cite this article
Joffe, M. The Concept of Causation in Biology. Erkenn 78, 179–197 (2013). https://doi.org/10.1007/s10670-013-9508-6
- Causal Relationship
- Causal Claim
- Deterministic Causation
- Causal Relevance