Kuhn, the correspondence theory of truth and coherentist epistemology

Kuhn argued against both the correspondence theory of truth and convergent realism. Although he likely misunderstood the nature of the correspondence theory, which it seems he wrongly believed to be an epistemic theory, Kuhn had an important epistemic point to make. He maintained that any assessment of correspondence between beliefs and reality is not possible, and therefore, the acceptance of beliefs and the presumption of their truthfulness has to be decided on the basis of other criteria. I will show that via Kuhn’s suggested epistemic values, specifically via problem-solving, his philosophy can be incorporated into a coherentist epistemology. Further, coherentism is, in principle, compatible with convergent realism. However, an argument for increasing likeness to truth requires appropriate historical continuity. Kuhn maintained that the history of science is full of discontinuity, and therefore, the historical condition of convergent realism is not satisfied.     

Successful visual epistemic representation

In this paper, I characterize visual epistemic representations as concrete two- or three-dimensional tools for conveying information about aspects of their target systems or phenomena of interest. I outline two features of successful visual epistemic representation: that the vehicle of representation contain sufficiently accurate information about the phenomenon of interest for the user's purpose, and that it convey this information to the user in a manner that makes it readily available to her. I argue that actual epistemic representation may involve tradeoffs between these features and is successful to the extent that they are present.     

Colligation in modelling practices: From Whewell’s tides to the San Francisco Bay Model

“Colligation”, a term first introduced in philosophy of science by William Whewell (1840), today sparks a renewed interest beyond Whewell scholarship. In this paper, we argue that adopting the notion of colligation in current debates in philosophy of science can contribute to our understanding of scientific models. Specifically, studying colligation allows us to have a better grasp of how integrating diverse model components (empirical data, theory, useful idealization, visual and other representational resources) in a creative way may produce novel generalizations about the phenomenon investigated. Our argument is built both on the theoretical appraisal of Whewell’s philosophy of science and the historical rehabilitation of his scientific work on tides. Adopting a philosophy of science in practice perspective, we show how colligation emerged from Whewell’s empirical work on tides. The production of idealized maps (“cotidal maps”) illustrates the unifying and creative power of the activity of colligating in scientific practice. We show the importance of colligation in modelling practices more generally by looking at its epistemic role in the construction of the San Francisco Bay Model.     

Scientific progress as increasing verisimilitude

According to the foundationalist picture, shared by many rationalists and positivist empiricists, science makes cognitive progress by accumulating justified truths. Fallibilists, who point out that complete certainty cannot be achieved in empirical science, can still argue that even successions of false theories may progress toward the truth. This proposal was supported by Karl Popper with his notion of truthlikeness or verisimilitude. Popper’s own technical definition failed, but the idea that scientific progress means increasing truthlikeness can be expressed by defining degrees of truthlikeness in terms of similarities between states of affairs. This paper defends the verisimilitude approach against Alexander Bird who argues that the “semantic” definition (in terms of truth or truthlikeness alone) is not sufficient to define progress, but the “epistemic” definition referring to justification and knowledge is more adequate. Here Bird ignores the crucial distinction between real progress and estimated progress, explicated by the difference between absolute (and usually unknown) degrees of truthlikeness and their evidence-relative expected values. Further, it is argued that Bird’s idea of returning to the cumulative model of growth requires an implausible trick of transforming past false theories into true ones.     

Scrutinizing thing knowledge

In his book Thing Knowledge Davis Baird argues that our accustomed understanding of knowledge as justified true beliefs is not enough to understand progress in science and technology. To be more accurate he argues that scientific instruments are to be seen as a form of “objective knowledge” in the sense of Karl Popper.I want to examine if this idea is plausible. In a first step I want to show that this proposal implies that nearly all man-made artifacts are materialized objective knowledge. I argue that this radical change in our concept of knowledge demands strong reasons and that Baird does not give them. I take a look at the strongest strand of arguments of Baird's book—the arguments from cognitive autonomy—and conclude that they do not suffice to make Baird's view of scientific instruments tenable.     

The abundant world: Paul Feyerabend's metaphysics of science

The goal of this paper is to provide an interpretation of Feyerabend's metaphysics of science as found in late works like Conquest of Abundance and Tyranny of Science. Feyerabend's late metaphysics consists of an attempt to criticize and provide a systematic alternative to traditional scientific realism, a package of views he sometimes referred to as “scientific materialism.” Scientific materialism is objectionable not only on metaphysical grounds, nor because it provides a poor ground for understanding science, but because it implies problematic claims about the epistemic and cultural authority of science, claims incompatible with situating science properly in democratic societies. I show how Feyerabend's metaphysical view, which I call “the abundant world” or “abundant realism,” constitute a sophisticated and challenging form of ontological pluralism that makes interesting connections with contemporary philosophy of science and issues of the political and policy role of science in a democratic society.     

The love of truth

It is frequently said that belief aims at truth, in an explicitly normative sense—that is, that one ought to believe the proposition that p if, and only if, p is true. This truth norm is frequently invoked to explain why we should seek evidential justification in our beliefs, or why we should try to be rational in our belief formation—it is because we ought to believe the truth that we ought to follow the evidence in belief revision. In this paper, I argue that this view is untenable. The truth norm clashes with plausible evidential norms in a wide range of cases, such as when we have excellent but misleading evidence for a falsehood or no evidence for a truth. I will consider various ways to resolve this conflict and argue that none of them work. However, I will ultimately attempt to vindicate the love of truth, by arguing that knowledge is the proper epistemic goal. The upshot is that we should not aim merely to believe the truth; we should aim to know it.     

Deflationary representation,inference, and practice

This paper defends the deflationary character of two recent views regarding scientific representation, namely RIG Hughes' DDI model and the inferential conception. It is first argued that these views' deflationism is akin to the homonymous position in discussions regarding the nature of truth. There, we are invited to consider the platitudes that the predicate “true” obeys at the level of practice, disregarding any deeper, or more substantive, account of its nature. More generally, for any concept X, a deflationary approach is then defined in opposition to a substantive approach, where a substantive approach to X is an analysis of X in terms of some property P, or relation R, accounting for and explaining the standard use of X. It then becomes possible to characterize a deflationary view of scientific representation in three distinct senses, namely: a “no-theory” view, a “minimalist” view, and a “use-based” view—in line with three standard deflationary responses in the philosophical literature on truth. It is then argued that both the DDI model and the inferential conception may be suitably understood in any of these three different senses. The application of these deflationary ‘hermeneutics’ moreover yields significant improvements on the DDI model, which bring it closer to the inferential conception. It is finally argued that what these approaches have in common—the key to any deflationary account of scientific representation—is the denial that scientific representation may be ultimately reduced to any substantive explanatory property of sources, or targets, or their relations.     

Inevitability,contingency, and epistemic humility

This paper offers an epistemological framework for the debate about whether the results of scientific enquiry are inevitable or contingent. I argue in Sections 2 and 3 that inevitabilist stances are doubly guilty of epistemic hubris—a lack of epistemic humility—and that the real question concerns the scope and strength of our contingentism. The latter stages of the paper—Sections 4 and 5—address some epistemological and historiographical worries and sketch some examples of deep contingencies to guide further debate. I conclude by affirming that the concept of epistemic humility can usefully inform critical reflection on the contingency of the sciences and the practice of history of science.     

The rationale behind Pierre Duhem's natural classification

The central concern of this paper is the interpretation of Duhem's attitude towards physical theory. Based on his view that the classification of experimental laws yielded by theory progressively approaches a natural classification—a classification reflecting that of underlying realities—Duhem has been construed as a realist of sorts in recent literature. Here I argue that his positive attitude towards the theoretic classification of laws had rather to do with the pragmatic rationality of the physicist. Duhem's idea of natural classification was an intuitive idea in the mind of the physicist that had to be affirmed in order to justify the physicist's pursuit of theory.     

Rehabilitating the regulative use of reason: Kant on empirical and chemical laws

In his Kritik der reinen Vernunft, Kant asserts that laws of nature “carry with them an expression of necessity” (A159/B198). There is, however, widespread interpretive disagreement regarding the nature and source of the necessity of empirical laws of natural sciences in Kant's system. It is especially unclear how chemistry—a science without a clear, straightforward connection to the a priori principles of the understanding—could contain such genuine, empirical laws. Existing accounts of the necessity of causal laws unfortunately fail to illuminate the possibility of non-physical laws. In this paper, I develop an alternative, ‘ideational’ account of natural laws, according to which ideas of reason necessitate the laws of some non-physical sciences. Chemical laws, for instance, are grounded on ideas of the elements, and the chemist aims to reduce her phenomena to these elements via experimentation. Although such ideas are beyond the possibility of experience, their postulation is necessary for the achievement of reason's theoretical ends: the unification and explanation of the cognitions of science.     

Chance,determinism and the classical theory of probability

This paper situates the metaphysical antinomy between chance and determinism in the historical context of some of the earliest developments in the mathematical theory of probability. Since Hacking's seminal work on the subject, it has been a widely held view that the classical theorists of probability were guilty of an unwitting equivocation between a subjective, or epistemic, interpretation of probability, on the one hand, and an objective, or statistical, interpretation, on the other. While there is some truth to this account, I argue that the tension at the heart of the classical theory of probability is not best understood in terms of the duality between subjective and objective interpretations of probability. Rather, the apparent paradox of chance and determinism, when viewed through the lens of the classical theory of probability, manifests itself in a much deeper ambivalence on the part of the classical probabilists as to the rational commensurability of causal and probabilistic reasoning.     

On Understanding: Maxwell on the Methods of Illustration and Scientific Metaphor

In this paper I examine the notion and role of metaphors and illustrations in Maxwell's works in exact science as a pathway into a broader and richer philosophical conception of a scientist and scientific practice. While some of these notions and methods are still at work in current scientific research—from economics and biology to quantum computation and quantum field theory—, here I have chosen to attest to their entrenchment and complexity in actual science by attempting to make some conceptual sense of Maxwell's own usage; this endeavour includes situating Maxwell's conceptions and applications in his own culture of Victorian science and philosophy. I trace Maxwell's notions to the formulation of the problem of understanding, or interpreting, abstract representations such as potential functions and Lagrangian equations. I articulate the solution in terms of abstract-concrete relations, where the concrete, in tune with Victorian British psychology and engineering, includes the muscular as well as the pictorial. This sets the basis for a conception of understanding in terms of unification and concrete modelling, or representation. I examine the relation of illustration to analogies and metaphors on which this account rests. Lastly, I stress and explain the importance of context-dependence, its consequences for realism-instrumentalism debates, and Maxwell's own emphasis on method.     

Inference to the hypothesis of extended cognition

This paper examines the justification for the hypothesis of extended cognition (HEC). HEC claims that human cognitive processes can, and often do, extend outside our head to include objects in the environment. HEC has been justified by inference to the best explanation (IBE). Both advocates and critics of HEC claim that we can infer the truth value of HEC based on whether HEC makes a positive or negative explanatory contribution to cognitive science. I argue that IBE cannot play this epistemic role. A serious rival to HEC exists with a differing truth value, and this invalidates IBEs for both the truth and the falsity of HEC. Explanatory value to cognitive science is not a guide to the truth value of HEC.     

English engineer John Smeaton's experimental method(s): Optimisation,hypothesis testing and exploratory experimentation

In this paper I provide a detailed account of eighteenth-century engineer John Smeaton's experimental methods, with the aim of bringing our understanding of his work into line with recent research in the history and philosophy of science. Starting from his use of the technique of parameter variation, I identify three distinct methodological aims in the research he carried out on waterwheels, windmills and hydraulic mortars. These aims are: optimisation, hypothesis testing and maxim generation. The main claim of this paper is that Smeaton did more than merely improve engineering methods by systematising earlier artisanal approaches, which is the classic view of Smeaton's method developed by historians of technology in the 1990s. I argue instead that his approach bridged the divide between science and technology, by integrating both hypothesis testing and exploratory experimentation. This is borne out, in particular, by the way that Smeaton emphasised the exploratory side of the work he published in the Philosophical Transactions, in contrast to his account of the construction of the Eddystone lighthouse, which was aimed at a broader, non-specialist public. I contribute to recent research on exploratory experimentation by showing – in line with other work on this topic – that exploratory experimentation is not incompatible with hypothesis testing. This new perspective on Smeaton's method will hopefully lead to further research and new insights into the relation between science and technology at the start of the Industrial Revolution.     

Modelling and representing: An artefactual approach to model-based representation

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation.     

Simplicius on Tekmeriodic Proofs

In this study I examine the sole detailed evidence we have for Simplicius’ view of sign-based, i.e. tekmeriodic proofs, thereby questing the widespread assumption that he espouses Philoponus’ account of these proofs. Specifically, I argue that (1) it is more plausible to understand the signs on which Simplicius bases his tekmeriodic proofs as refutable, (2) he grounds the epistemic worth of these proofs in the evidential strength of their premises rather than in their validity, (3) unlike Philoponus, he conceives of the argument that leads to the principles of natural philosophy, which tekmeriodic proofs are aimed to prove, as inductive, and (4) he evaluates these proofs against Plato’s un-hypothetical science, hence denying natural philosophy the autonomy from metaphysics that Philoponus’ account of tekmeriodic proofs grants.     

Evaluating community science

Community science—scientific investigation conducted partly or entirely by non-professional scientists—has many advantages. For example, community science mobilizes large numbers of volunteers who can, at low cost, collect more data than traditional teams of professional scientists. Participation in research can also increase volunteers’ knowledge about and appreciation of science. At the same time, there are worries about the quality of data that community science projects produce. Can the work of non-professionals really deliver trustworthy results? Attempts to answer this question generally compare data collected by volunteers to data collected by professional scientists. When volunteer data is more variable or less accurate than professionally collected data, then the community science project is judged to be inferior to traditional science. I argue that this is not the right standard to use when evaluating community science, because it relies on a false assumption about the aims of science. I show that if we adopt the view that science has diverse aims which are often in tension with one another, then we cannot justify holding community science data to an expert accuracy standard. Instead, we should evaluate the quality of community science data based on its adequacy-for-purpose.     

Scientific progress: Knowledge versus understanding

What is scientific progress? On Alexander Bird's epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird's epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart.     

A tale of three theories: Feyerabend and Popper on progress and the aim of science

In this paper, three theories of progress and the aim of science are discussed: (i) the theory of progress as increasing explanatory power, advocated by Popper in The logic of scientific discovery (1935/1959); (ii) the theory of progress as approximation to the truth, introduced by Popper in Conjectures and refutations (1963); (iii) the theory of progress as a steady increase of competing alternatives, which Feyerabend put forward in the essay “Reply to criticism. Comments on Smart, Sellars and Putnam” (1965) and defended as late as the last edition of Against method (1993). It is argued that, contrary to what Feyerabend scholars have predominantly assumed, Feyerabend's changing attitude towards falsificationism—which he often advocated at the beginning of his career, and vociferously attacked in the 1970s and 1980s—must be explained by taking into account not only Feyerabend's very peculiar view of the aim of science, but also Popper's changing account of progress.