•  636
    In this paper I discuss probabilistic models of experimental intervention, and I show that such models elucidate the intuition that observations during intervention are more informative than observations per se. Because of this success, it seems attractive to also cast other problems addressed by the philosophy of experimentation in terms of such probabilistic models. However, a critical examination of the models reveals that some of the aspects of experimentation are covered up rather than reso…Read more
  •  557
    An inductive logic is a system of inference that describes the relation between propositions on data, and propositions that extend beyond the data, such as predictions over future data, and general conclusions on all possible data. Statistics, on the other hand, is a mathematical discipline that describes procedures for deriving results about a population from sample data. These results include predictions on future samples, decisions on rejecting or accepting a hypothesis about the population, …Read more
  •  496
    This paper investigates the viability of the Bayesian model of belief change. Van Benthem (2003) has shown that a particular kind of information change typical for dynamic epistemic logic cannot be modelled by Bayesian conditioning. I argue that the problems described by van Benthem come about because the information change alters the semantics in which the change is supposed to be modelled by conditioning: it induces a shift in meanings. I then show that meaning shifts can be modelled in terms …Read more
  •  277
    Learning juror competence: a generalized Condorcet Jury Theorem
    with David Atkinson
    Politics, Philosophy and Economics 10 (3): 237-262. 2011.
    This article presents a generalization of the Condorcet Jury Theorem. All results to date assume a fixed value for the competence of jurors, or alternatively, a fixed probability distribution over the possible competences of jurors. In this article, we develop the idea that we can learn the competence of the jurors by the jury vote. We assume a uniform prior probability assignment over the competence parameter, and we adapt this assignment in the light of the jury vote. We then compute the poste…Read more
  •  274
    The discursive dilemma as a lottery paradox
    Economics and Philosophy 23 (3): 301-319. 2007.
    List and Pettit have stated an impossibility theorem about the aggregation of individual opinion states. Building on recent work on the lottery paradox, this paper offers a variation on that result. The present result places different constraints on the voting agenda and the domain of profiles, but it covers a larger class of voting rules, which need not satisfy the proposition-wise independence of votes
  •  263
    This paper offers a new angle on the common idea that the process of science does not support epistemic diversity. Under minimal assumptions on the nature of journal editing, we prove that editorial procedures, even when impartial in themselves, disadvantage less prominent research programs. This purely statistical bias in article selection further skews existing differences in the success rate and hence attractiveness of research programs, and exacerbates the reputation difference between the p…Read more
  •  232
    This paper concerns exchangeable analogical predictions based on similarity relations between predicates, and deals with a restricted class of such relations. It describes a system of Carnapian λγ rules on underlying predicate families to model the analogical predictions for this restricted class. Instead of the usual axiomatic definition, the system is characterized with a Bayesian model that employs certain statistical hypotheses. Finally the paper argues that the Bayesian model can be general…Read more
  •  218
    New theory about old evidence. A framework for open-minded Bayesianism
    with Sylvia9 Wenmackers
    Synthese 193 (4). 2016.
    We present a conservative extension of a Bayesian account of confirmation that can deal with the problem of old evidence and new theories. So-called open-minded Bayesianism challenges the assumption—implicit in standard Bayesianism—that the correct empirical hypothesis is among the ones currently under consideration. It requires the inclusion of a catch-all hypothesis, which is characterized by means of sets of probability assignments. Upon the introduction of a new theory, the former catch-all …Read more
  •  185
    A paper on how to adapt your probabilisitc beliefs when learning a conditional
  •  136
    This note contains a corrective and a generalization of results by Borsboom et al. (2008), based on Heesen and Romeijn (2019). It highlights the relevance of insights from psychometrics beyond the context of psychological testing.
  •  111
    Probabilistic Logics and Probabilistic Networks
    with Rolf Haenni, Gregory Wheeler, and Jon Williamson
    Synthese Library. 2010.
    Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
  •  101
    Probabilist antirealism
    Pacific Philosophical Quarterly 91 (1): 38-63. 2010.
    Until now, antirealists have offered sketches of a theory of truth, at best. In this paper, we present a probabilist account of antirealist truth in some formal detail, and we assess its ability to deal with the problems that are standardly taken to beset antirealism.
  •  91
    Conditioning and Interpretation Shifts
    Studia Logica 100 (3): 583-606. 2012.
    This paper develops a probabilistic model of belief change under interpretation shifts, in the context of a problem case from dynamic epistemic logic. Van Benthem [4] has shown that a particular kind of belief change, typical for dynamic epistemic logic, cannot be modelled by standard Bayesian conditioning. I argue that the problems described by van Benthem come about because the belief change alters the semantics in which the change is supposed to be modelled: the new information induces a shif…Read more
  •  72
    Mechanistic curiosity will not kill the Bayesian cat
    with Denny Borsboom and Eric-Jan Wagenmakers
    Behavioral and Brain Sciences 34 (4): 192-193. 2011.
    Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer specific issues that arise from the study of processes, one cannot expect them to provide constraints in general
  •  66
    This chapter1 concerns the relation between statistics and inductive logic. I start by describing induction in formal terms, and I introduce a general notion of probabilistic inductive inference. This provides a setting in which statistical procedures and inductive logics can be cap- tured. Speciacally, I discuss three statistical procedures (hypotheses testing, parameter estimation, and Bayesian statistics) and I show to what extend they can be captured by certain inductive logics. I end with s…Read more
  •  60
    Radical Uncertainty: Beyond Probabilistic Models of Belief
    Erkenntnis 79 (6): 1221-1223. 2014.
    Over the past decades or so the probabilistic model of rational belief has enjoyed increasing interest from researchers in epistemology and the philosophy of science. Of course, such probabilistic models were used for much longer in economics, in game theory, and in other disciplines concerned with decision making. Moreover, Carnap and co-workers used probability theory to explicate philosophical notions of confirmation and induction, thereby targeting epistemic rather than decision-theoretic as…Read more
  •  58
    Theory Change and Bayesian Statistical Inference
    Philosophy of Science 72 (5): 1174-1186. 2005.
    This paper addresses the problem that Bayesian statistical inference cannot accommodate theory change, and proposes a framework for dealing with such changes. It first presents a scheme for generating predictions from observations by means of hypotheses. An example shows how the hypotheses represent the theoretical structure underlying the scheme. This is followed by an example of a change of hypotheses. The paper then presents a general framework for hypotheses change, and proposes the minimiza…Read more
  •  58
    Psychiatric comorbidity: fact or artifact?
    with Hanna M. van Loo
    Theoretical Medicine and Bioethics 36 (1): 41-60. 2015.
    The frequent occurrence of comorbidity has brought about an extensive theoretical debate in psychiatry. Why are the rates of psychiatric comorbidity so high and what are their implications for the ontological and epistemological status of comorbid psychiatric diseases? Current explanations focus either on classification choices or on causal ties between disorders. Based on empirical and philosophical arguments, we propose a conventionalist interpretation of psychiatric comorbidity instead. We ar…Read more
  •  55
    Hypotheses and inductive predictions
    Synthese 141 (3). 2004.
    This paper studies the use of hypotheses schemes in generatinginductive predictions. After discussing Carnap–Hintikka inductive logic,hypotheses schemes are defined and illustrated with two partitions. Onepartition results in the Carnapian continuum of inductive methods, the otherresults in predictions typical for hasty generalization. Following theseexamples I argue that choosing a partition comes down to making inductiveassumptions on patterns in the data, and that by choosing appropriately an…Read more
  •  40
    Changing The Definition of The Kilogram: Insights For Psychiatric Disease Classification
    with Hanna M. Van Loo and Kenneth S. Kendler
    Philosophy, Psychiatry, and Psychology 26 (4): 97-108. 2019.
    In psychiatry, many scientists desire to move from a classification system based on symptoms toward a system based on biological causes. The idea is that psychiatric diseases should be redefined such that each disease would be associated with specific biological causes. This desire is intelligible because causal disease models often facilitate understanding and identification of new ways to intervene in disease processes. In its attempt to move from syndromal to specific etiological definitions,…Read more
  •  36
    Intervention and Identifiability in Latent Variable Modelling
    Minds and Machines 28 (2): 243-264. 2018.
    We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with uni…Read more
  •  34
    All agreed: Aumann meets DeGroot
    Theory and Decision 85 (1): 41-60. 2018.
    We represent consensus formation processes based on iterated opinion pooling as a dynamic approach to common knowledge of posteriors :1236–1239, 1976; Geanakoplos and Polemarchakis in J Econ Theory 28:192–200, 1982). We thus provide a concrete and plausible Bayesian rationalization of consensus through iterated pooling. The link clarifies the conditions under which iterated pooling can be rationalized from a Bayesian perspective, and offers an understanding of iterated pooling in terms of higher…Read more
  •  31
    Enantiomorphy and time
    International Studies in the Philosophy of Science 19 (2). 2005.
    This article argues that time-asymmetric processes in spacetime are enantiomorphs. Subsequently, the Kantian puzzle concerning enantiomorphs in space is reviewed to introduce a number of positions concerning enantiomorphy, and to arrive at a dilemma: one must either reject that orientations of enantiomorphs are determinate, or furnish space or objects with orientation. The discussion on space is then used to derive two problems in the debate on the direction of time. First, it is shown that cert…Read more
  •  29
    Abducted by Bayesians?
    Journal of Applied Logic 11 (4): 430-439. 2013.
  •  28
    Inherent Complexity: A Problem for Statistical Model Evaluation
    Philosophy of Science 84 (5): 797-809. 2017.
    This article investigates a problem for statistical model evaluation, in particular for curve fitting: by employing a different family of curves we can fit any scatter plot almost perfectly at apparently minor cost in terms of model complexity. The problem is resolved by an appeal to prior probabilities. This leads to some general lessons about how to approach model evaluation.
  •  26
    This edited collection showcases some of the best recent research in the philosophy of science. It comprises of thematically arranged papers presented at the 5th conference of the European Philosophy of Science Association, covering a broad variety of topics within general philosophy of science, and philosophical issues pertaining to specific sciences. The collection will appeal to researchers with an interest in the philosophical underpinnings of their own discipline, and to philosophers who wi…Read more
  •  25
    This paper explores the fact that linear opinion pooling can be represented as a Bayesian update on the opinions of others. It uses this fact to propose a new interpretation of the pooling weights. Relative to certain modelling assumptions the weights can be equated with the so-called truth-conduciveness known from the context of Condorcet's jury theorem. This suggests a novel way to elicit the weights.
  •  25
    Combining Probability and Logic
    with Fabio Cozman, Rolf Haenni, Federica Russo, Gregory Wheeler, and Jon Williamson
    Journal of Applied Logic 7 (2): 131-135. 2009.