Jonah N. Schupbach


  • Forthcoming. "Robustness, Diversity of Evidence, and Probabilistic Independence." In Mäki, Ruphy, Schurz and Votsis (eds.), Recent Developments in the Philosophy of Science: EPSA13 Helsinki.
    [ Preprint Abstract ]
  • In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity relevant to robustness analysis. I close by briefly outlining a promising alternative approach inspired by Horwich’s (1982) eliminative account of evidential diversity.
  • Forthcoming. "Experimental Philosophy Meets Formal Epistemology." In Sytsma and Buckwalter (eds.), Blackwell Companion to Experimental Philosophy.
    [ Preprint Abstract ]
  • Formal epistemology is just what it sounds like: epistemology done with formal tools. Coinciding with the general rise in popularity of experimental philosophy, formal epistemologists have begun to apply experimental methods in their own work. In this entry, I survey some of the work at the intersection of formal and experimental epistemology. I show that experimental methods have unique roles to play when epistemology is done formally, and I highlight some ways in which results from formal epistemology have been used fruitfully to advance epistemically-relevant experimental work. The upshot of this brief, incomplete survey is that formal and experimental methods often constitute mutually informative means to epistemological ends.
  • 2015 (with Igor Douven). "Probabilistic Alternatives to Bayesianism: The Case of Explanationism." Frontiers in Psychology.
    [ Article (open access) • Abstract ]
  • There has been a probabilistic turn in contemporary cognitive science. Far and away, most of the work in this vein is Bayesian, at least in name. Coinciding with this development, philosophers have increasingly promoted Bayesianism as the best normative account of how humans ought to reason. In this paper, we make a push for exploring the probabilistic terrain outside of Bayesianism. Non-Bayesian, but still probabilistic, theories provide plausible competitors both to descriptive and normative Bayesian accounts. We argue for this general idea via recent work on explanationist models of updating, which are fundamentally probabilistic but assign a substantial, non-Bayesian role to explanatory considerations.
  • 2015. "The Possibility of Coherentism and the Stringency of Ceteris Paribus Conditions." Theoria.
    [ Article (open access) • Abstract ]
  • In (Schupbach, 2008), I put forward a "possibility result" for Bayesian Coherentism, showing that there exist plausible sets of ceteris paribus conditions that imply that coherence is truth-conducive. Against this result, Schubert (2012) argues that the specific ceteris paribus conditions I consider are "jointly inconsistent". In this article, I prove to the contrary that these conditions can consistently be enforced while allowing degrees of coherence to vary. Next, I consider a related criticism, inspired by Olsson's (2005) constraints on ceteris paribus conditions. This leads to a general discussion of the principle(s) that should guide one in choosing appropriately stringent ceteris paribus conditions.
  • 2014. "Is the Bad Lot Objection Just Misguided?" Erkenntnis.
    [ Article Abstract ]
  • In this paper, I argue that van Fraassen’s "bad lot objection" against Inference to the Best Explanation [IBE] severely misses its mark. First, I show that the objection holds no special relevance to IBE; if the bad lot objection poses a serious problem for IBE, then it poses a serious problem for any inference form whatever. Second, I argue that, thankfully, it does not pose a serious threat to any inference form. Rather, the objection misguidedly blames a form of inference for not achieving what it never sets out to achieve in the first place.
  • 2012. "Is the Conjunction Fallacy tied to Probabilistic Confirmation?" Synthese.
    [ Article Abstract ]
  • Crupi et al. (2008) offer a confirmation-theoretic, Bayesian account of the conjunction fallacy —- an error in reasoning that occurs when subjects judge that Pr(h1 & h2|e) > Pr(h1|e). They introduce three formal conditions that are satisfied by classical conjunction fallacy cases, and they show that these same conditions imply that h1 & h2 is confirmed by e to a greater extent than is h1 alone. Consequently, they suggest that people are tracking this confirmation relation when they commit conjunction fallacies. I offer three experiments testing the merits of Crupi et al.’s account specifically and confirmation-theoretic accounts of the conjunction fallacy more generally. The results of Experiment 1 show that, although Crupi et al.’s conditions do seem to be causally linked to the conjunction fallacy, they are not necessary for it; there exist cases that do not meet their three conditions in which subjects still tend to commit the fallacy. The results of Experiments 2 and 3 show that Crupi et al.’s conditions, and those offered by other confirmation-theoretic accounts of the fallacy, are not sufficient for the fallacy either; there exist cases that meet all three of CFT’s conditions in which subjects do not tend to commit the fallacy. Additionally, these latter experiments show that such confirmation-theoretic conditions are at best only weakly causally relevant to the presence of the conjunction fallacy. Given these findings, CFT’s account specifically, and any general confirmation-theoretic account more broadly, falls short of offering a satisfying explanation of the presence of the conjunction fallacy.
  • 2011. "Comparing Probabilistic Measures of Explanatory Power." Philosophy of Science.
    [ Article Abstract ]
  • Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in particular is an accurate descriptor of explanatory judgments. Then, I discuss some interesting implications of this result for both the epistemology and the psychology of explanatory reasoning.
  • 2011. "New Hope for Shogenji's Coherence Measure." British Journal for the Philosophy of Science.
    [ Article Abstract ]
  • I show that the two most devastating objections to Shogenji's formal account of coherence necessarily involve information sets of cardinality n>2. Given this, I surmise that the problem with Shogenji's measure has more to do with his means of generalizing the measure than with the measure itself. I defend this claim by offering an alternative generalization of Shogenji's measure. This alternative retains the intuitive merits of the original measure while avoiding both of the relevant problems that befall it. In the light of all of this, I suggest that there is new hope for Shogenji's analysis: Shogenji's early and influential attempt at measuring coherence, when generalized in a subset-sensitive way, is able to clear its most troubling objections.
  • 2011 (with Jan Sprenger). "The Logic of Explanatory Power." Philosophy of Science.
    [ Article Abstract ]
  • This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, we briefly describe some promising future projects inspired by our account.
  • 2008. "On the Alleged Impossibility of Bayesian Coherentism." Philosophical Studies.
    [ Article Abstract ]
  • The success of Bovens and Hartmann’s recent "impossibility result" against Bayesian Coherentism relies upon the adoption of a specific set of ceteris paribus conditions. In this paper, I argue that these conditions are not clearly appropriate; certain proposed coherence measures motivate different such conditions and also call for the rejection of at least one of Bovens and Hartmann's conditions. I show that there exist sets of intuitively plausible ceteris paribus conditions that allow one to sidestep the impossibility result. This shifts the debate from the merits of the impossibility result itself to the underlying choice of ceteris paribus conditions.
  • 2007. "Must the Scientific Realist Be a Rationalist?" Synthese.
    [ Article Abstract ]
  • Marc Alspector-Kelly claims that Bas van Fraassen's primary challenge to the scientific realist is for the realist to find a way to justify the use of some mode of inference that takes him from the world of observables to knowledge of the world of unobservables without thereby abandoning empiricism. It is argued that any effort to justify such an "inferential wand" must appeal either to synthetic a priori or synthetic a posteriori knowledge. This disjunction turns into a dilemma for the empirically-minded realist as either disjunct leads to unwanted consequences. In this paper, I split the horns of this dilemma by arguing that the realist can justify one particular such mode of inference -- abduction -- without committing himself to rationalism. The realist may justify this mode of inference by appealing to the analytic a priori axioms of the probability calculus. I show that Peter Lipton's tripartite defense of abduction constitutes such a method of justification.
  • 2005. "On a Bayesian Analysis of the Virtue of Unification." Philosophy of Science.
    [ Article Abstract ]
  • In three recent papers, Wayne Myrvold (1996, 2003) and Timothy McGrew (2003) have developed Bayesian accounts of the virtue of unification. In his account, McGrew demonstrates that, ceteris paribus, a hypothesis that unifies its evidence will have a higher posterior probability than a hypothesis that does not. Myrvold, on the other hand, offers a specific measure of unification that can be applied to individual hypotheses. He argues that one must account for this measure in order to calculate correctly the degree of confirmation that a hypothesis receives from its evidence. Using the probability calculus, I prove that the two accounts of unification require the same underlying inequality; thus, McGrew and Myrvold have accounted for unification in fundamentally identical probabilistic terms. I then evaluate five putative counterexamples to this account and show that these examples, far from disqualifying it, serve to clarify our notion of unification by disentangling it from a host of other concepts.
  • 2005. "Paley's Inductive Inference to Design." Philosophia Christi.
    [ Article Abstract ]
  • In a recent article, Graham Oppy offers a lucid and intriguing examination of William Paley's design argument. Oppy sets two goals for his article. First, he sets out to challenge the "almost universal assumption" that Paley's argument is inductive by revealing it actually to be a deductive argument. Second, he attempts to expose Paley's argument as manifestly poor when interpreted in this way. I will argue that Oppy is unsuccessful in accomplishing his first goal, leaving his second goal quite irrelevant. Contrary to Oppy's interpretation, Paley's argument is best interpreted as an inference to the best explanation.

Book reviews

  • 2010. Review of Reflective Knowledge, by Ernest Sosa. The Review of Metaphysics.
    [ Review ]
  • 2010 (with Stephan Hartmann). Review of Depth: An Account of Scientific Explanation, by Michael Strevens. Notre Dame Philosophical Reviews.
    [ Review ]


  • 2011. Studies in the Logic of Explanatory Power. Department of History and Philosophy of Science, University of Pittsburgh; Edouard Machery and John Earman, supervisors.
    [ Pittsburgh ETD Abstract ]
  • Human reasoning often involves explanation. In everyday affairs, people reason to hypotheses based on the explanatory power these hypotheses afford; I might, for example, surmise that my toddler has been playing in my office because I judge that this hypothesis delivers a good explanation of the disarranged state of the books on my shelves. But such explanatory reasoning also has relevance far beyond the commonplace. Indeed, explanatory reasoning plays an important role in such varied fields as the sciences, philosophy, theology, medicine, forensics, and law.

    This dissertation provides an extended study into the logic of explanatory reasoning via two general questions. First, I approach the question of what exactly we have in mind when we make judgments pertaining to the explanatory power that a hypothesis has over some evidence. This question is important to this study because these are the sorts of judgments that we constantly rely on when we use explanations to reason about the world. Ultimately, I introduce and defend an explication of the concept of explanatory power in the form of a probabilistic measure. This formal explication allows us to articulate precisely some of the various ways in which we might reason explanatorily.

    The second question this dissertation examines is whether explanatory reasoning constitutes an epistemically respectable means of gaining knowledge. I defend the following ideas: The probability theory can be used to describe the logic of explanatory reasoning, the normative standard to which such reasoning attains. Explanatory judgments, on the other hand, constitute heuristics that allow us to approximate reasoning in accordance with this logical standard while staying within our human bounds. The most well known model of explanatory reasoning, Inference to the Best Explanation, describes a cogent, nondeductive inference form. And reasoning by Inference to the Best Explanation approximates reasoning directly via the probability theory in the real world. Finally, I respond to some possible objections to my work, and then to some more general, classic criticisms of Inference to the Best Explanation. In the end, this dissertation puts forward a clearer articulation and novel defense of explanatory reasoning. (Defended on June 14, 2011).



Assistant Professor of Philosophy at the University of Utah. My teaching and research interests have to do with the study of human reasoning. I have ongoing research projects in the philosophy of science (pertaining to explanation, confirmation, and scientific method), mainstream epistemology (regarding the internalism / externalism debate, nature of understanding, and induction), formal epistemology (on inductive logics, explication, and formal accounts of epistemic coherence), and the psychology of human reasoning (heuristics and biases, and fallacies).

Some Recent Teaching

Other Activities

Site Design