Francesco Nappo

This paper defends an epistemology for terrestrial black hole simulations based on Hesse’s theory of material analogy in science. We outline the main verdicts and recommendations of this approach, arguing that they not only fit the experimental practice but are also more credible than those supported by competing proposals. Our analysis questions the role of so-called ‘universality results’ in establishing an evidential function for current experiments, while also escaping the conclusion that we learn nothing about black holes from simulating them.

Beginning with her 1952 paper “Operational Definition and Analogy in Physical Theories”, Mary Hesse has championed an approach to analogy in scientific investigation that aims to capture the different ways in which analogies are used by working scientists. For various reasons, Hesse’s pioneering contribution, which culminated in her Models and Analogies in Science (1963–66), has often been misunderstood. This paper addresses what is arguably one of the most common misunderstandings of Hesse’s approach, having to do with the distinction between ‘formal’ and ‘material’ analogies in science. In response to concerns about the overly restrictive character of Hesse’s requirements on inductively strong analogical inferences, an interpretation and partial refinement of Hesse’s proposal will be provided that does justice to its significance for the epistemology of science.

This paper discusses the role of analogy in scientific revolutions. A challenge to Kuhn’s philosophy of science emerges from this study. On the one hand, the fact that many new paradigms (understood here as ‘exemplars’) have borne out of analogies is partly explained by the fact that, compatibly with Kuhn’s requirement of ‘open-endedness’ or ‘fruitfulness’ on paradigms, they contained immediately graspable indications as to their extensions to novel domains of phenomena. On the other hand, the consideration of scientific exemplars possessing an analogical origin also suggests that new exemplars may be successful partly as the result of drawing upon a common background of familiar experiences and training among competing scientific parties. It follows that, for reasons possibly endemic to Kuhn’s conception of science, scientific revolutions are unlikely to display the forms of incommensurability that Kuhn famously ascribed to them.

This article provides an epistemological assessment of climate analogue methods, with specific reference to the use of spatial analogues in the study of the future climate of target locations. Our contention is that, due to formal and conceptual inadequacies of geometrical dissimilarity metrics and the loss of relevant information, especially when reasoning from the physical to the socio-economical level, purported inferences from climate analogues of the spatial kind we consider here prove limited in a number of ways. Indeed, we formulate five outstanding problems concerning the search for best analogues, which we call the problem of non-uniqueness of the source, problem of non-uniqueness of the target, problem of average, problem of non-causal correlations and problem of inferred properties, respectively. In the face of such problems, we then offer two positive recommendations for a fruitful application of this methodology to the assessment of impact, adaptation and vulnerability studies of climate change, especially in the context of what we may prosaically dub “twin cities”. Arguably, such recommendations help decision-makers constrain the set of plausible climate analogues by integrating local knowledge relevant to the locations of interest.

Analogy has received attention as a form of inductive reasoning in the empirical sciences. Its role in mathematics has, instead, received less consideration. This paper provides a novel account of how an analogy with a more familiar mathematical domain can contribute to the confirmation of a mathematical conjecture. By reference to case-studies, we propose a distinction between an _incremental_ and a _non-incremental_ form of confirmation by mathematical analogy. We offer an account of the former within the popular framework of Bayesian confirmation theory. As for the non-incremental notion, we defend its role in rationally informing the prior credences of mathematicians in those circumstances in which no new mathematical evidence is introduced. The resulting framework captures many important aspects of the use of analogical inference in the domain of pure mathematics.

The widespread use of algorithms for prediction-based decisions urges us to consider the question of what it means for a given act or practice to be discriminatory. Building upon work by Kusner and colleagues in the field of machine learning, we propose a counterfactual condition as a necessary requirement on discrimination. To demonstrate the philosophical relevance of the proposed condition, we consider two prominent accounts of discrimination in the recent literature, by Lippert-Rasmussen and Hellman respectively, that do not logically imply our condition and show that they face important objections. Specifically, Lippert-Rasmussen’s definition proves to be over-inclusive, as it classifies some acts or practices as discriminatory when they are not, whereas Hellman’s account turns out to lack explanatory power precisely insofar as it does not countenance a counterfactual condition on discrimination. By defending the necessity of our counterfactual condition, we set the conceptual limits for justified claims about the occurrence of discriminatory acts or practices in society, with immediate applications to the ethics of algorithmic decision-making.

This paper addresses the role of analogical reasoning in archaeoastronomy - the discipline which studies the connections between the ancient monuments and the heavens. Archaeoastronomy is a highly interdisciplinary science, placed at the border between the humanities – especially archaeology – and the scientific approach to cultural heritage. As a consequence, its scientific foundations are a delicate matter. We plan to investigate here the question of what constitutes the evidence for analogical inferences in archaeoastronomy and to what extent one can achieve confirmation of archaeoastronomical hypotheses by means of such analogies. Our claim will be that, when deployed in accordance with the methodology articulated in this paper, analogies can be a highly effective epistemic tool for generating and supporting hypotheses about the relation of archaeological sites with astronomical events.

This paper defends the thesis of learning from non-causal models: viz. that the study of some model can prompt justified changes in one’s confidence in empirical hypotheses about a real-world target in the absence of any known or predicted similarity between model and target with regards to their causal features. Recognizing that we can learn from non-causal models matters not only to our understanding of past scientific achievements, but also to contemporary debates in the philosophy of science. At one end of the philosophical spectrum, my thesis undermines the views of those who, like Cartwright (Erkenntnis 70:45–58, 2009), follow Hesse (Models and Analogies in Science, Notre Dame, University of Notre Dame Press, 1963) in restricting the possibility of learning from models to only those situations where a model identifies some causal factors present in the target. At the other end of the spectrum, my thesis also helps undermine some extremely permissive positions, e.g., Grüne-Yanoff’s (Erkenntnis 70(1):81–99, 2009, Philos Sci 80(5): 850–861, 2013) claim that learning from a model is possible even in the absence of any similarity at all between model and target. The thesis that we can learn from non-causal models offers a cautious middle ground between these two extremes.

Reflections on the Practice of Physics has two admirable aims: on one hand, to contribute to a comprehensive historical understanding of Maxwell’s approach to physical inquiry; on the other, to extract philosophical lessons from the story of Maxwell’s astounding scientific breakthroughs. In line with an established tradition in scholarship (for example, Achinstein [1991]; Siegel [1991]; Harman [1998]), the authors defend the view that the method of ‘physical analogy’ that Maxwell first presented in the introductory section of his ‘On Faraday’s Lines of Force’, and continued to invoke throughout his later physical works, was in fact many different methods. The authors deserve praise for bringing new life to the narration of Maxwell’s alleged twists in methodology, merging historical and philosophical perspectives to defend it. In this review, I elaborate on some of the book’s main strengths and weaknesses, in the spirit of pursuing a constructive critical discussion.

Building upon work by Mary Hesse (1974), this paper aims to show that a single method of investigation lies behind Maxwell’s use of physical analogies in his major scientific works before the Treatise on Electricity and Magnetism. Key to understanding the operation of this method is to recognize that Maxwell’s physical analogies are intended to possess an ‘inductive’ function in addition to an ‘illustrative’ one. That is to say, they not only serve to clarify the equations proposed for an unfamiliar domain with a working interpretation drawn from a more familiar science, but can also be sources of defeasible yet relatively strong arguments from features of the more familiar domain to features of the less. Compared with the reconstructions by Achinstein (1991), Siegel (1991), Harman (1998) and others, which postulate a discontinuity in Maxwell’s approach to physical analogy, the account defended in this paper i) makes sense of the continuity in Maxwell’s remarks on scientific methodology, ii) explains his quest for a “mathematical classification of physical quantities” and iii) offers a new and more plausible interpretation of the debated episode of the introduction of the displacement current in Maxwell’s “On Physical Lines of Forces”.

In this paper, we offer a descriptive theory of analogical reasoning in mathematics, stating general conditions under which an analogy may provide genuine inductive support to a mathematical conjecture (over and above fulfilling the merely heuristic role of ‘suggesting’ a conjecture in the psychological sense). The proposed conditions generalize the criteria of Hesse in her influential work on analogical reasoning in the empirical sciences. By reference to several case studies, we argue that the account proposed in this paper does a better job in vindicating the use of analogical inference in mathematics than the prominent alternative defended by Bartha.

This paper proposes a framework for representing in Bayesian terms the idea that analogical arguments of various degrees of strength may provide inductive support to yet untested scientific hypotheses. On this account, contextual information plays a crucial role in determining whether, and to what extent, a given similarity or dissimilarity between source and target may confirm an empirical hypothesis over a rival one. In addition to showing confirmation by analogy compatible with the adoption of a Bayesian standpoint, the proposal outlined in this paper reveals a close agreement between the fulfillment of Hesse’s (Models and analogies in science, University of Notre Dame Press, 1963) criteria for analogical arguments capable of inductive support and the attribution of confirmatory power by the lights of Bayesian confirmation theory. In this sense, the Bayesian representation not only enriches a framework, Hesse’s, of enduring relevance for understanding scientific activity, but may offer something akin to a proof of concept of it.

Few contributions in the field of metaphysics can be compared, for their depth and impact, to the work of the American philosopher David K. Lewis. A feature of this work, which partly explain its great appeal, is its systematicity. Lewis’s views on intrinsicality, naturalness, supervenience, mind and modality, to mention just a few themes, constitute a unified and connected body of doctrines. As Lewis himself acknowledged in the introduction to the first volume of collected papers: “I should have liked to be a piecemeal, unsystematic philosopher, offering independent proposals on a variety of topics. It was not to be”. Surely there is an element of beauty in this systematicity. But there is also an element of precariousness. For a body of doctrines has some vital organs: claims or assumptions that are so central to the life of the system that, if one were to reject them, the system as a whole would likely collapse. This seems to be true, in particular, of Lewis’s metaphysical system. What I present here are two investigations concerning, respectively, the problem of ontic vagueness and the existence of a fundamental level. I believe that the evaluation of these two issues is of vital importance for assessing the tenability of Lewis’s systematic metaphysics. There is a general worry lurking behind my discussion, which it’s worth making explicit here. The worry is that, if the justification for Lewis’s claims on ontic vagueness and fundamentality turned out to be wanting or otherwise unsatisfactory, and if I am right to think that these theses are part of a number of central claims constituting the basis of his metaphysical system, then it seems we should start being suspicious of the very tenability of the Lewisian metaphysics as a whole. What I will be arguing for in the two main chapters of this dissertation provides, in my view, enough material for a modest defense of Lewis’s views on ontic vagueness and fundamentality. I will clarify the content of this modest defense, and explain its significance for the development of the contemporary debate in metaphysics, as well as for a redefinition of a kind of Lewisian metaphysics, in a brief note at the end of the introduction.