Jonah N. Schupbach

Books

Papers

2024 (with David H. Glass). "Conjunctive Explanations: When Are Two Explanations Better than One?" Synthese.
[ Article • Abstract ]
When is it explanatorily better to adopt a conjunction of explanatory hypotheses as opposed to committing to only some of them? Although conjunctive explanations are inevitably less probable than less committed alternatives, we argue that the answer is not `never'. This paper provides an account of the conditions under which explanatory considerations warrant a preference for less probable, conjunctive explanations. After setting out four formal conditions that must be met by such an account, we consider the shortcomings of several approaches. We develop an account that avoids these shortcomings and then defend it by applying it to a well-known example of explanatory reasoning in contemporary science.
2023. "On the Logical Structure of Best Explanations." Philosophy of Science.
[ Article • Abstract ]
Standard articulations of Inference to the Best Explanation (IBE) imply the uniqueness claim that exactly one explanation should be inferred in response to an explanandum. This claim has been challenged as being both too strong (sometimes agnosticism between candidate explanatory hypotheses seems the rational conclusion) and too weak (in cases where multiple hypotheses might sensibly be conjointly inferred). I propose a novel interpretation of IBE that retains the uniqueness claim while also allowing for agnostic and conjunctive conclusions. I then argue that a particular probabilistic explication of explanatory goodness helpfully guides us in navigating such options when using IBE.
2023 (with David H. Glass). "Conjunctive Explanation: Is the Explanatory Gain Worth the Cost?" In Schupbach and Glass (eds.), Conjunctive Explanations: The Nature, Epistemology, and Psychology of Explanatory Multiplicity.
[ Article • Abstract ]
This chapter develops and defends a formal epistemology of conjunctive explanation by determining the conditions under which multiple distinct explanations are better than one. The general approach is to identify an appropriate measure of explanatory goodness that can then be applied to conjunctive explanations. If a conjunctive explanation is to be preferred it needs to have greater explanatory virtue (e.g., power or scope) with respect to the evidence, but this explanatory gain is insufficient on its own. Given a conjunctive explanation’s greater complexity, it also has a cost associated with it and so a balance needs to be struck between the gain and the cost. We show how this can be achieved by employing a Bayesian measure of explanation proposed by I. J. Good which can be cashed out in terms of information. We also explore some properties of this measure and its application to conjunctive explanations and address the question of whether it is desirable in general to have more informative, less probable hypotheses when seeking for good explanations.
2021. "William Paley." In Goetz and Taliaferro (eds.), The Encyclopedia of Philosophy of Religion.
[ Article • Abstract ]
This entry provides a brief summary of the works of William Paley (1743–1805) that are of most interest and relevance to contemporary philosophy of religion.
2019. "Conjunctive Explanations and Inference to the Best Explanation." TEOREMA (invited contribution to a special issue on "Explanation in Science").
[ Article • Abstract ]
This paper explores one way in which discussions of the nature of scientific explanation can inform the proper statement of explanatory inference. Inference to the Best Explanation (IBE) advises reasoners to infer exactly one explanation. This uniqueness claim apparently binds us when it comes to "conjunctive explanations," distinct explanations that are nonetheless explanatorily better together than apart. To confront this worry, explanationists qualify their statement of IBE, stipulating that this inference form only adjudicates between competing hypotheses. However, a closer look into the nature of competition reveals problems for this qualified account. Given the most common explication of competition, this qualification artificially and radically constrains IBE's domain of applicability. Using a more subtle, recent explication of competition, this qualification no longer provides a compelling treatment of conjunctive explanations. In light of these results, I suggest a different strategy for accommodating conjunctive explanations. Instead of modifying the form of IBE, I suggest a new way of thinking about the structure of IBE's lot of considered hypotheses.
2018. "Robustness Analysis as Explanatory Reasoning." British Journal for the Philosophy of Science.
[2018 Popper Prize Winner • Article • Abstract ]
When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a unified, explanatory account of diversity in RAs. The resulting account is, I argue, truer to actual cases of RA in science; moreover, this account affords us a helpful, new foothold on the logic undergirding RAs.
2018. "Troubles for Bayesian Formal Epistemology?" Res Philosophica.
[ Article • Preprint • Abstract ]
This paper responds to Terry Horgan's recent critique of Bayesian formal epistemology ("Troubles for Bayesian formal epistemology." Res Philosophica, 94(2):233–255, 2017). I argue that each of Horgan's criticisms misses its mark when Bayesianism is viewed as putting forward an inductive logic of confidences. Along the way, I explore the nature, scope, and limits of a defensible brand of Bayesianism.
2017 (with David H. Glass). "Hypothesis Competition Beyond Mutual Exclusivity." Philosophy of Science.
[ Article • Preprint • Abstract ]
Competition between scientific hypotheses is generally not a matter of mutual exclusivity. Consistent hypotheses can compete to varying degrees either directly or indirectly via the evidence. We motivate and defend a particular account of hypothesis competition by showing how it captures these features. Computer simulations of Bayesian inference are used to highlight the limitations of adopting mutual exclusivity as a simplifying assumption to model scientific reasoning, particularly due to the exclusion of hypotheses that may be true, while discussion of a case study demonstrates the subtleties involved in hypothesis competition in scientific practice.
2017. "Inference to the Best Explanation, Cleaned Up and Made Respectable." In McCain and Poston (eds.), Best Explanations: New Essays on Inference to the Best Explanation.
[ Preprint • Abstract ]
Despite decades of focused philosophical investigation, Inference to the Best Explanation (IBE) still lacks a precise articulation and compelling defense. The primary reason for this is that it is not at all clear what it means for a hypothesis to be the best available explanation of the evidence. This paper first seeks to rectify this problem by developing a formal explication of the explanatory virtue of power. A resulting account of IBE is then evaluated as a form of uncertain inference. Overall, this paper offers a precise account and novel defense of one important version of IBE.
2017. "Experimental Explication." Philosophy and Phenomenological Research.
[ Article • Abstract ]
Two recently popular metaphilosophical movements, formal philosophy and experimental philosophy, promote what seem to be conflicting methodologies. Nonetheless, I argue that the two can be mutually supportive. I propose an experimentally-informed variation on explication, a powerful formal philosophical tool introduced by Carnap. The resulting method, which I call "experimental explication," provides the formalist with a means of responding to explication's gravest criticism. Moreover, this method introduces a philosophically salient, positive role for survey-style experiments while steering clear of several objections that critics of "positive experimental philosophy" raise. Thus, it provides the experimentalist with a more defensible example of how empirical work can have positive philosophical import. For these reasons, experimental explication should appeal to experimental philosophers (at least those working within the positive program) and formal philosophers alike.
2017 (with Igor Douven). "Formal Epistemology." Oxford Handbooks Online.
[ Article • Abstract ]
Formal epistemology is a young but vibrant field of research in analytic philosophy. This entry highlights its major achievements and gives a sense of what can be accomplished by addressing problems from mainstream epistemology with the use of logic, probability theory, computer simulations, and other formal tools. The historical roots of the field are also described, and there is a discussion of new questions that have been raised by formal epistemology that should also be of interest to mainstream epistemologists.
2016. "Competing Explanations and Explaining-Away Arguments." Theology and Science.
[ Article • Preprint • Abstract ]
An "explaining-away argument" [EAA] aims to discredit some explanatory hypothesis by appealing to the explanatory power of an alternative hypothesis. Nietzsche's genealogical argument against theism and Darwin's case against Paley's "old argument of design in nature" are famous examples. In order for EAAs to have their negative force, they must satisfy several conditions. After clarifying these conditions, I focus in on one in particular: the two hypotheses in question offer potential explanations that compete with one another. I develop a formal account of what it takes for potential explanations to compete, and I use this account to argue that EAAs are often misapplied today. This is due to the fact that philosophers often fail to appreciate the subtle line dividing competing from non-competing explanations.
2016. "Experimental Philosophy Meets Formal Epistemology." In Sytsma and Buckwalter (eds.), Blackwell Companion to Experimental Philosophy.
[ Article • 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. "Robustness, Diversity of Evidence, and Probabilistic Independence." In Mäki, Votsis, Ruphy, Schurz (eds.), Recent Developments in the Philosophy of Science: EPSA13 Helsinki.
[ Article • 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.
2015 (with Igor Douven). "The Role of Explanatory Considerations in Updating." Cognition.
[ Article • Abstract ]
There is an ongoing controversy in philosophy about the connection between explanation and inference. According to Bayesians, explanatory considerations should be given weight in determining which inferences to make, if at all, only insofar as doing so is compatible with Strict Conditionalization. Explanationists, on the other hand, hold that explanatory considerations can be relevant to the question of how much confidence to invest in our hypotheses in ways which violate Strict Conditionalization. The controversy has focused on normative issues. This paper investigates experimentally the descriptive question of whether judgments of the explanatory goodness of hypotheses do play a role when people revise their degrees of belief in those hypotheses upon the receipt of new evidence. We present the results of three experiments that together strongly support the predictive superiority of the explanationist position.
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.
2014 (with Jan Sprenger). "Explanatory Power and Explanatory Justice." Unpublished.
[ Article • Abstract ]
Crupi and Tentori (2012) propose a condition of adequacy for any Bayesian measure of explanatory power, which they call Explanatory Justice. They criticize Schupbach and Sprenger's (2011) account for failing to satisfy this condition, and they offer a new explanatorily just measure of explanatory power. In this paper, we investigate Explanatory Justice's merits as a condition of adequacy. We offer three arguments against this condition, thus supporting the idea that a measure of explanatory power should rather be unjust. Then, in order to ensure that the debate advances beyond a mere battle of intuitions, we offer some new empirical results. All of this strengthens the case for Schupbach and Sprenger's measure while simultaneously posing new challenges to Crupi and Tentori's alternative proposal.
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

2023. Review of The Last Writings of Thomas S. Kuhn: Incommensurability in Science, edited by Bojana Mladenović. The Review of Metaphysics.
[ Review • Preprint ]
2019. Review of Truth-Seeking by Abduction, by Ilkka Niiniluoto. Notre Dame Philosophical Reviews.
[ Review ]
2018. Review of Formal Epistemology and Cartesian Skepticism: In Defense of Belief in the Natural World, by Tomoji Shogenji. Notre Dame Philosophical Reviews.
[ Review ]
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 ]

Dissertation

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).

Presentations

The Disjunction Objection in the Jamesian Balance. [ Venues ]
16th Orange Beach Epistemology Workshop; University of Alabama; Orange Beach, Alabama; May 14-15, 2024.
Trimming IBE's Hedges: In Defense of Naive Explanatory Inference. [ Venues ]
Philosophy Department Colloquium; Simon Fraser University; Burnaby, British Columbia, Canada; February 9, 2024 (Invited).

Philosophy Department Colloquium; University of Illinois; Urbana-Champaign, Illinois; January 26, 2024 (Invited).
Creative Intelligence, Abduction, and Inference to the Best Explanation. [ Venues ]
XVIIth Congress on Logic, Methodology, and Philosophy of Science and Technology; Buenos Aires, Argentina; July 24-29, 2023.

Philosophy Department Colloquium; University of Illinois; Urbana-Champaign, Illinois; January 20, 2023 (Invited).
The Logical Structure of Best Explanations. [ Venues ]
28th Biennial Meeting of the Philosophy of Science Association; Pittsburgh, Pennsylvania; November 10-13, 2022.

8th Biennial Conference of the European Philosophy of Science Association; University of Turin, Italy; September, 2021.

Colloquium; Düsseldorf Center for Logic and Philosophy of Science; Düsseldorf, Germany; May 18, 2021.

British Society for the Philosophy of Science, Annual Conference; University of Kent; Canterbury, England; July 13-15, 2020.

Studies in Science and Technology colloquium; University of Minnesota; Minneapolis, Minnesota; December 6, 2019.
Computer Simulations and Conceptual Engineering. [Video] [ Venues ]
ARCHÉ Conceptual Engineering Seminar; ARCHÉ Philosophical Research Centre; University of St. Andrews; St. Andrews, Scotland; April 20, 2021 (Invited).
Conjunctive Explanations (with David Glass). [ Venues ]
27th Biennial Meeting of the Philosophy of Science Association; Baltimore, Maryland; November 19-22, 2020.

7th Biennial Conference of the European Philosophy of Science Association; University of Geneva; Geneva, Switzerland; September 11-14, 2019.

Summer Seminar in Philosophy of Statistics; Virginia Tech University; Blacksburg, Virginia; August 10, 2019.

British Society for the Philosophy of Science, Annual Conference; Durham University; Durham, England; July 17-19, 2019
Inductive Logical Pluralism. [ Venues ]
Conference on Bayesian Epistemology: Perspectives and Challenges; Munich Center for Mathematical Philosophy, LMU Munich, Germany; August 10-14, 2020.

Philosophy Department colloquium; University of Notre Dame; Notre Dame, Indiana; November 30, 2018.

Formal Philosophy International Conference; Higher School of Economics; Moscow, Russia; October 1-2, 2018.
Reasoning Between Conjunctive and Competing Explanations. [ Venues ]
27th Annual Meeting of the European Society for Philosophy and Psychology; Athens, Greece; September 5-8, 2019.

Society for Philosophy and Psychology, Preconference; University of California, San Diego; July 10, 2019.
IBE's Uniqueness Claim, Competition, and Conjunctive Explanations. [ Venues ]
11th MuST Conference in Philosophy of Science, "Models of Explanation"; University of Turin; Turin, Italy; June 11-13, 2018.
Logical Pluralism, Inference to the Best Explanation, and Bayesianism. [ Venues ]
Logic and Philosophy of Science Department colloquium; University of California, Irvine; Irvine, California; November 3, 2017.

School of Computing and Mathematics seminar; Ulster University; Belfast, Northern Ireland; June, 2017.

International Conference on Thinking; Brown University; Providence, Rhode Island; August 4-6, 2016.
When do Hypotheses Compete? (with David Glass). [ Venues ]
Philosophy Department colloquium; Western Michigan University; Kalamazoo, Michigan; October 13, 2017 (Alumni Achievement Award).

Northwest Philosophy Conference; North Idaho College; Coeur d'Alene, Idaho; October 9-10, 2015.
Isolating the Effects of Coherence. [ Venues ]
6th Biennial Conference of the European Philosophy of Science Association; University of Exeter; Exeter, England; September 8, 2017.

Workshop on Unification and Coherence; Düsseldorf Center for Logic and Philosophy of Science; Düsseldorf, Germany; January 16, 2014.
Hypothesis Competition Beyond Mutual Exclusivity (with David Glass). [ Venues ]
45th Annual Meeting of the Society for Exact Philosophy; University of Calgary; Calgary, Alberta; May 5-7, 2017.

Biennial Meeting of the Philosophy of Science Association.; Atlanta, Georgia; November 3-5, 2016.
Inference to the Best Explanation, Cleaned Up and Made Respectable. [ Venues ]
7th Orange Beach Epistemology Workshop; University of South Alabama; Orange Beach, Alabama; May 19-20, 2015.

5th Formal Epistemology Festival; University of Toronto; Toronto, Ontario, Canada; June 3-5, 2013.
Evolution, Theism, and Explaining-Away Arguments. [ Venues ]
Conference on Explaining and Explaining Away in Science and Religion; Ulster University; Belfast, Northern Ireland; January 8-9, 2015.
Robustness Analysis as Explanatory Reasoning. [ Venues ]
Working Seminar on Robustness Analysis; University of Helsinki; Helsinki, Finland; September 25-26, 2014.

Colloquium; Düsseldorf Center for Logic and Philosophy of Science; Düsseldorf, Germany; January 22, 2014.

1st Workshop on Inductive Logic and Confirmation in Science; University of Kent (Paris Campus); Paris, France; October 17-18, 2013.

4th Conference of the European Philosophy of Science Association; University of Helsinki; Helsinki, Finland; August 28-31, 2013.
Best Explanations, Bayes's Rule, and Bonus Points (with Igor Douven). [ Venues ]
The Eighth London Reasoning Workshop; Birkbeck, University of London; London, England; July 9-10, 2014 (presented by Igor Douven).

Institute of Cognitive and Brain Sciences seminar; University of California Berkeley; Berkeley, California; May 2, 2014.
Competing Explanations and Explaining-Away Arguments. [ Venues ]
Tanner Humanities Center; University of Utah; Salt Lake City, Utah; February 4, 2014.

7th Annual Philosophy of Religion Conference; Baylor University; Waco, Texas; January 27-28, 2012.
Experimental Explication. [ Venues ]
1st Pittsburgh-Tilburg Workshop: Formal Epistemology Meets Experimental Philosophy; Tilburg University; Tilburg, the Netherlands; September 29-30, 2011.
Comparing Probabilistic Measures of Explanatory Power. [ Venues ]
Biennial Meeting of the Philosophy of Science Association; Montreal, Quebec, Canada; November 4-6, 2010.

3rd Sydney-Tilburg Conference: The Future of Philosophy of Science; Tilburg University; Tilburg, the Netherlands; April 14-16, 2010.
The Logic of Explanatory Power (with Jan Sprenger). [ Venues ]
The Seventh Annual Formal Epistemology Workshop; Universität Konstanz; Konstanz, Germany; September 2-4, 2010 (schedule).

European Science Foundation Workshop on "Physical and Philosophical Perspectives on Probability, Explanation and Time"; Woudschouten; October, 2009 (presented by Jan Sprenger).

Progic 2009: 4th Workshop on Combining Probability and Logic; University of Groningen; Groningen, The Netherlands; September 17-19, 2009 (presented by Jan Sprenger).
Coherence: Philosophical Issues, Psychological Implications (with Adam Harris & Ulrike Hahn). [ Venues ]
The Fourth London Reasoning Workshop; Birkbeck, University of London; London, England; July 27-28, 2009 (presented by Adam Harris).
Confirming the Disconfirmed and Conjunction Fallacies. [ Venues ]
Vereniging voor Analytische Filosofie 2009 (Conference for the Dutch-Flemish Society for Analytic Philosophy); Tilburg University; Tilburg, the Netherlands; January 23, 2009.

Presented to the Seminar on Probability, Decision, and Uncertainty; Institut d'Histoire et de Philosophie des Sciences et des Techniques; Paris, France; January 16, 2009.

The Workshop on the Psychology of Argumentation and Inductive Reasoning; Tilburg University; Tilburg, the Netherlands; November 17-21, 2008.
How to Be (and How not to Be) a Bayesian Explanationist. [ Venues ]
Presented to the Formal Philosophy Seminar; Katholieke Universiteit; Leuven, Belgium; November 28, 2008 (Pictures).

The Second London-Paris-Tilburg Workshop in Logic and Philosophy of Science; Tilburg University; Tilburg, The Netherlands; October 24, 2008.
Is the Conjunction Fallacy Tied to Probabilistic Confirmation? [ Venues ]
The Workshop on Probability, Confirmation and Fallacies; Katholieke Universiteit; Leuven, Belgium; April 3 - April 7, 2008; schedule).

The First Western Michigan University Graduate Philosophy Conference; Kalamazoo, Michigan; November 30 - December 2, 2007 (Distinguished Alumnus Talk).
On the Alleged Impossibility of Bayesian Coherentism. [ Venues ]
The Fourth Annual Formal Epistemology Workshop; Carnegie Mellon University; Pittsburgh, Pennsylvania; May 31 - June 3, 2007 (schedule).

Foundations of the Formal Sciences VI: Reasoning about Probabilities and Probabilistic Reasoning; Universiteit van Amsterdam; Amsterdam, The Netherlands; May 2-5, 2007.

Appointments

Research Profile

Select Courses

• († = graduate course; ‡ = independent study)
• † S25: New Illustrations of the Logic of Science
• † S25: Metaphysics (with Anne Peterson)
• S24: Great Science Books (co-instructor)
• S24: Deductive Logic
• F22: Reasoning and Rational Decision Making
• S22: History and Philosophy of Science
• S20: Inductive Logic
• ‡ S19: Bayesianism
• † F18: Metaphysics and Logic (with Anne Peterson)
• † S18: Advanced Deductive Logic
• † S17: Advanced Inductive Logic
• † F15: Metaphysics of Modality (with Anne Peterson)
• † S15: Advanced Deductive Logic
• ‡ F13: Scientific Explanation & Explanatory Reasoning
• F13: Foundations of Probability and Statistics
• † S13: Foundations of Logic and Mathematics
• † S12: Symbolic Logic

Other Activities

• Templeton Project: Conjunctive Explanations: How Science and Religion Can Work Together
• Scientific Explanations, Competing and Conjunctive
• Inductive Logic and Confirmation in Science 2

Site Design

• Inspired by JC Beall's site design,
• Which was based on Ted Sider's