Igor Douven

In a celebrated experiment, Joshua Knobe showed that people are much more prone to attribute intentionality to an agent for a side effect of a given act when that side effect is harmful than when it is beneficial. This asymmetry has become known as ‘the Knobe Effect’. According to Knobe's Moral Valence Explanation, bad effects trigger the attributions of intentionality, whereas good effects do not. Many others believe that the Knobe Effect is best explained in terms of the high amount of blame attributed in the harm condition, and the low amount of praise attributed in the help condition. This Blame Hypothesis explains the high number of intentionality attributions in the harm condition in terms of the high degree of blame people ascribe, and the low number of intentionality attributions in the help conditions in terms of the low degree of praise people attribute. We replicated Knobe's original experiment and conducted a logistic regression on the results to probe more deeply into the relationship between attributions of intentionality and responsibility. The statistical analysis revealed a hitherto unknown interaction effect: intentionality correlates with blame, but not with praise. This interaction effect is consistent with the Moral Valence Hypothesis, but inconsistent with the Blame Hypothesis, as well as with two of the three other hypotheses discussed here.

According to the Lockean thesis, a proposition is believed just in case it is highly probable. While this thesis enjoys strong intuitive support, it is known to conflict with seemingly plausible logical constraints on our beliefs. One way out of this conflict is to make probability 1 a requirement for belief, but most have rejected this option for entailing what they see as an untenable skepticism. Recently, two new solutions to the conflict have been proposed that are alleged to be non-skeptical. We compare these proposals with each other and with the Lockean thesis, in particular with regard to the question of how much we gain by adopting any one of them instead of the probability 1 requirement, that is, of how likely it is that one believes more than the things one is fully certain of.

According to what is now commonly referred to as “the Equation” in the literature on indicative conditionals, the probability of any indicative conditional equals the probability of its consequent of the conditional given the antecedent of the conditional. Philosophers widely agree in their assessment that the triviality arguments of Lewis and others have conclusively shown the Equation to be tenable only at the expense of the view that indicative conditionals express propositions. This study challenges the correctness of that assessment by presenting data that cast doubt on an assumption underlying all triviality arguments

The Preface Paradox has led many philosophers to believe that, if it isassumed that high probability is necessary for rational acceptability, the principleaccording to which rational acceptability is closed under conjunction (CP)must be abandoned. In this paper we argue that the paradox is far less damaging to CP than is generally believed. We describe how, given certain plausibleassumptions, in a large class of cases in which CP seems to lead tocontradiction, it does not do so after all. A restricted version of CP canthus be maintained.

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

In van Fraassen's The Scientific Image we are told that the scientific anti‐realist need not appeal to some special semantics for scientific language. He can allegedly hold – just like his direct opponents typically do – that truth‐conditional semantics is appropriate both for claims about the observable and claims about the unobservable. However, I shall point out that this kind of semantics goes badly with the anti‐realist's epistemic attitude vis‐his the unobservable. In this paper an alternative semantics shall be outlined that is perfectly compatible with the rest of the anti‐realist's position. Although this alternative semantics will be seen to fly in the face of the established doctrine in the field, I shall argue that there is currently no good reason not to adopt it. It will further be pointed out that this semantics has something to be recommended from a realist perspective as well.

So far, color-naming studies have relied on a rather limited set of color stimuli. Most importantly, stimuli have been largely limited to highly saturated colors. Because of this, little is known about how people categorize less saturated colors and, more generally, about the structure of color categories as they extend across all dimensions of color space. This article presents the results from a large Internet-based color-naming study that involved color stimuli ranging across all available chroma levels in Munsell space. These results help answer such questions as how English speakers name a more complex color set, whether English speakers use so-called basic color terms (BCTs) more frequently for more saturated colors, how they use non-BCTs in comparison with BCTs, whether non-BCTs are highly consensual in less saturated parts of the solid, how deep inside color space basic color categories extend, or how they behave on the chroma dimension.

In previous published research (“Conditionals and Inferential Connections: A Hypothetical Inferential Theory,” Cognitive Psychology, 2018), we investigated experimentally what role the presence and strength of an inferential connection between a conditional’s antecedent and consequent plays in how people process that conditional. Our analysis showed the strength of that connection to be strongly predictive of whether participants evaluated the conditional as true, false, or neither true nor false. In this article, we re-analyse the data from our previous research, now focussing on the semantics of conditionals rather than on how they are processed. Specifically, we use those data to compare the main extant semantics with each other and with inferentialism, a semantics according to which the truth of a conditional requires the presence of an inferential connection between the conditional’s component parts.

The Principle of the Benefit of Doubt dictates that, whenever reasonably possible, we interpret earlier-day scientists as referring to entities posited by current science. Putnam has presented the principle as supplementary to his Causal Theory of Reference in order to make this theory generally applicable to theoretical terms. The present paper argues that the principle is of doubtful standing. In particular, it will be argued that the principle lacks a justification and, indeed, is unjustifiable as it stands.

As part of an exceptionally lucid analysis of the Lottery Paradox, Dana Nelkin castigates the solutions to that paradox put forward by Laurence Bonjour and Sharon Ryan. According to her, these are “so finely tailored to lottery-like cases that they are limited in their ability to explain [what seem the intuitively right responses to such cases]”. She then offers a solution to the Lottery Paradox that allegedly has the virtue of being independently motivated by our intuitions regarding certain non-lottery-like cases. This note argues that Nelkin fails to show that her solution applies to other than lottery-like cases or in any event that it is more general than Bonjour’s and Ryan’s solutions.

This paper argues that if epistemological contextualism is correct, then not only have knowledge-ascribing sentences context-sensitive truth conditions, certain comparative and superlative constructions involving ‘know’ have context-sensitive truth conditions as well. But not only is there no evidence for the truth of the latter consequence, the evidence seems to indicate that it is false.The position I aim to criticize has been defended by, most notably, Stewart Cohen, Keith DeRose, and David Lewis. While the contextualist theories offered by these authors differ in their details, the problem to be presented seems to arise irrespective of these details. And though in most of the illustrations below I rely on Lewis's account, I could have made essentially the same points in terms of any of the other accounts.

This book contains ten papers that were presented at the symposium about the realism debate, held at the Center for Logic, Philosophy of Science and Philosophy of Language of the Institute of Philosophy at the Katholieke Universiteit Leuven on 10 and 11 March 1995. The first group of papers are directly concerned with the realism/anti-realism debate in the general philosophy of science. This group includes the articles by Ernan McMullin, Diderik Batens/Joke Meheus, Igor Douven and Herman de Regt. The papers of the second group concentrate on specific problems arising from the realism/anti-realism debate. Theo Kuipers' contribution discusses the problem of truth-approximation. Roger Vergauwen's article pertains to the issue of realism in the philosophy of mind and semantics. Jaap van Brakel's article focusses on the relation between everyday concepts and scientific concepts, and on the theory-dependence of observation. Paul Cortois investigates the relation between the question of realism and Kuhn's concept of incommensurability between scientific theories. The final group contains two papers on the realism/anti-realism debate in the special sciences. James Cushing discusses the problem of underdetermination in quantum mechanics and Jean Paul van bendegem addresses the question of the possiblity of an empiricist philosophy of mathematics.

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.