Igor Douven

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.

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.

If coherence is to have justificatory status, as some analytical philosophers think it has, it must be truth-conducive, if perhaps only under certain specific conditions. This paper is a critical discussion of some recent arguments that seek to show that under no reasonable conditions can coherence be truth-conducive. More specifically, it considers Bovens and Hartmann’s and Olsson’s “impossibility results,” which attempt to show that coherence cannot possibly be a truth-conducive property. We point to various ways in which the advocates of a coherence theory of justification may attempt to divert the threat of these results.

Edgington has proposed a solution to the sorites paradox in terms of ‘verities’, which she defines as degrees of closeness to clear truth. Central to her solution is the assumption that verities are formally probabilities. She is silent on what verities might derive from and on why they should be probabilities. This paper places Edgington’s solution in the framework of a spatial approach to conceptualization, arguing that verities may be conceived of as deriving from how our concepts relate to each other. Building on work by Kamp and Partee, this paper further shows how verities, thus conceived of, may plausibly be assumed to have probabilistic structure. The new interpretation of verities is argued to also help answer the question of what the verities of indicative conditionals are, a question which Edgington leaves open. Finally, the question of how to accommodate higher-order vagueness, given this interpretation, is addressed.

Unger (1974/2000) presents an argument for skepticism that significantly differs from the more traditional arguments for skepticism. The argument is based on two premises, to wit, that knowledge would entitle the knower to absolute certainty, and that an attitude of absolute certainty is always inadmissible from an epistemic viewpoint. The present paper scrutinizes the arguments that Unger provides in support of these premises and shows that none of them is tenable. It thus concludes that Unger's argument for skepticism fails to threaten the possibility of knowledge.

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.

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 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.

Various authors have recently argued that you cannot rationally stick to your belief in the face of known disagreement with an epistemic peer, that is, a person you take to have the same evidence and judgmental skills as you do. For, they claim, because there is but one rational response to any body of evidence, a disagreement with an epistemic peer indicates that at least one of you is not responding rationally to the evidence. Given that you take your peer to have the same judgmental skills as you do, and thus regard her to be equally good at assessing the evidence as you are, you will have as much reason for thinking that it is you who is not responding rationally to the evidence as for thinking that it is her. You thus have reason for thinking that your belief on the disputed matter is not a rational response to the evidence. Hence, you cannot rationally stick to your belief.

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.

We present a model for studying communities of epistemically interacting agents who update their belief states by averaging the belief states of other agents in the community. The agents in our model have a rich belief state, involving multiple independent issues which are interrelated in such a way that they form a theory of the world. Our main goal is to calculate the probability for an agent to end up in an inconsistent belief state due to updating. To that end, an analytical expression is given and evaluated numerically, both exactly and using statistical sampling. It is shown that, under the assumptions of our model, an agent always has a probability of less than 2% of ending up in an inconsistent belief state. Moreover, this probability can be made arbitrarily small by increasing the number of independent issues the agents have to judge or by increasing the group size. A real-world situation to which this model applies is a group of experts participating in a Delphi-study

This article addresses two questions related to colour categorization, to wit, the question what a colour category is, and the question how we identify colour categories. We reject both the relativist and universalist answers to these questions. Instead, we suggest that colour categories can be identified with the help of the criterion of psychological saliency, which can be operationalized by means of consistency and consensus measures. We further argue that colour categories can be defined as well-structured entities that optimally partition colour space. We provide some empirical support for this claim by presenting experimental results, which indicate that internal structure is a better predictor of colour categories than perceptual saliency

Conceptual spaces have become an increasingly popular modeling tool in cognitive psychology. The core idea of the conceptual spaces approach is that concepts can be represented as regions in similarity spaces. While it is generally acknowledged that not every region in such a space represents a natural concept, it is still an open question what distinguishes those regions that represent natural concepts from those that do not. The central claim of this paper is that natural concepts are represented by the cells of an optimally designed similarity space.

Regier, Kay, and Khetarpal report the results of computer simulations that cluster color stimuli on the basis of their coordinates in CIELAB space, one of two commonly used perceptual color spaces. Regier and coauthors find partitions of those stimuli that are strikingly similar to the way actual color lexicons partition color space. They do not argue for the custom-made clustering method used in their simulations, nor for the assumption of CIELAB space. The present paper aims to answer the question to what extent their computational results depend on these assumptions. It does this by applying a great variety of known clustering methods to Regier et al.’s stimuli, and by assuming not only CIELAB space but also CIELUV space, the other main color space.