Search

The paper addresses the problem of imaginative resistance in science, that is, why and under what circumstances imagination sometimes resists certain scenarios. In the first part, the paper presents and discusses two accounts concerning the problem and relevant for the main thesis of this study. The first position is that of Gendler (Journal of Philosophy 97:55–81, 2000), (Gendler, in: Nichols (ed) The Architecture of the Imagination: New essays on pretence, possibility and fiction, Oxford University Press, New York, 2006a), (Gendler & Liao, in: Gibson, Carroll (eds) The routledge companion to philosophy of literature, Routledge, New York, 2016), according to which imaginative resistance mainly concerns evaluative scenarios, presenting deviant moral attitudes. The second account examined is that of Kim et al. (in: Cova, Réhault (eds) Advances in experimental philosophy of aesthetics, Bloomsbury, London, 2018), who insisted on the link between imaginative resistance on the one hand and counterfactual and counterdescriptive scenarios on the other. In the light of both theories, this paper discusses the importance of addressing the problem of imaginative resistance in the scientific enterprise in the light of some mechanisms of embodied simulation, based on the activity of mirror neurons and investigated within the framework of the Embodied Simulation Theory. [ABSTRACT FROM AUTHOR]

In a recent paper, Negri and Pavlović (Studia Logica 1–35, 2020) have formulated a decidable sequent calculus for the logic of agency, specifically for a deliberative see-to-it-that modality, or dstit. In that paper the adequacy of the system is demonstrated by showing the derivability of the axiomatization of dstit from Belnap et al. (Facing the future: agents and choices in our indeterminist world. Oxford University Press, Oxford, 2001). And while the influence of the latter book on the study of logics of agency cannot be overstated, we note that this is not the only axiomatization of that modality available. In fact, an earlier (and arguably purer) one was offered in Xu (J Philosophical Logic 27(5):505–552, 1998). In this article we fill this lacuna by proving that this alternative axiomatization is likewise readily derivable in the system of Negri and Pavlović (Studia Logica 1–35, 2020). [ABSTRACT FROM AUTHOR]

In this paper I will evaluate whether some knowledge states that are interpretatively derived from statistical mechanical probabilities could be somehow relevant in actual practices, as famously rejected by Albert (Time and chance, Harvard University Press, 2000). On one side, I follow Frigg (in: Ernst & Hüttermann (eds) Probability in Boltzmannian statistical mechanics, 2010) in rejecting the causal relevance of knowledge states as a mere byproduct of misinterpreting this theoretical field. On the other side, I will argue against Uffink (in: Beisbart & Hartmann (eds) Probabilities in physics, Oxford University Press, 2011) that probability-represented epistemic states cannot be explanatorily relevant, because (i) probabilities cannot faithfully represent significant epistemic states, and (ii) those states cannot satisfactorily account for why an agent should theoretically believe or expect something. [ABSTRACT FROM AUTHOR]

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma (Pincock in: Reutlinger A, Saatsi J (eds) Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible (Morrison in Reconstructing reality, Oxford University Press, Oxford, 2015). Others suggest that there is a set of necessary features that can unify all explanations under a single account (Potochnik in Idealization and the aims of science, Chicago University Press, Chicago, 2017; Reutlinger in Reutlinger A, Saatsi J (eds) Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock's dilemma. [ABSTRACT FROM AUTHOR]