The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Of course, these goals are interwoven. For instance, predictive power is also an epistemic goal. Moreover, these goals are historically dynamic—see Footnote 33.
The notion of robustness we have in mind here is closely related to the following Chang’s argument for the benefits of toleration among rivaling scientific camps: “Faced with an insurmountable unpredictability, what rational agents have to do is clear: hedge our bets. Given that we do not know which line of inquiry will ultimately lead to our destination, we should keep multiple lines open, instead of pursuing one line faithfully to its dead end, only then to try a different one.” (Chang 2012, p. 211).
Hansson (2003) also makes—in reference to David Makinson—the distinction between actual and potential justification of beliefs.
Nevertheless, there have been accounts of pursuit worthiness with a clear epistemic flavor, such as the one by Laurie Anne Whitt. In response to McMullin’s approach, she remarks that “There seems to be no reason to accept the stipulation that epistemic appraisals are limited to contexts of acceptance.” (Whitt 1992, p. 616). See also footnote 19. Also Hasok Chang’s coherentist epistemic iteration addresses some aspects of pursuit worthiness assessment even though he does not explicitly discuss it as such (see also Sect. 1.3).
For a discussion on the criteria in view of which individual scientists choose which theories to pursue, see Whitt (1990).
For a detailed discussion on the difference between the epistemic and the practical pursuit worthiness, see Šešelja et al. (2012).
See, for example, Chang’s discussion of the pursuit worthiness of phlogistic chemistry during the development of Lavoisier’s program (Chang 2012).
In the remainder of the paper we will—for the sake of simplicity—use the terms “cognitive system”, “(scientific) theory” or “(scientific) hypothesis” interchangeably. It is clear though that especially in the early stages of their development, such cognitive structures have neither all the properties of a theory nor all the links which would make them sufficiently systematic, and yet, they can be more than just a hypothesis. For the compatibility of our approach with Vickers’ theory eliminativism (Vickers 2013, 2014) see Sect. 8.
For the sake of transparency we will give each criterion (or group of criteria) an appropriate name.
Bonjour remarks that making the criterion for consistency absolutely necessary might be an oversimplification. Moreover, recent research has shown that it is sensible to ask how inconsistent a theory is and that logical inconsistency can be considered to come in degrees as well. In order to measure such degrees syntactic approaches based on minimal inconsistent sets (Hunter and Konieczny 2008) or maximal consistent sets (Knight 2002) have been suggested, as well as semantic approaches employing paraconsistent models such as (Hunter 2002; Hunter and Konieczny 2005; Grant 1978; Grant and Hunter 2006, 2008; Ma et al. 2009).
It is interesting to notice that William Wimsatt emphasizes the role of two properties of scientific theories that are based on the inferential density, namely the robustness and the generative entrenchment of parts of cognitive systems. Given a directed graph of inferential connections “a robust node has multiple inferential paths leading to it and resists failure because of its multiple sources of support.” and the generative entrenchment of a node is given proportional to the “number of nodes reachable from that node” (Wimsatt 2007 p. 142).
“By devising a new system of theoretical concepts the theoretician makes an explanation available and thus enhances the coherence of the system. In this way the progress of theoretical science may be plausibly viewed as a result of the search for greater coherence.” (Bonjour 1985, p. 100).
For the precise distinction between the internal and external consistency, see Sect. 5.3.
Alexander Rueger’s criticism of Laudan’s criterion (Rueger 1996, p. 267) along the similar lines overlooks the fact that Laudan expresses his criterion only as a sufficient, but not a necessary one. In contrast, according to (Whitt 1992, pp. 616–617), Laudan’s criterion is not even sufficient for the evaluation of pursuit worthiness.
Note that even though the criteria constituting our account are similar to those explicated by Whitt, our approaches differ in two key respects. First, our account is formulated in terms of a coherentist account of epistemic justification, while Whitt’s approach is rooted in Laudan’s (1977) and McMullin’s (1976) methodological frameworks. Second, our account introduces a unificatory aspect to the evaluation in the context of pursuit and the context of acceptance by allowing for both to be presented within the same epistemic framework (namely, Bonjour’s coherentism).
In contrast, the notion of actual coherence regards a retrospective assessment, that is, an assessment of a theory in view of its epistemic performance up to a given point (for the difference between the prospective and the retrospective assessment, see Nickles (2006)).
Since Bonjour treats explanations and predictions as involving the same sort of inferential relations (see Bonjour 1985, p. 240, Note 15), we will do the same. It would be possible, of course, to introduce a separate criterion for the predictive power of a theory.
Even though we are not here discussing the notion of a scientific explanation, it is the task of an account of explanation fitting our account to be able to dismiss spurious explanations as non-scientific (e.g., if someone offers to “explain” all the phenomena by claiming that they occur because god wanted them that way). For instance, in view of a causal-mechanical account, most of spurious explanations can be rejected due to the fact that they do not offer any underlying causal mechanism.
As Friedel Weinert remarks: “Copernicus’ observations do not establish any new facts. \(\dots \) It is therefore fair to say that from an observational point of view, the Copernican and Ptolemaic systems were equivalent.” (Weinert 2009, pp. 24–25, italics in original).
Of course, “How much is ‘enough’?” is one of the essential questions of epistemic justification in the context of acceptance.
We are indebted to Steffen Ducheyne for suggesting van Helden’s paper to us.
We take a theory to consist of a certain set of propositions and all their consequences. We restrict the latter to the consequences which are known at the given time point since the coherence evaluation can only take into account the known consequences and thus the inconsistencies known at that time point. On the basis of new consequences it may turn out that a seemingly consistent theory is in fact inconsistent. Two other remarks are important at this point. First, we are of course aware of the fact that the language of propositional logic is rather suboptimal for the task of a proper formalization of scientific theories. We use it as a simplification (and so does Bonjour). It is an open question what formal language is best for this task, and if there is any one (!) such language at all. Second, according to the received view, it is often the case that especially (but not only) immature theories contain contradictions. To speak about consequences of such systems in terms of classical logic is not very helpful, since in face of contradictions classical logic derives anything. Logicians have developed various ways to cope with such situations by use of paraconsistent logics (see e.g.Béziau and Carnielli 2006; Batens et al. 2000).
Even though Thagard doesn’t clarify what he means by an inconsistency being isolated in the network of elements, he probably refers to avoiding the explosion which is inevitable in terms of classical logic. Some logics that are able to deal with inconsistencies block problematic applications of certain rules, such as disjunctive syllogism, to inconsistent formulas while at the same time allowing for the full classical derivative power for the consistent parts of a theory (see Batens 1999). In this sense they isolate inconsistencies since they prevent them from spreading.
For a detailed discussion on the pursuit worthiness of the theory of continental drift by means of the framework presented in this paper, see Šešelja and Weber (2012).
This was precisely the outcome of the expeditions conducted in the early 1930s, which included Dutch geologist Vening Meinesz and North American geologists Richard Field and Harry Hess. The results of their investigation confirmed an uneven distribution of radioactive constituents and thermal properties in the earth, which made Meinesz conclude that “in the actual earth there can be no doubt that convection currents must develop” (quoted from Oreskes 1999, p. 248).
Pera rightly pointed out that it is more accurate and awarding to view science as a discourse between multiple agents and nature (Pera 1994). However, in order to make our point it is fine to simplify matters.
There may of course be more than one dominant rival. In this case our discussion can easily be adjusted accordingly.
For instance, McMullin shows how the focus on prediction, which was characteristic for Babylonian astronomy, and on explanation, characteristic for Greek astronomy, conjoined into the complementary goals of the new science of the seventeenth century (McMullin 1984, p. 48).
McMullin (1984) as well as Laudan (1984) argue that shifts in standards of theory evaluation are based on epistemic reasons as well. For a discussion on Kuhnian approach to this problem, see Šešelja and Straßer (2012). For the problem of disagreement regarding the assessment of pursuit worthiness, see Straßer et al. (2014).
For instance, it could be argued that the criterion of predictive power is insufficiently represented in Bonjour’s account, or that the virtue of robustness of theories and theoretical entities—although indirectly addressed in terms of inferential density—could be presented in a more elaborated way (see footnotes 2 and 15).
Batens, D. (1999). Inconsistency-adaptive logics. In E. Orłowska (Ed.), Logic at work. Essays dedicated to the memory of Helena Rasiowa (pp. 445–472). New York: Physica Verlag (Springer).
Batens, D., Mortensen, C., Priest, G., & Van Bendegem J. P. (Eds.) (2000). Frontiers of paraconsistent logic. Baldock, UK: Research Studies Press.
Béziau, J.-Y., & Carnielli W. A. (Eds.) (2006). Paraconsistent logic with no frontiers. Studies in logic and practical reasoning. Amsterdam: North-Holland/Elsevier.
Bonjour, L. (1985). The structure of empirical knowledge. Cambridge, MA: Harvard University Press.
Bonjour, L. (1989). Replies and clarifications. In J. W. Bender (Ed.), The current state of the coherence theory (pp. 276–292). Dordrecht: Kluwer Academic Publishers.
Calcott, B. (2011). Wimsatt and the robustness family: Review of Wimsatt’s re-engineering philosophy for limited beings. Biology and Philosophy, 26, 281–293.
Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford: Oxford University Press.
Chang, H. (2011). The persistence of epistemic objects through scientific change. Erkenntnis, 75(3), 413–429.
Chang, H. (2012). Is water H2O? evidence, pluralism and realism. New York: Springer.
Curd, M. V. (1980). The Logic of Discovery: An Analysis of three approaches. In T. Nickles (Ed.), Scientific Discovery: Case Studies (pp. 201–219). Dordrecht: D. Reidel Publishing Company.
Douglas, H. E. (2009). Science, policy, and the value-free ideal. Pittsburgh: University of Pittsburgh Press.
Fitton, J. (1974). Velikovsky Mythistoricus. Chiron, I(1,2), 29–36.
Frankel, H. (1979). The reception and acceptance of continental drift theory as a rational episode in the history of science. In S. H. Mauskopf (Ed.), The reception of unconventional science (AAAS Selected Symposia Series) (pp. 51–89). Boulder, CO: Westview Press.
Friedman, M. (1974). Explanation and scientific understanding. The Journal of Philosophy, LXXI(1), 5–19.
Grant, J. (1978). Classifications for inconsistent theories. Notre Dame Journal of Formal Logic, 19(3), 435–444.
Grant, J., & Hunter, A. (2006). Measuring inconsistency in knowledgebases. Journal of Intelligent Information Systems, 27(2), 159–184.
Grant, J., & Hunter, A. (2008). Analysing inconsistent first-order knowledgebases. Artificial Intelligence, 172(8–9), 1064–1093.
Hansson, S. O. (2003). Ten philosophical problems in belief revision. Journal of Logic and Computation, 13(1), 37–49.
Hoyningen-Huene, P. (2006). Context of discovery versus context of justification and Thomas Kuhn. In J. Schickore & F. Steinle (Eds.), Revisiting discovery and justification: Historical and philosophical perspectives on the context distinction (pp. 119–131). Dordrecht: Springer.
Hunter, A. (2002). Measuring inconsistency in knowledge via quasi-classical models. In Eighteenth national Conference on Artificial intelligence. Menlo Park, CA, USA (pp. 68–73). American Association for Artificial Intelligence.
Hunter, A., & Konieczny, S. (2005). Approaches to measuring inconsistent information. In L. Bertossi, A. Hunter, & T. Schaub (Eds.), Inconsistency tolerance. Lecture Notes in Computer Science (Vol. 3300, pp. 191–236). Berlin: Springer.
Hunter, A., & Konieczny, S. (2008). Measuring inconsistency through minimal inconsistent sets. In G. Brewka & J. Lang (Eds.), KR (pp. 358–366). Menlo Park: AAAI Press.
Kitcher, P. (1981). Explanatory unification. Philosophy of Science, 48(4), 507–531.
Kitcher, P. (1989). Explanatory unification and the causal structure of the world. In W. S. Philip Kitcher (Ed.), Scientific explanation (pp. 410–505). Minneapolis: University of Minnesota Press.
Kitcher, P. (2000). Patterns of scientific controversies. In M. P. Peter Machamer & A. Baltas (Eds.), Scientific controversies: Philosophical and historical perspectives (pp. 21–39). Oxford: Oxford University Press.
Kitcher, P. (2001). Science, truth and democracy. New York: Oxford University Press.
Kleiner, S. A. (2003). Explanatory coherence and empirical adequacy: The problem of abduction, and the justification of evolutionary models. Biology and Philosophy, 18, 513–527.
Knight, K. (2002). Measuring inconsistency. Journal of Philosophical Logic, 31, 77–98.
Kuukkanen, J.-M. (2007). Kuhn, the correspondence theory of truth and coherentist epistemology. Studies in History and Philosophy of Science, 38, 555–566.
Lakatos, I. (1978). The methodology of scientific research programmes. Cambridge: Cambridge University Press.
Laudan, L. (1977). Progress and its problems: Towards a theory of scientific growth. London: Routledge & Kegan Paul Ltd.
Laudan, L. (1984). Science and values. Berkeley, CA: University of California Press.
Laudan, R. (1981) The recent revolution in geology and Kuhn’s Theory of scientific change. In: P. Asquith & I. Hacking (Eds.), PSA 1978: Proceedings of the 1978 biennial meeting of the Philosophy (pp. 227–239). Philosophy of Science Association.
Le Grand, H. E. (1988). Drifting continents and shifting theories. Cambridge: Cambridge University Press.
Ma, Y., Qi, G., Xiao, G., Hitzler, P., & Lin, Z. (2009). An anytime algorithm for computing inconsistency measurement. Knowledge Science, Engineering and Management (pp. 29–40). Springer.
McMullin, E. (1976). The fertility of theory and the unit for appraisal in science. In R. S. Cohen, P. K. Feyerabend, & M. W. Wartofsky (Eds.), Essays in memory of Imre Lakatos. Boston Studies in the Philosophy of Science (Vol. 39, pp. 395–432). Dordrecht: D. Reidel Publishing Company.
McMullin, E. (1984). The goals of natural science. Proceedings and Addresses of the American Philosophical Association, 58(1), 37–64.
Meheus, J. (Ed.) (2002). Inconsistency in science. Dordrecht: Kluwer.
Miller, A. I. (2002). Inconsistent Reasoning Toward Consistent Theories. In J. Meheus (Ed.), Inconsistency in science (pp. 35–41). Dordrecht: Kluwer.
Neurath, O. 1932/1933 (1983). Protocol statement. In R. S. Cohen & M. Neurath (Eds.), Philosophical papers 1913–1946 (pp. 91–99). Dordrecht: Reidel.
Nickles, T. (1980a). Introductory essay: Scientific discovery and the future of philosophy of science. In T. Nickles (Ed.), Scientific discovery: Case studies (pp. 1–59). Dordrecht: D. Reidel Publishing Company.
Nickles, T. (Ed.) (1980b) Scientific discovery: Case studies. Dordrecht: D. Reidel Publishing Company.
Nickles, T. (2006). Heuristic appraisal: Context of discovery or justification? In J. Schickore & F. Steinle (Eds.), Revisiting discovery and justification: Historical and philosophical perspectives on the context distinction (pp. 159–182). Dordrecht: Springer.
Oreskes, N. (1999). The rejection of continental drift: Theory and method in American Earth Science. Oxford: Oxford University Press.
Pera, M. (1994). The discourses of science. Chicago: The University of Chicago Press.
Priest, G. (2002). Inconsistency and the empirical sciences. In J. Meheus (Ed.), Inconsistency in science (pp. 119–128). Dordrecht: Kluwer.
Reichenbach, H. (1938). Experience and prediction. An analysis of the foundations and the structure of knowledge. Chicago: University of Chicago Press.
Rheinberger, H.-J. (1997). Toward a history of epistemic things: Synthesizing proteins in the test tube. Stanford: Stanford University Press.
Rueger, A. (1996). Risk and diversification in theory choice. Synthese, 109(2), 263–280.
Schickore, J., & Steinle, F. (2006a). Introduction: Revisiting the Context Distinction. In J. Schickore & F. Steinle (Eds.), Revisiting discovery and justification: Historical and philosophical perspectives on the context distinction (vii ed., p. xix). Dordrecht: Springer.
Schickore, J. & Steinle F. (Eds.) (2006b). Revisiting discovery and justification: Historical and philosophical perspectives on the context distinction. Dordrecht: Springer.
Šešelja, D., Kosolosky, L., & Straßer, C. (2012). Rationality of scientific reasoning in the context of pursuit: Drawing appropriate distinctions. Philosophica, 86, 51–82.
Šešelja, D., & Straßer, C. (2012). Kuhn and the question of pursuit worthiness. Topoi, 32, 9–19.
Šešelja, D., & Weber, E. (2012). Rationality and irrationality in the history of continental drift: Was the hypothesis of continental drift worthy of pursuit? Studies in History and Philosophy of Science, 43, 147–159.
Stelling, J., Sauer, U., Szallasi, Z., Doyle, F. J., & Doyle, J. (2004). Robustness of cellular functions. Cell, 118(6), 675–685.
Straßer, C., Šešelja, D., & Wieland, J. W. (2014). Withstanding Tensions: Scientific Disagreement and Epistemic Tolerance. In E. Ippoliti (Ed.), Heuristic Reasoning, Springer Series Studies in Applied Philosophy, Epistemology and Rational Ethics. Springer (forthcoming).
Thagard, P. (1981). The autonomy of a logic of discovery. In L. Sumner, J. G. Slater, & F. Wilson (Eds.), Pragmatism and purpose. Essays presented to Thomas A. Goudge (pp. 248–260). Toronto: University of Toronto Press.
Thagard, P. (1992). Conceptual revolutions. Princeton: Princeton University Press.
Thagard, P. (2000). Coherence in thought and action. Cambridge: MIT Press.
Tursman, R. (1987). Peirce’s theory of scientific discovery. Bloomington: Indiana University Press.
van Helden, A. (1974). The telescope in the seventeenth century. Isis, 65(1), 38–58.
Vickers, P. (2013). Understanding inconsistent science. Oxford: Oxford University Press.
Vickers, P. (2014). Scientific theory Eliminativism. Erkenntnis, 79, 111–126.
Weber, E. (1999). Unification: What is it, how do we Reach and why do we Want it? Synthese, 118(3), 479–499.
Weinert, F. (2009). Copernicus, Darwin, and Freud: Revolutions in the history and philosophy of science. Oxford: Wiley-Blackwell.
Whitt, L. A. (1990). Theory pursuit: Between discovery and acceptance. In: PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association (Vol. 1. pp. 467–483).
Whitt, L. A. (1992). Indices of theory promise. Philosophy of Science, 59, 612–634.
Wimsatt, W. C. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Cambridge: Harvard University Press.
Research for this paper was supported by the Research Fund of Ghent University by means of Research Projects 01D03807 and 01G01907. We are indebted to Erik Weber for comments on an earlier draft of this paper.
About this article
Cite this article
Šešelja, D., Straßer, C. Epistemic justification in the context of pursuit: a coherentist approach. Synthese 191, 3111–3141 (2014). https://doi.org/10.1007/s11229-014-0476-4
- Epistemic justification
- Explanatory power
- Pursuit worthiness