This paper investigates the logic of compatibility as a ground for the logic of conditionals. We identify a family of principles expressing key properties of compatibility, which can be coherently ordered. Assuming that conditionals are definable in terms of incompatibility—the negation of compatibility—each of the principles identified yields corresponding principles governing conditionals. Clarifying these derivability relations provides a new perspective on several existing accounts of conditionals.

Science communication is a broad field and involves very diverse activities. This paper aims to illuminate and partly systematise the diversity of science communication. We focus on three important dimensions: size of the audience, frequency of interaction, and decision-making relevance. Based on them, we introduce a three-dimensional space of science communication wherein particular scenarios can be located. We argue that relevant challenges for science communication are particularly associated with certain areas of this space. Based on the proposed framework, we also address potential strategies and developments in science communication.

According to the analysis of concessive conditionals suggested by Crupi and Iacona, a concessive conditional p ↪ q is adequately formalized as a conjunction of conditionals. This paper presents a sound and complete axiomatic system for concessive conditionals so understood. The soundness and completeness proofs that will be provided rely on a method that has been employed by Raidl, Iacona, and Crupi to prove the soundness and completeness of an analogous system for evidential conditionals.

According to the view of conditionals named inferentialism, a conditional holds when its consequent can be inferred from its antecedent. This paper identifies some major challenges that inferentialism has to face, and uses them to assess three accounts of conditionals: one is the classical strict account, the other two have recently been proposed by Douven and Rott. As will be shown, none of the three proposals meets all challenges in a fully satisfactory way. We argue through novel formal results that a variation of the evidential account of conditionals suggested by Crupi and Iacona is the most promising candidate to develop inferentialism in a coherent formal framework.

Wason's selection task is a paramount experimental problem in the study of human reasoning, often connected with the celebrated ravens paradox in the philosophical literature. Various normative accounts of the selection task rely on a Bayesian approach. Some claim vindication of participants' rationality. Others don't, thus following Wason's original intuition that observed responses are mistaken. In this article we argue that despite claims to the contrary, all these accounts actually speak to the same effect: Wason was right. First, we provide a new accuracy-based analysis of the selection task that includes the existing proposals as special cases. We then show on this basis that none can actually vindicate participants' rationality. We conclude that all normative renditions considered eventually concur: all in all, Bayesians should follow Wason in the selection task.

This paper develops a formal theory of non-monotonic consequence which differs from most extant theories in that it assumes Contraposition as a basic principle of defeasible reasoning. We define a minimal logic that combines Contraposition with three uncontroversial inference rules, and we prove some key results that characterize this logic and its possible extensions.

In 2022 came out Cosmology in the Early Modern Age: A Web of Ideas (Dordrecht, Springer), an important and ambitious book by two Italian scholars, Paolo Bussotti and Brunel- lo Lotti. The book is the result of the collaboration between a historian of science and mathematics and a historian of philosophy, a collaboration - one might add - that is indispensable for addressing the topic of cosmology, which is rich in content and implications and which runs through modern thought between Copernicus and Leibniz. The relationship between the history of philosophy and the history of science is a subject that the tradition of the << Rivista di Filosofia >> has widely explored. The << Rivista di Filosofia >> has therefore invited Vincenzo Crupi, Antonella Del Prete and Flavia Marcacci to discuss the book. Bussotti and Lotti's reply concludes the discussion.

The following copyright notice is a publisher requirement: This book chapter has been published in The Drive for Knowledge: The Science of Human Information Seeking edited by Irene Cogliati Dezza, Eric Schulz and Charley M. Wu, https://doi.org/10.1017/9781009026949. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © 2022 Cambridge University Press

Bayesian approaches to human cognition have been extensively advocated in the last decades, but sharp objections have been raised too within cognitive science. In this paper, we outline a diagnosis of what has gone wrong with the prevalent strand of Bayesian cognitive science (here labelled pure Bayesian cognitive science), relying on selected illustrations from the psychology of reasoning and tools from the philosophy of science. Bayesians’ reliance on so-called method of rational analysis is a key point of our discussion. We tentatively conclude on a constructive note, though: an appropriately modified variant of Bayesian cognitive science can still be coherently pursued, as some scholars have noted.

Consider the task of selecting a medical test to determine whether a patient has a particular disease. Normatively, this requires taking into account (i) the prior probability of the disease, (ii) the likelihood---for each available test---of obtaining a positive result if the medical condition is present or absent, respectively, and (iii) the utilities for both correct and incorrect treatment decisions based upon each possible test result. But these quantities may not be precisely known. Are there strategies that could help identify the test with the highest utility given incomplete information? Here we consider the Likelihood Difference Heuristic (LDH), a simple heuristic that selects the test with the highest difference between the likelihood of obtaining a true positive and a false positive test result, ignoring all other information. We prove that the LDH is optimal when the probability of the disease equals the therapeutic threshold, the probability for which treating the patient and not treating the patient have the same expected utility. By contrast, prominent models of the value of information from the literature, such as information gain, probability gain, and Bayesian diagnosticity, are not optimal under these circumstances. Further results show how, depending on the relationship of the therapeutic threshold and prior probability of the disease, it is possible to determine which likelihoods are more important for assessing tests' expected utilities. Finally, to illustrate the potential relevance for real-life contexts, we show how the LDH might be applied to choosing tests for screening of latent tuberculosis infection.

This paper investigates the logic of reasons. Its aim is to provide an analysis of the sentences of the form ‘p is a reason for q’ that yields a coherent account of their logical properties. The idea that we will develop is that ‘p is a reason for q’ is acceptable just in case a suitably defined relation of incompatibility obtains between p and ¬q. As we will suggest, a theory of reasons based on this idea can solve three challenging puzzles that concern, respectively, contraposing reasons, conflicting reasons, and supererogatory reasons, and opens a new perspective on some classical issues concerning non-deductive inferences.

This paper outlines an account of concessive conditionals that rests on two main ideas. One is that the logical form of a sentence as used in a given context is determined by the content expressed by the sentence in that context. The other is that a coherent distinction can be drawn between a reading of ‘if’ according to which a conditional is true when its consequent holds on the supposition that its antecedent holds, and a stronger reading according to which a conditional is true when its antecedent supports its consequent. As we will suggest, the logical form of concessive conditionals can be elucidated by relying on this distinction.

In some recent works, Crupi and Iacona proposed an analysis of 'if' based on Chrysippus' idea that a conditional holds whenever the negation of its consequent is incompatible with its antecedent. This paper presents a sound and complete system of conditional logic that accommodates their analysis. The soundness and completeness proofs that will be provided rely on a general method elaborated by Raidl, which applies to a wide range of systems of conditional logic.

Searching for information in a goal-directed manner is central for learning, diagnosis, and prediction. Children continuously ask questions to learn new concepts, doctors do medical tests to diagnose their patients, and scientists perform experiments to test their theories. But what makes a good question? What principles govern human information acquisition and how do people decide which query to conduct to achieve their goals? What challenges need to be met to advance theory and psychology of human inquiry? Addressing these issues, we introduce the conceptual and mathematical ideas underlying different models of the value of information, what purpose these models serve in psychological research, and how they can be integrated in a unified formal framework. We also discuss the conflict between short- and long-term efficiency of prominent methods for query selection, and the resulting normative and methodological implications for studying human sequential search. A final point of discussion concerns the relations between probabilistic (Bayesian) models of the value of information and heuristic search strategies, and the insights than can be gained from bridging different levels of analysis and types of models. We conclude by discussing open questions and challenges that research needs to address to build a comprehensive theory of human information acquisition.

Hand hygiene among professionals plays a crucial role in preventing healthcare-associated infections, yet poor compliance in hospital settings remains a lasting reason for concern. Nudge theory is an innovative approach to behavioral change first developed in economics and cognitive psychology, and recently spread and discussed in clinical medicine. To assess a combined nudge intervention (localized dispensers, visual reminders, and gain-framed posters) to promote hand hygiene compliance among hospital personnel. A quasi-experimental study including a pre-intervention phase and a post-intervention phase (9 + 9 consecutive months) with 117 professionals overall from three wards in a 350-bed general city hospital. Hand hygiene compliance was measured using direct observations by trained personnel and measurement of alcohol-based hand-rub consumption. Levels of hand hygiene compliance were low in the pre-intervention phase: 11.44% of hand hygiene opportunities prescribed were fulfilled overall. We observed a statistically significant effect of the nudge intervention with an increase to 18.71% (p < 0.001) in the post-intervention phase. Improvement was observed in all experimental settings (the three hospital wards). A statistical comparison across three subsequent periods of the post-intervention phase revealed no significant decay of the effect. An assessment of the collected data on alcohol-based hand-rub consumption indirectly confirms the main result in all experimental settings. Behavioral outcomes concerning hand hygiene in the hospital are indeed affected by contextual, nudging factors to a significant extent. If properly devised, nudging measures can provide a sustainable contribution to increase hand hygiene compliance in a hospital setting.

Simpson’s Paradox has received a lot of attention in the contemporary literature. Typically, these presentations focus only on the qualitative structure of the phenomenon, and various explanations of its “paradoxicality” [1, 2]. In this paper, we discuss quantitative aspects of Simpson’s Paradox, via the use of various Bayesian measures of degree of confirmation. This leads to some interesting new results, both for the general phenomenon of Simpson’s Paradox and for Bayesian confirmation theory.