Explanation, representation and information

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Panagiotis Karadimas


The ontic conception of explanation is predicated on the proposition that “explanation is a relation between real objects in the world” and hence, according to this approach, scientific explanation cannot take place absent such a premise. Despite the fact that critics have emphasized several drawbacks of the ontic conception, as for example its inability to address the so-called “abstract explanations”, the debate is not settled and the ontic view can claim to capture cases of explanation that are non-abstract, such as causal relations between events. However, by eliminating the distinction between abstract and non-abstract explanations, it follows that ontic and epistemic proposals can no longer contend to capture different cases of explanation and either all are captured by the ontic view or all are captured by the epistemic view. On closer inspection, it turns out that the ontic view deals with events that fall outside the scientists’ scope of observation and that it does not accommodate common instances of explanation such as explanations from false propositions and hence it cannot establish itself as the dominant philosophical stance with respect to explanation. On the contrary, the epistemic conception does account for almost all episodes of explanation and can be described as a relation between representations, whereby the explanans transmit information to the explanandum and that this information can come, dependent on context, in the form of any of the available theories of explanation (law-like, unificatory, causal and non-causal). The range of application of the ontic view thus is severely restricted to trivial cases of explanation that come through direct observation of the events involved in an explanation and explanation is to be mostly conceived epistemically.

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Karadimas, P. (2024). Explanation, representation and information. Philosophical Problems in Science (Zagadnienia Filozoficzne W Nauce), (74), 21–55. https://doi.org/10.59203/zfn.74.636


Axfors, C. and Ioannidis, J.P.A., 2022. Infection fatality rate of COVID-19 in community-dwelling elderly populations. European Journal of Epidemiology [Online], 37(3), pp.235–249. https://doi.org/10.1007/s10654-022-00853-w.

Batterman, R.W., 2007. On the specialness of special functions (the nonrandom effusions of the divine mathematician). The British Journal for the Philosophy of Science [Online], 58(2), pp.263–286. Available at: <https://www.jstor.org/stable/30115226> [visited on 24 October 2023].

Bokulich, A., 2018. Representing and explaining: The eikonic conception of scientific explanation. Philosophy of Science [Online], 85(5), pp.793–805. https://doi.org/10.1086/699693.

Bolourian, A. and Mojtahedi, Z., 2021. COVID-19 and flu pandemics follow a pattern: a possible cross-immunity in the pandemic origin and graver disease in farther regions. Archives of Medical Research [Online], 52(2), pp.240–241. https://doi.org/10.1016/j.arcmed.2020.10.012.

Burgess, S., Ponsford, M.J. and Gill, D., 2020. Are we underestimating seroprevalence of SARS-CoV-2? BMJ [Online], p.m3364. https://doi.org/10.1136/bmj.m3364.

Craver, C. and Bechtel, W., 2006. Mechaninsm. In: S. Sarkar and J. Pfeifer, eds. The Philosophy of Science: An Encyclopedia. New York: Routledge, pp.469–478.

Craver, C.F., 2005. Beyond reduction: mechanisms, multifield integration and the unity of neuroscience. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences [Online], 36(2), pp.373–395. https://doi.org/10.1016/j.shpsc.2005.03.008.

Craver, C.F., 2007. Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience. Oxford: Oxford University Press.

Elgin, C.Z., 2010. Telling Instances. In: R. Frigg and M. Hunter, eds. Beyond Mimesis and Convention: Representation in Art and Science [Online], Boston Studies in the Philosophy of Science. Dordrecht: Springer Netherlands, pp.1–17. https://doi.org/10.1007/978-90-481-3851-7_1.

van Fraassen, B.C., 1980. The Scientific Image, Clarendon library of logic and philosophy. Oxford; New York: Clarendon Press; Oxford University Press.

van Fraassen, B.C., 2008. Scientific Representation: Paradoxes of Perspective [Online]. 1st ed. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199278220.001.0001.

Friedman, M., 1974. Explanation and scientific understanding. The Journal of Philosophy [Online], 71(1), pp.5–19. https://doi.org/10.2307/2024924.

Frigg, R. and Nguyen, J., 2017. Models and Representation. In: L. Magnani and T. Bertolotti, eds. Springer Handbook of Model-Based Science [Online], Springer Handbooks. Cham: Springer International Publishing, pp.49–102. https://doi.org/10.1007/978-3-319-30526-4_3.

Giere, R., 2018. Models of Experiments. In: I.F. Peschard and B.C. Van Fraassen, eds. The Experimental Side of Modeling, Minnesota studies in the philosophy of science, 21. Minneapolis: University of Minnesota Press, pp.59–70.

Glass, D.H., 2021. Coherence, explanation, and hypothesis selection. The British Journal for the Philosophy of Science [Online], 72(1), pp.1–26. https://doi.org/10.1093/bjps/axy063.

Glennan, S., 2005. Modeling mechanisms. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences [Online]. Mechanisms in biology, 36(2), pp.443–464. https://doi.org/10.1016/j.shpsc.2005.03.011.

Godfrey-Smith, P., 2009. Abstractions, Idealizations, and Evolutionary Biology. In: A. Barberousse, M. Morange and T. Pradeu, eds. Mapping the Future of Biology: Evolving Concepts and Theories [Online], Boston Studies in the Philosophy of Science. Dordrecht: Springer Netherlands, pp.47–56. https://doi.org/10.1007/978-1-4020-9636-5_4.

Hempel, C.G. and Oppenheim, P., 1948. Studies in the logic of explanation. Philosophy of Science [Online], 15(2), pp.135–175. https://doi.org/10.1086/286983.

Jansson, L. and Saatsi, J., 2019. Explanatory abstractions. The British Journal for the Philosophy of Science [Online], 70(3), pp.817–844. https://doi.org/10.1093/bjps/axx016.

Jefferson, T., Heneghan, C., Spencer, E. and Brassey, J., 2020. Are you infectious if you have a positive PCR test result for COVID-19? Available at: <https://www.cebm.net/covid-19/infectious-positive-pcr-test-result-covid-19/> [visited on 27 October 2023].

Karadimas, P., 2022. Thought experiments and the pragmatic nature of explanation. Foundations of Science [Online]. https://doi.org/10.1007/s10699-022-09844-2.

Karadimas, P., 2023. The Covid-19 Pandemic: A Public Choice View [Online]. Vol. 42, Studies in Public Choice. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-24967-9.

Kitcher, P., 1981. Explanatory unification. Philosophy of Science [Online], 48(4), pp.507–531. https://doi.org/10.1086/289019.

Lange, M., 2013. What makes a scientific explanation distinctively mathematical? The British Journal for the Philosophy of Science [Online], 64(3), pp.485–511. https://doi.org/10.1093/bjps/axs012.

Le Bert, N. et al., 2021. Highly functional virus-specific cellular immune response in asymptomatic SARS-CoV-2 infection. Journal of Experimental Medicine [Online], 218(5), e20202617. https://doi.org/10.1084/jem.20202617.

Levy, A., 2021. Idealization and abstraction: refining the distinction. Synthese [Online], 198(24), pp.5855–5872. https://doi.org/10.1007/s11229-018-1721-z.

Love, A.C. and Nathan, M.J., 2015. The idealization of causation in mechanistic explanation. Philosophy of Science [Online], 82(5), pp.761–774. https://doi.org/10.1086/683263.

Machamer, P., Darden, L. and Craver, C.F., 2000. Thinking about mechanisms. Philosophy of Science [Online], 67(1), pp.1–25. https://doi.org/10.1086/392759.

Parker, W.S., 2017. Computer simulation, measurement, and data assimilation. The British Journal for the Philosophy of Science [Online], 68(1), pp.273–304. https://doi.org/10.1093/bjps/axv037.

Pincock, C., 2007. A role for mathematics in the physical sciences. Noűs [Online], 41(2), pp.253–275. https://doi.org/10.1111/j.1468-0068.2007.00646.x.

Potochnik, A., 2017. Idealization and the Aims of Science [Online]. Chicago, IL: University of Chicago Press. Available at: <https://press.uchicago.edu/ucp/books/book/chicago/I/bo27128726.html> [visited on 27 October 2023].

Richardson, A., 1995. Explanation: Pragmatics and asymmetry. Philosophical Studies [Online], 80(2), pp.109–129. https://doi.org/10.1007/BF00989758.

Rovelli, C., 2015. Aristotle’s physics: A physicist’s look. Journal of the American Philosophical Association [Online], 1(1), pp.23–40. https://doi.org/10.1017/apa.2014.11.

Russell, B., 1956. On denoting. In: R.C. Marsh, ed. Logic and Knowledge Essays, 1901-1950. London: Allen & Unwin, pp.41–56.

Salis, F. and Frigg, R., 2020. Capturing the Scientific Imagination. In: A. Levy and P. Godfrey-Smith, eds. The Scientific Imagination [Online]. Oxford, New York: Oxford University Press, pp.17–50. https://doi.org/10.1093/oso/9780190212308.003.0002.

Salmon, W.C., 1984. Scientific explanation: Three basic conceptions. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association [Online], (2), pp.293–305. https://doi.org/10.1086/psaprocbienmeetp.1984.2.192510.

Salmon, W.C., 1989. Four decades of scientific explanation. In: P. Kitcher and W.C. Salmon, eds. Scientific Explanation [Online], Minnesota studies in the philosophy of science, 13. Minneapolis: University of Minnesota Press, pp.3–219. Available at: <http://conservancy.umn.edu/handle/11299/185700> [visited on 4 October 2023].

Salmon, W.C., 1998. Causality and Explanation [Online]. 1st ed. New York: Oxford University Press. https://doi.org/10.1093/0195108647.001.0001.

Shapere, D., 1982. The concept of observation in science and philosophy. Philosophy of Science [Online], 49(4), pp.485–525. https://doi.org/10.1086/289075.

Sheredos, B., 2016. Re-reconciling the epistemic and ontic views of explanation (or, why the ontic view cannot support norms of generality). Erkenntnis [Online], 81(5), pp.919–949. https://doi.org/10.1007/s10670-015-9775-5.

Sheredos, B., 2019. Re-re-reconciling the epistemic and ontic views of explanation: a reply to Wright & van Eck [Online]. Available at: <https://dx.doi.org/10.13140/RG.2.2.14862.20805>.

Strevens, M., 2011. Depth: An Account of Scientific Explanation. Cambridge, MA: Harvard University Press.

Winning, J., 2020. Mechanistic causation and constraints: Perspectival parts and powers, non-perspectival modal patterns. The British Journal for the Philosophy of Science [Online], 71(4), pp.1385–1409. https://doi.org/10.1093/bjps/axy042.

Woodward, J., 2002. What is a mechanism? a counterfactual account. Philosophy of Science [Online], 69(S3), S366–S377. https://doi.org/10.1086/341859.

Woodward, J., 2016. Unificationism, Explanatory Internalism, and Autonomy. In: M. Couch and J. Pfeifer, eds. The Philosophy of Philip Kitcher [Online]. Oxford University Press, pp.121–152. https://doi.org/10.1093/acprof:oso/9780199381357.003.0006.

Wright, C., 2012. Mechanistic explanation without the ontic conception. European Journal for Philosophy of Science [Online], 2(3), pp.375–394. https://doi.org/10.1007/s13194-012-0048-8.

Wright, C., 2015. The ontic conception of scientific explanation. Studies in History and Philosophy of Science Part A [Online], 54, pp.20–30. https://doi.org/10.1016/j.shpsa.2015.06.001.

Wright, C. and van Eck, D., 2018. Reconciling ontic and epistemic constraints on mechanistic explanation, epistemically. Ergo, an Open Access Journal of Philosophy [Online], 5(38). https://doi.org/10.3998/ergo.12405314.0005.038