Skip to main content
Log in

The Ontology of Causation: A Carnapian-Pragmatist Approach

  • Article
  • Published:
Journal for General Philosophy of Science Aims and scope Submit manuscript

Abstract

Metaphysicians of causation have long debated the existence of primitive causal modalities (e.g., powers), with reductionists and realists taking opposing stances. However, little attention has been given to the legitimacy of the metaphysical question itself, despite our longstanding awareness of Rudolf Carnap’s critique of metaphysics. This article develops a (broadly) Carnapian-pragmatist approach to causation as an alternative to existing metaphysical approaches. Within this pragmatist approach, metaphysical questions about causation are reinterpreted as practical questions about the choice of causal frameworks. To motivate and justify this new approach, I argue that, in emphasizing the priority of ontology over methodology, metaphysical approaches to causation fail to adequately capture the interplay between causal ontology and causal methodology in scientific practice. In contrast, the Carnapian approach provides a more appealing alternative that emphasizes the mutual dependence and ‘balance’ between the two in an ongoing process of scientific inquiry. I use the recent controversy over ‘What counts as a cause’ in statistical causal inference as a case study to demonstrate how the Carnapian approach can help us better understand the role of ontological issues in methodological practices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. Danks (2015) and Ludwig (2016) can be interpreted as taking (broadly construed) Carnapian approaches to scientific ontology. Antoniou (2021) defends a Carnapian pragmatist approach to the ontology of scientific models. Lauer (2022) proposes a pragmatic approach to social ontology that seems to be Carnapian in spirit.

  2. Fischer (2023) develops a Carnapian approach to the ontology of actual causation which emphasizes the role of goals and context in improving or explicating our concept of actual causation. In addition, broadly pragmatist approaches to causation can be found in Eagle (2007), Hitchcock (2012), Price (2001; 2007), and Woodward (2014; 2015; 2017; 2021).

  3. At the end of the paper, Carnap (1956, 221) says, “[t]o decree dogmatic prohibitions of certain linguistic forms instead of testing them by their success or failure in practical use […] is positively harmful because it may obstruct scientific progress”.

  4. I thank two anonymous reviewers for suggesting this important clarification. My distinction here draws inspiration from Woodward’s (2015, 3578–3579) distinction between ontology1 and ontology2. Our distinctions are essentially the same except for one important difference: my ontologyC subsumes Woodward’s narrower notion of ontology1. An ‘ontology1’ (e.g., a gene ontology) refers to a system of ‘basic’ entities, properties, and structures, together with ways of classifying them, in a particular scientific domain. OntologyC, in contrast, encompasses any kind of ontological commitments, classifications, frameworks, and inquiries in science or philosophy that are Carnapian in nature.

  5. In this paper, ‘causal realism’ refers specifically to a metaphysically inflationary thesis about causation. Therefore, my rejection of causal realism doesn’t imply that causation cannot be ‘real’ in some deflationary sense.

  6. I agree with Cartwright (1989; esp., 2007) on many things she has said about causation; nevertheless, I think Cartwright and Pemberton (2013) have gone too far in making unnecessary metaphysical commitments to Aristotelian powers. I will say more about this in Sect. 4.

  7. Readers may be interested in what Carnap himself thinks about the ontology of causation. Unfortunately, he was somewhat equivocal on this. On the one hand, Carnap (1966, 201) was sympathetic to reductionism: “A statement about a causal relation […] describes an observed regularity of nature, nothing more.” Therefore, it seems that here, even Carnap failed to resist the temptation to make a metaphysical (i.e., a Humean) claim about causation. On the other hand, Carnap also acknowledged that “I do not deny the possibility of introducing a necessity concept, provided it is not a metaphysical concept but is a concept within the logic of [causal] modalities” Carnap (1966, 208). The idea expressed in this latter quote is clearly a Carnapian one: if a framework needs to postulate causal necessities to fulfill our goals, we are justified to admit them to our ontologyC.

  8. Here ‘truth’ is understood in terms of some sort of correspondence relation between assertions and (some portion of) external reality. I assume that causal realists, and more generally speaking, metaphysical realists, typically adopt a correspondence theory of truth which says that truth consists in some kind of correspondence between statements/propositions/frameworks and external reality (see David 2022).

  9. According to Carnap (1962, 3), “explication consists in transforming a given more or less inexact concept into an exact one.” See also Fischer (2023) for how Carnapian explications work in the context of actual causation.

  10. A similar point has also been made by Woodward (2007, 90): “Relative to a specification of system and a level of description or graining for it […] one fixes the variables one is talking about, it is [an] ‘objective’ matter whether and how [the variables] are causally related”, and by Eagle (2007, 167): “even if the variable and their ranges are chosen for pragmatic and context-sensitive reasons, the truth of the resulting counterfactuals will be a perfectly objective feature of those variables.”

  11. What is this infrastructure? Weinberger et al. (2023, 4) write: “there are certain generic features of our world that license and support the application of causal thinking and inferences to causal conclusions […] (i) some variables are statistically independent of others […] (ii) interventions, in the sense of unconfounded manipulations, are often possible […] (iii) the macroscopic, coarse-grained behavior of many systems is largely independent of variations in their microscopic realizing details […]”.

  12. Fischer (2023) reaches a similar conclusion about frameworks of actual causation.

  13. Hitchcock (2007, 200) helpfully identifies “a plurality of causal pluralisms”; see references therein.

  14. Although I am not opposed to Cartwright’s thesis of causal pluralism, I argue in Sect. 4.1 that her thesis about causal diversity does not square well with Cartwright and Pemberton’s (2013) desire for a unified causal ontologyM.

  15. Another popular statistical causal inference framework is the potential-outcomes framework (also known as ‘the Rubin Causal Model’; see Rubin 1974; Holland 1986), which is discussed in Sect. 4.3.

  16. I don’t have the space to elaborate on how the backdoor criterion works, but see Pearl (2009, 79–80) and Pearl et al. (2016, 61–64) for detailed explanations.

  17. An analogous problem is also noted in Danks (2015). Danks shows that depending on our goals, we may need different models with incompatible ontological commitments even about the same target system.

  18. In a broadly Quinean spirit, Schurz and Gebharter (2016, 1073) argue that causation is a “theoretical concept” explicated by “axioms” of the “theory” of causal Bayes nets (aka SCMs). My project and theirs share important common grounds, but I disagree that the SCM framework alone is sufficient to explicate the concept (or rather concepts) of causation. In making this claim, they seem to assume that SCMs can capture everything important about causation and that it is the single best causal framework we have. There are good reasons to doubt these assumptions. First, the framework of SCM is merely concerned with the ‘thin’ concept of causation. But there are plenty of ‘thick’ causal concepts used in the sciences that the formalism simply cannot capture (cf. Cartwright 2007). For example, in classical mechanics, the detailed dynamics of a system’s evolution needs to be described using Hamiltonian equations which we do not find in SCMs. Additionally, axioms of SCMs presuppose idealized assumptions (such as modularity) that may be violated in biological sciences. Moreover, even in domains where SCMs plays a significant role, causal notions used there are often richer and messier than what the axioms of SCMs can tell us. For example, actual interventions conducted in clinical trials are much more complicated than the kind of atomic or ideal interventions assumed in the SCM framework. Additionally, the formalism of SCM does not capture other peripheral causal notions like invariance, proportionality, and stability that play an indispensable role in causal inference practice.

  19. I am not the only one who is skeptical about the possibility of having conclusive arguments against the metaphysician. Woodward (2017, 193), for example, found that “putting everything into an ordinary ‘linear’ argument [against the metaphysician] was impossible”; so, he organized his article as an imaginary dialogue with ‘Professor Metafisico’.

  20. E.g., consider downward causation in science (e.g., biology). The existence of downward causation is often accepted without questioning by biologists due to the evident usefulness of this ontological postulate; what biologists are interested in are typically internal questions about downward causation. Metaphysicians, however, are interested in the following metaphysical question: ‘Is there really downward causation?’ Surprisingly, the metaphysician Kim (1993) has ‘compellingly’ argued—in the sense that the premises of the argument are widely accepted among metaphysicians—that downward causation is impossible! This sharp discontinuity between ontological postulations in scientific practice and our metaphysics seems baffling and counterintuitive, to say the least.

  21. I am not saying it is incoherent to be a pragmatist Aristotelian, but I doubt that anyone who are sympathetic to a pragmatist meta-ontologyC would label themselves an Aristotelian without adding any caveat.

  22. Cartwright (2007, 19; emphasis added) writes: “We think of causation as a single monolithic concept. But that is a mistake […] there is no single thing of much detail that [causal laws] all have in common, something they share that makes them all causal laws.”

  23. “The explicatum is to be similar to the explicandum in such a way that, in most cases in which the explicandum has been so far used, the explicatum can be used (Cartwright 2007, 7)”.

  24. The question, especially of whether attributes or characteristics should be seen as causes in causal inference, has stimulated much debate in both philosophy and science (Holland 2003; Woodward 2003; 2016; Greiner and Rubin 2011; Sen and Wasow 2016). My discussion below will unavoidably be brief and oversimplified.

  25. Note that you can of course change these attributes indirectly by assigning treatments to an individual. For example, you can improve a student’s scholastic performance by helping them with their homework. But this is not the same thing as assigning high scholastic performance as a treatment to that student. What is assigned as treatment here is homework help, not high scholastic performance.

References

  • Anjum, R. L., and S. Mumford. 2018. Causation in science and the methods of scientific discovery. Oxford: Oxford University Press.

  • Antoniou, A. 2021. ‘A pragmatic approach to the ontology of models’: Synthese 199: 6645–6664. https://doi.org/10.1007/s11229-021-03085-9.

  • Blatti, S., and S. Lapointe (eds.) 2016. Ontology after Carnap. Oxford: Oxford University Press.

  • Carnap, R. 1956. Empiricism, semantics, and ontology. Reprinted in Meaning and necessity: A study in semantics and modal logic. Enlarged edition (first published in 1950). Chicago: University of Chicago Press.

  • Carnap, R. 1962. Logical foundations of probability (2nd edition). Chicago: University of Chicago Press.

  • Carnap, R. 1966. Philosophical foundations of physics: an introduction to the philosophy of science. New York: Basic Books.

  • Cartwright, N. 1989. Nature’s capacities and their measurement. Oxford: Oxford University Press.

  • Cartwright, N. 2007. Hunting causes and using them: approaches in philosophy and economics. Cambridge: Cambridge University Press.

  • Cartwright, N., and J. Pemberton. 2013. Aristotelian powers. In Powers and capacities in philosophy: the new Aristotelianism, eds. R. Groff, and J. Greco. 93–112. New York: Routledge.

  • Chakravartty, A. 2005. Causal realism: Events and processes. Erkenntnis 63(1): 7–31. https://doi.org/10.1007/s10670-005-4411-4

  • Cinelli, C., A. Forney, and J. Pearl. 2022. ‘A Crash course in good and bad controls’: Sociological Methods & Research. https://doi.org/10.1177/00491241221099552.

    Article  Google Scholar 

  • Danks, D. 2015. ‘Goal-dependence in (scientific) ontology’: Synthese 192(11): 3601–3616. https://doi.org/10.1007/s11229-014-0649-1.

    Article  Google Scholar 

  • David, M. 2022. The correspondence theory of truth. In The Stanford Encyclopedia of Philosophy (Summer 2022 Edition), ed. E. N. Zalta. https://plato.stanford.edu/archives/sum2022/entries/truth-correspondence/.

  • Eagle, A. 2007. Pragmatic causation. In Causation, physics, and the constitution of reality: Russell’s republic revisited, eds. H. Price, and R. Corry, 156–190. Oxford: Clarendon Press.

  • Eklund, M. 2009. Carnap and ontological pluralism. In Metametaphysics: new essays on the foundations of ontology, eds. D. Chalmers, D. Manley, and R. Wasserman, 130–156. Oxford: Oxford University Press.

  • Eklund, M. 2013. ‘Carnap’s metaontology’: Noûs 47(2): 229–249. https://doi.org/10.1111/j.1468-0068.2011.00830.x.

    Article  Google Scholar 

  • Esfeld, M. 2012. Causal realism. In Probabilities, laws, and structures, eds. Dieks, D., W. Gonzalez, S. Hartmann, et. al., 157–168. Dordrecht: Springer.

    Chapter  Google Scholar 

  • Fischer, E. 2023. ‘Actual causation and the challenge of purpose’: Erkenntnis, 1–21. https://doi.org/10.1007/s10670-023-00660-z.

  • Glymour, C., and M. R. Glymour. 2014. ‘Commentary: race and sex are causes’: Epidemiology (Cambridge, Massachusetts) 25(4): 488–490. https://doi.org/10.1097/EDE.0000000000000122.

    Article  Google Scholar 

  • Greenland, S., J. Pearl, and J. M. Robins. 1999. Causal diagrams for epidemiologic research. Epidemiology (Cambridge, Massachusetts) 10(1): 37–48.

  • Greiner, D. J., and D. B. Rubin. 2011. Causal effects of perceived immutable characteristics. Review of Economics and Statistics 93(3): 775–785.

    Article  Google Scholar 

  • Hall, N. 2004. Two concepts of causation. In Causation and counterfactuals, eds. J. Collins, N. Hall, and L. A. Paul, 225–276. Cambridge (Massachusetts): MIT Press.

  • Hernán, M. A., and S. L. Taubman. 2008. ‘Does obesity shorten life? The importance of well-defined interventions to answer causal questions’: International Journal of Obesity 32(3): 8–14. https://doi.org/10.1038/ijo.2008.82.

    Article  Google Scholar 

  • Hitchcock, C. 2007. How to be a causal pluralist. In Thinking about causes: from Greek philosophy to modern physics, eds. P. K. Machamer, and G. Wolters, 200–221. Pittsburgh: University of Pittsburgh Press.

  • Hitchcock, C. 2012. Events and times: a case study in means-ends metaphysics. Philosophical Studies 160(1): 79–96. https://www.jstor.org/stable/23262474.

    Article  Google Scholar 

  • Holland, P. W. 1986. ‘Statistics and causal inference’: Journal of American Statistical Association 81(396): 945–960. https://doi.org/10.2307/2289064.

    Article  Google Scholar 

  • Holland, P. W. 2003. Causation and race. ETS Research Report Series 2003(1): i–21.

    Article  Google Scholar 

  • Ibeling, D., and T. Icard. 2023. Comparing causal frameworks: Potential outcomes, structural models, graphs, and abstractions. arXiv preprint arXiv:2306.14351.

  • Kim, J. 1993. The non-reductivist’s troubles with mental causation. In Mental causation, eds. J. Heil and A. R. Mele, 189–210. Oxford: Oxford University Press.

  • Lauer, R. 2022. ‘Motivating a pragmatic approach to naturalized social ontology’: Journal for General Philosophy of Science 1–17. https://doi.org/10.1007/s10838-021-09581-3.

  • Lewis, D. 1973. Causation. Journal of Philosophy 73: 556–567.

    Article  Google Scholar 

  • Lewis, D. 1983. ‘New work for a theory of universals’: Australasian Journal of Philosophy 61(4): 343–377. https://doi.org/10.1080/00048408312341131.

  • Ludwig, D. 2016. ‘Ontological choices and the value-free ideal’: Erkenntnis 81(6): 1253–1272. https://doi.org/10.1007/s10670-015-9793-3.

    Article  Google Scholar 

  • Mumford, S. 2009. Causal powers and capacities. In The Oxford handbook of causation, eds. H. Beebee, C. Hitchcock, and P. Menzies, 265–278. Oxford: Oxford University Press.

  • Neyman, J. 1990. On the application of probability theory to agricultural experiments. Essay on principles. Section 9 (D. M. Dabrowska and T. P. Speed, Trans.). Statistical Science, 465–472. (Original work published 1923).

  • Paul, L. A. 2012. Metaphysics as modeling: the handmaiden’s tale. Philosophical Studies 160: 1–29.

    Article  Google Scholar 

  • Paul, L. A., and N. Hall. 2013. Causation: a user’s guide. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199673445.001.0001.

  • Pearl, J. 2009. Causality: Models, reasoning, and inference (2nd edition). Cambridge: Cambridge University Press.

  • Pearl, J. 2018. ‘Does obesity shorten life? Or is it the soda? On non-manipulable causes’: Journal of Causal Inference 6(2). https://doi.org/10.1515/jci-2018-2001.

  • Pearl, J., M. Glymour, and N. P. Jewell. 2016. Causal inference in statistics: a primer. Chichester, UK: John Wiley & Sons.

  • Price, H. 2001. Causation in the special sciences: the case for Pragmatism. In Stochastic causality, eds. M. C. Galavotti, P. Suppes, and D. Costantini. Stanford: CSLI Lecture Notes.

  • Price, H. 2007. Causal perspectivalism. In Causation, physics, and the constitution of reality: Russell’s republic revisited, eds. H. Price, and R. Corry, 250–292. Oxford: Clarendon Press.

  • Price, H. 2009. Metaphysics after Carnap: the ghost who walks. In Metametaphysics: new essays on the foundations of ontology, eds. D. Chalmers, D. Manley, and R. Wasserman, 320–346. Oxford: Oxford University Press.

  • Price, H. 2017. Causation, intervention and agency—Woodward on menzies and Price. In Making a difference: essays on the philosophy of causation, eds. H. Beebee, C. Hitchcock, and H. Price, 73–98. Oxford: Oxford University Press.

  • Rubin, D. B. 1974. ‘Estimating causal effects of treatments in randomized and nonrandomized studies’: Journal of Educational Psychology 66(5): 688–701. https://doi.org/10.1002/j.2333-8504.1972.tb00631.x.

    Article  Google Scholar 

  • Schurz, G., and A. Gebharter. 2016. ‘Causality as a theoretical concept: explanatory warrant and empirical content of the theory of causal nets’: Synthese 193(4): 1073–1103. https://doi.org/10.1007/s11229-014-0630-z.

    Article  Google Scholar 

  • Sen, M., and O. Wasow. 2016. Race as a bundle of sticks: designs that estimate effects of seemingly immutable characteristics. Annual Review of Political Science 19: 499–522.

    Article  Google Scholar 

  • Shrier, I., and R. W. Platt. 2008. Reducing bias through directed acyclic graphs. BMC Medical Research Methodology 8(1): 1–15.

    Article  Google Scholar 

  • Spirtes, P., C. Glymour, and R. Scheines. 2000. Causation, prediction and search. Cambridge (Massachusetts): MIT Press.

  • Suppes, P. 1970. A probabilistic theory of causality. Amsterdam: North-Holland Publishing Company.

  • Suzuki, E., T. Shinozaki, and E. Yamamoto. 2020. Causal diagrams: pitfalls and tips. Journal of Epidemiology 30(4): 153–162.

    Article  Google Scholar 

  • Thomasson, A. L. 2014. Ontology made easy. Oxford: Oxford University Press.

  • Weinberger, N. 2021. Comparing Rubin and Pearl’s causal modelling frameworks: a commentary on Markus (2021). Economics & Philosophy, 39(3):485–493.

  • Weinberger, N., P. Williams, and J. Woodward. 2023. The Worldly Infrastructure of Causation. PhilSci-Archive. http://philsci-archive.pitt.edu/id/eprint/22125.

  • Woodward, J. 2003. Making things happen: a theory of causal explanation. Oxford: Oxford University Press.

  • Woodward, J. 2007. Causation with a human face. In Causation, physics, and the constitution of reality: Russell’s republic revisited, eds. H. Price, and R. Corry, 66–105. Oxford: Oxford University Press.

  • Woodward, J. 2014. ‘A functional account of causation; or, a defense of the legitimacy of causal thinking by reference to the only standard that matters—usefulness (as opposed to metaphysics or agreement with intuitive judgment)’: Philosophy of Science 81(5): 691–713. https://doi.org/10.1086/678313.

    Article  Google Scholar 

  • Woodward, J. 2015. ‘Methodology, ontology, and interventionism’: Synthese 192(11): 3577–3599. https://doi.org/10.1007/s11229-014-0479-1.

    Article  Google Scholar 

  • Woodward, J. 2016. The problem of variable choice. Synthese 193(4): 1047–1072.

    Article  Google Scholar 

  • Woodward, J. 2017. Interventionism and the missing metaphysics. In Metaphysics and the philosophy of science: new essays, eds. M. H. Slater, and Z. Yudell, 193–228. Oxford: Oxford University Press.

  • Woodward, J. 2021. Causation with a human face: normative theory and descriptive psychology. Oxford University Press.

  • Wright, S. 1920. The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proceedings of the National Academy of Sciences 6: 320–332.

Download references

Acknowledgements

I am grateful to Wayne Myrvold and two anonymous reviewers for their invaluable feedback on earlier versions of this paper. I also thank Xiuyuan An, Weixin Cai, Eric Desjardins, Yousuf Hasan, Yichen Luo, Zihan Qu, Shuguo Tang and Shimin Zhao for their helpful comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zili Dong.

Ethics declarations

Conflict of interest

The author has no conflict of interest to declare.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, Z. The Ontology of Causation: A Carnapian-Pragmatist Approach. J Gen Philos Sci (2024). https://doi.org/10.1007/s10838-023-09669-y

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10838-023-09669-y

Keywords

Navigation