Metaphors are found all throughout science: in published papers, working hypotheses, policy documents, lecture slides, grant proposals, and press releases. They serve different functions, but perhaps most striking is the way they enable understanding, of a theory, phenomenon, or idea. In this paper, we leverage recent advances on the nature of metaphor and the nature of understanding to explore how they accomplish this feat. We attempt to shift the focus away from the epistemic value of the content of metaphors, to (...) the epistemic value of the metaphor’s consequences. Many famous scientific metaphors are epistemically good, not primarily because of what they say about the world, but because of how they cause us to think. Specifically, metaphors increase understanding either by improving our sets of representations, or by making it easier for us to encode and process data about complex subjects by changing how we are disposed to conceptualize those subjects. This view hints towards new positions concerning testimonial understanding, factivity, abilities, discovery via metaphor, and the relation between metaphors and models. (shrink)

The standard view in current philosophy of creativity says that being creative has two requirements: being novel and being valuable. The standard view on creativity has recently become an object of critical scrutiny. Hills and Bird have specifically proposed to remove the value requirement from the definition, as it is not clear that creative objects are necessarily valuable or creative people necessarily praiseworthy. In this paper, I argue against Hills and Bird, since eliminating the element of value from the explanation (...) of creativity hinders the understanding of the role that creative products play in actual epistemic practices, which are fundamentally normative. More specifically, I argue that the terms ‘creativity’ and ‘creative’ function as thick epistemic concepts when employed by competent epistemic agents in practice, that is, these concepts have both a descriptive and an evaluative content that cannot be disentangled from one another. Accordingly, I suggest that philosophers should prefer thick accounts over thin accounts of creativity. A thick account of creativity is one that endorses the standard view at its basis, but further develops it in two ways: by stressing the entanglement of the value and novelty requirements; by permitting to encompass a range of domain-specific characterizations of such entanglement for different epistemic situations. In order to take the first steps in the development of such a thick account of creativity, I look at the domain of scientific practices as a case in point, and try to spell out what the thickness of creative instances typically entails here. Namely, I identify the worthy novelty of creative models and methods with their potential to clarify a tradition, with fruitfulness, and with the fulfilment of exploratory aims. (shrink)

Recent philosophical literature has turned its attention towards assessments of how to judge scientific proposals as worthy of further inquiry. Previous work, as well as papers contained within this special issue, propose criteria for pursuitworthiness (Achinstein, 1993; Whitt, 1992; DiMarco & Khalifa, 2019; Laudan, 1977; Shan, 2020; Šešelja et al., 2012). The purpose of this paper is to assess the grounds on which pursuitworthiness demands can be legitimately made. To do this, I propose a challenge to the possibility of even (...) minimal criteria of pursuitworthiness, inspired by Paul Feyerabend. I go on to provide a framework for identifying the contexts in which pursuitworthiness criteria may promote the efficiency of scientific inquiry. I then spell out some implications this framework has for values and pursuit. (shrink)

In this paper, I shall defend two main claims. First, Friedman’s famous paper “On the methodology of positive economics” (“F53”) cannot be properly understood without taking into account the influence of three authors who are neither cited nor mentioned in the paper: Max Weber, Frank Knight, and Karl Popper. I shall trace both their substantive influence on F53 and the historical route by which this influence took place. Once one has understood these ingredients, especially Weber’s ideal types, many of F53’s (...) astonishing sentences like “the more significant the theory, the more unrealistic the assumptions”, make good sense. Second, I shall claim that the much-discussed question whether Friedman’s essay espouses an instrumentalist or a realist position, is the wrong question to be asked. I shall illustrate that by a comparison with examples from physics in which also unrealistic assumptions are made. Also there, the question whether these assumptions are indicators of instrumentalism or realism is not appropriate. Cleared from these misunderstandings, F53 presents itself as an interesting and reasonable but much less controversial contribution to the methodology of economics. (shrink)

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. (shrink)

Around fifteen years before the chemical substance alumina could be decomposed in the laboratory, it was identified as a compound and predicted to contain a new element called ‘aluminium’. Using this episode from early nineteenth-century chemistry as a case study for the use of analogical reasoning in science, this paper examines how chemists relied on chemical classifications for the prediction of aluminium. I argue that chemists supplemented direct evidence of chemical decomposition with analogical inferences in order to evaluate the composition (...) of substances. Since they were established on the basis of relevant similarities in chemical properties, classifications were taken to reflect so-called ‘chemical analogies’ between substances. In combination with the knowledge that analogous properties indicated similarities in composition, this enabled chemists to infer the composition of experimentally indecomposable substances by analogy. The trust in such analogical inferences, even if they could not be confirmed through experiment, was justified by pragmatic considerations. Whereas the possibility of decomposing a substance depended on the available laboratory techniques, chemical analogies were thought to last independently of internal composition. It was therefore more practical to keep well-established classes of substances together rather than separate them on the basis of experimental results that might evolve as new techniques were developed. Besides highlighting the links between analogical reasoning and classification, this paper also illustrates the importance of analogy in the evaluation of elementary nature in the early nineteenth century. (shrink)

This paper aims to develop an account of the pursuitworthiness of models based on a view of models as epistemic tools. This paper is motivated by the historical question of why, in the 1960s, when many scientists hardly found QSAR models attractive, some pharmaceutical scientists pursued Quantitative Structure–Activity Relationship (QSAR) models despite the lack of potential for theoretical development or empirical success. This paper addresses this question by focusing on how models perform their heuristic functions as epistemic tools rather than (...) as potential theories. I argue that models perform their heuristic function by “constructing” phenomena from data in the sense that they allow the model users who interact with the medium of the models to recognise the phenomena as such. The constructed phenomena assist model users in identifying which conditional hypotheses that are focused on low-level regularities concerning entities such as chemical compounds are more “testworthy,” a concept that links the costs associated with hypothesis testing with the fertility of the hypothesis. (shrink)

What is the role of the imagination in scientific practice? Here I focus on the nature and role of invitations to imagine in certain scientific texts as represented by the example of Einstein’s Special Relativity paper from 1905. Drawing on related discussions in aesthetics, I argue, on the one hand, that this role cannot be simply subsumed under ‘supposition’ but that, on the other, concerns about the impact of genre and symbolism can be dealt with, and hence present no obstacle (...) to regarding imagination as appropriately belief-like. By applying the framework of ‘semi- propositional representations’ and ‘quasi-truth’ to this case I thereby offer a new unitary framework for understanding the epistemology of scientific imagination. (shrink)

Sometimes inquirers may rationally pursue a theory even when the available evidence does not favor that theory over others. Features of a theory that favor pursuing it are known as considerations of promise or pursuitworthiness. Examples of such reasons include that a theory is testable, that it has a useful associated analogy, and that it suggests new research and experiments. These reasons need not be evidence in favor of the theory. This raises the question: what kinds of reasons are provided (...) by pursuitworthiness considerations? Are they epistemic reasons or practical reasons? I argue that pursuitworthiness considerations are a kind of non-evidential epistemic reason, which I call an inquisitive reason. In support of this, I first point out two important similarities between the traditional pursuitworthiness considerations discussed in philosophy of science, which I call promise reasons, and certain social epistemic reasons that I call social inquisitive reasons. Specifically, both kinds of reason (1) favor pursuing a theory in a non-evidential way, and (2) concern promoting successful inquiry. I then propose recognition of a new category of normative reason: inquisitive reasons. This category contains both promise and social inquisitive reasons. Finally, I argue that inquisitive reasons share three essential features with previously recognized epistemic reasons: a connection to epistemic aims, explanatory independence, and the presence of a specific right-kind/wrong-kind reasons distinction. Each of these features have been used to argue that evidence should be treated as part of a distinct, independent domain of epistemic normativity. Since inquisitive reasons share these features, they too should be considered part of this independent epistemic domain. Thus, inquisitive reasons, including pursuitworthiness considerations, are epistemic reasons. (shrink)

Despite wide recognition that speculation is critical for successful science, philosophers have attended little to it. When they have, speculation has been characterized in narrowly epistemic terms: a hypothesis is speculative due to its (lack of) evidential support. These ‘evidence-first’ accounts provide little guidance for what makes speculation productive or egregious, nor how to foster the former while avoiding the latter. I examine how scientists discuss speculation and identify various functions speculations play. On this basis, I develop a ‘function-first’ account (...) of speculation. This analysis grounds a richer discussion of when speculation is egregious and when it is productive, based in both fine-grained analysis of the speculation’s purpose, and what I call the ‘epistemic situation’ scientists face. (shrink)

Paleobiologists often provide simple narratives to explain complex, contingent episodes. These narratives are sometimes ‘one-shot hypotheses’ which are treated as being mutually exclusive with other possible explanations of the target episode, and are thus extended to accommodate as much about the episode as possible. I argue that a provisional preference for such hypotheses provides two kinds of productive scaffolding. First, they generate ‘hypothetical difference-makers’: one-shot hypotheses highlight and isolate empirically tractable dependencies between variables. Second, investigations of hypothetical difference-makers provision explanatory (...) resources, the ‘raw materials’ for constructing more complex—and likely more adequate—explanations. Provisional preferences for simple, one-shot hypotheses in historical science, then, is defeasibly justified on indirect—strategic—grounds. My argument is made in reference to recent developments regarding the K–Pg extinction. (shrink)

It is often thought that the vindication of experimental work lies in its capacity to be revelatory of natural systems. I challenge this idea by examining laboratory experiments in ecology. A central task of community ecology involves combining mathematical models and observational data to identify trophic interactions in natural systems. But many ecologists are also lab scientists: constructing microcosm or ‘bottle’ experiments, physically realizing the idealized circumstances described in mathematical models. What vindicates such ecological experiments? I argue that ‘extrapolationism’, the (...) view that ecological lab work is valuable because it generates truths about natural systems, does not exhaust the epistemic value of such practices. Instead, bottle experiments also generate ‘understanding’ of both ecological dynamics and empirical tools. Some lab work, then, aids theoretical understanding, as well as targeting hypotheses about nature. 1Introduction2Trophic Interactions and Observational Techniques3Cryptic Dynamics in Bottle Experiments4Extrapolationism 4.1Ecological possibility and actuality4.2Ecological heterogeneity5Understanding 5.1The epistemic good of understanding5.2Bottle experiments as understanding-generators5.3How understanding travels6Conclusion. (shrink)

This paper proposes an account of natural analogy in scientific theorizing via Mary Hesse’s original understanding of analogical reasoning. Starting with discussing Hesse’s examples and her symbolic scheme, I argue that the traditional distinction between the type of formal analogy and the type of material analogy should be abandoned. All analogies in theorizing, that are both formal and material, contain a set of pretheoretic associations and a theoretic structure between two analogues. I thus provide a new interpretation of Hesse’s symbolic (...) scheme to reveal the pretheoretical and the structural dimensions of analogy and further illustrate the account of natural analogy by applying it to the history of the construction of Coulomb’s law, which is traditionally seen as a typical case of formal analogy, arguing that pretheoretic associations as well as a theoretic structure play a necessary role in this case. In the final part of this paper, I argue that the account of natural analogy is preferable to Dedre Gentner’s structural mapping theory. (shrink)

This paper proposes an account of natural analogy in scientific theorizing via Mary Hesse’s original understanding of analogical reasoning. Starting with discussing Hesse’s examples and her symbolic scheme, I argue that the traditional distinction between the type of formal analogy and the type of material analogy should be abandoned. All analogies in theorizing, that are both formal and material, contain a set of pretheoretic associations and a theoretic structure between two analogues. I thus provide a new interpretation of Hesse’s symbolic (...) scheme to reveal the pretheoretical and the structural dimensions of analogy and further illustrate the account of natural analogy by applying it to the history of the construction of Coulomb’s law, which is traditionally seen as a typical case of formal analogy, arguing that pretheoretic associations as well as a theoretic structure play a necessary role in this case. In the final part of this paper, I argue that the account of natural analogy is preferable to Dedre Gentner’s structural mapping theory. (shrink)

Recent case studies have revealed that purely formal analogies have been successfully used as a heuristic in physics. This is at odds with most general philosophical accounts of analogies, which require analogies to be physical in order to be justifiably used. The main goal of this paper is to supply a philosophical account that justifies the use of purely formal analogies in physics. Using Bartha’s (2010) articulation model as a starting point, I offer precise definitions of formal and physical analogies (...) and propose a new submodel of analogical reasoning that accounts for the successful use of purely formal analogies in the development of renormalization group methods for use in particle physics in the early 1970’s (Fraser 2020). Two distinctive features of this new applied mathematics submodel for analogical reasoning are that the conclusion of the argument from analogy includes both an entire model (and not only a hypothesis or a prediction) and the construction procedure for this model. A third important difference from arguments from physical analogy is that only the prima facie plausibility of the conclusion is established, and not stronger types of plausibility associated with confirmation. The use of purely formal analogies is justified because they are suited to supporting conclusions of this sort. Formulating a general philosophical account of analogies that covers purely formal analogies also serves two additional purposes: (1) to highlight the features of this case that are novel in the context of examples of analogies traditionally considered by philosophers and (2) to establish that physicists should not automatically dismiss purely formal analogies when evaluating heuristics for the development of new models. (shrink)