In this paper I offer a unified causal account of natural kinds. Using as a starting point the widely held view that natural kind terms or predicates are projectible, I argue that the ontological bases of their projectibility are the causal properties and relations associated with the natural kinds themselves. Natural kinds are not just concatenations of properties but ordered hierarchies of properties, whose instances are related to one another as causes and effects in recurrent causal processes. The resulting account (...) of natural kinds as clusters of core causal properties that give rise to clusters of derivative properties enables us to distinguish genuine natural kinds from non-natural kinds. For instance, it enables us to say why some of the purely conventional categories derived from the social domain do not correspond to natural kinds, though other social categories may. (shrink)

Philosophers have long been interested in a series of interrelated questions about natural kinds. What are they? What role do they play in science and metaphysics? How do they contribute to our epistemic projects? What categories count as natural kinds? And so on. Owing, perhaps, to different starting points and emphases, we now have at hand a variety of conceptions of natural kinds—some apparently better suited than others to accommodate a particular sort of inquiry. Even if coherent, this situation isn’t (...) ideal. My goal in this article is to begin to articulate a more general account of ‘natural kind phenomena’. While I do not claim that this account should satisfy everyone—it is built around a certain conception of the epistemic role of kinds and has an obvious pragmatic flavour—I believe that it has the resources to go further than extant alternatives, in particular the homeostatic property cluster view of kinds. (shrink)

The “demarcation problem,” the issue of how to separate science from pseu- doscience, has been around since fall 1919—at least according to Karl Pop- per’s (1957) recollection of when he first started thinking about it. In Popper’s mind, the demarcation problem was intimately linked with one of the most vexing issues in philosophy of science, David Hume’s problem of induction (Vickers 2010) and, in particular, Hume’s contention that induction cannot be logically justified by appealing to the fact that “it works,” (...) as that in itself is an inductive argument, thereby potentially plunging the philosopher straight into the abyss of a viciously circular argument. (shrink)

This paper defines in a formal and computational way the notion of ‘consilience’, a term introduced by Whewell in 1847 for the evaluation of scientific theories. Informally, as has been used to date, a model or theory is ‘consilient’ if it is predictive, explanatory and unifies the evide-nce. Centred in a constructive framework, where new terms can be intro-duced, we essay a formalisation of the idea of unification based on the avoidance of ‘sepa-ration’. However, it is soon manifest that this (...) classical approach is vulnerable to the introduction of fantastic concepts to unify disparate sub-theories. Our second approach is constructed by using a detailed evaluation of the relationship between the theory and the evid-ence by means of reinforcement propagation. With the use of reinfor-cement, fantastic concepts can be better detected and the role of con-silience for theory construction and revision can be specialised for dif-ferent inference mechanisms like explanatory induction, abduction, deduc-tion and analogy. (shrink)

The dominance of string theory in the research landscape of quantum gravity physics (despite any direct experimental evidence) can, I think, be justified in a variety of ways. Here I focus on an argument from mathematical fertility, broadly similar to Hilary Putnam’s ‘no miracles argument’ that, I argue, many string theorists in fact espouse in some form or other. String theory has generated many surprising, useful, and well-confirmed mathematical ‘predictions’—here I focus on mirror symmetry and the mirror theorem. These predictions (...) were made on the basis of general physical principles entering into string theory. The success of the mathematical predictions are then seen as evidence for the framework that generated them. I shall attempt to defend this argument, but there are nonetheless some serious objections to be faced. These objections can only be evaded at a considerably high (philosophical) price. (shrink)

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

This paper considers the role of mathematics in the process of acquiring new knowledge in physics and astronomy. The defining of the notions of continuum and discreteness in mathematics and the natural sciences is examined. The basic forms of representing the heuristic function of mathematics at theoretical and empirical levels of knowledge are studied: deducing consequences from the axiomatic system of theory, the method of generating mathematical hypotheses, “pure” proofs for the existence of objects and processes, mathematical modelling, the formation (...) of mathematics on the basis of internal mathematical principles and the mathematical theory of experiment. (shrink)

This paper describes the development of theories of scientific explanation since Hempel's earliest models in the 1940ies. It focuses on deductive and probabilistic whyexplanations and their main problems: lawlikeness, explanation-prediction asymmetries, causality, deductive and probabilistic relevance, maximal specifity and homogenity, the height of the probability value. For all of these topic the paper explains the most important approaches as well as their criticism, including the author's own accounts. Three main theses of this paper are: (1) Both deductive and probabilistic explanations (...) are important in science, not reducible to each other. (2) One must distinguish between (cause giving) explanations and (reason giving) justifications and predictions. (3) The adequacy of deductive as well as probabilistic explanations is relative to a pragmatically given background knowledge-which does not exclude, however, the possibility of purely semantic models. (shrink)

Methodological dualism in linguistics occurs when its theories are subjected to standards that are inappropriate for them qua scientific theories. Despite much opposition, methodological dualism abounds in contemporary thinking. In this paper, I treat linguistics as a scientific activity and explore some instances of dualism. By extracting some ubiquitous aspects of scientific methodology from its typically quantitative expression, I show that two recent instances of methodologically dualistic critiques of linguistics are ill-founded. I then show that there are nonetheless some divergences (...) between linguistic and other ordinary scientific methods, reflecting yet a third instance of methodological dualism. (shrink)

Scientists cannot devise theories, construct models, propose explanations, make predictions, or even carry out observations, without first classifying their subject matter. The goal of scientific taxonomy is to come up with classification schemes that conform to nature's own. Another way of putting this is that science aims to devise categories that correspond to 'natural kinds.' The interest in ascertaining the real kinds of things in nature is as old as philosophy itself, but it takes on a different guise when one (...) adopts a naturalist stance in philosophy, that is when one looks closely at scientific practice and takes it as a guide for identifying natural kinds and investigating their general features. This Element surveys existing philosophical accounts of natural kinds, defends a naturalist alternative, and applies it to case studies in a diverse set of sciences. This title is also available as Open Access on Cambridge Core. (shrink)

In the last half century we have gone from storing data on 5-1/4 inch floppy diskettes to cloud and now fog computing. But one should ask why so much data is being collected. Part of the answer is simple in light of scientific projects but why is there so much data on us? Then, we ask about its “interface” through fog computing. Such questions prompt this chapter on the philosophy of big data and fog computing. After some background on definitions, (...) origins and contemporary applications, the main discussion begins with thinking about modern data collection, management, and applications from a complexity standpoint. Big data is turned into knowledge but knowledge is extrapolated from the past and used to manage the future. Yet it is questionable whether humans have the capacity to manage contemporary technological and social complexity evidenced by our world in crisis and possibly on the brink of extinction. Such calls for a new way of studying societies from a scientific point of view. We are at the center of the observation from which big data emerge and are manipulated, the overall human project being not only to create an artificial brain with an attendant mind but a society that might be able to survive what “natural” humans cannot. (shrink)

I show how Sir William Rowan Hamilton’s philosophical commitments led him to a causal interpretation of classical mechanics. I argue that Hamilton’s metaphysics of causation was injected into his dynamics by way of a causal interpretation of force. I then detail how forces are indispensable to both Hamilton’s formulation of classical mechanics and what we now call Hamiltonian mechanics (i.e., the modern formulation). On this point, my efforts primarily consist of showing that the contemporary orthodox interpretation of potential energy is (...) the interpretation found in Hamilton’s work. Hamilton called the potential energy function the “force-function” because he believed that it represents forces at work in the world. Various non-historical arguments for this orthodox interpretation of potential energy are provided, and matters are concluded by showing that in classical Hamiltonian mechanics, facts about the potential energies of systems are grounded in facts about forces. Thus, if one can tolerate the view that forces are causes of motion, then Hamilton provides one with a road map for transporting causation into one of the most mathematically sophisticated formulations of classical mechanics, viz., Hamiltonian mechanics. (shrink)

Scientific revolution has been one of the most controversial topics in the history and philosophy of science. Yet it has been no consensus on what is the best unit of analysis in the historiography of scientific revolutions. Nor is there a consensus on what best explains the nature of scientific revolutions. This chapter provides a critical examination of the historiography of scientific revolutions. It begins with a brief introduction to the historical development of the concept of scientific revolution, followed by (...) an overview of the five main philosophical accounts of scientific revolutions. It then challenges two historiographical assumptions of the philosophical analyses of scientific revolutions. (shrink)

In the 1940s, the ‘modern synthesis’ (MS) of Darwinism and genetics cast genetic mutation and recombination as the source of variability from which environmental events naturally select the fittest, such ‘natural selection’ constituting the cause of evolution. Recent biology increasingly challenges this view by casting genes as followers and awarding the leading role in the genesis of adaptations to the agency and plasticity of developing phenotypes—making natural selection a consequence of other causal processes. Both views of natural selection claim to (...) capture the core of Darwin’s arguments in On the Origin of Species. Today, historians largely concur with the MS’s reading of Origin as a book aimed to prove natural selection the cause (vera causa) of adaptive change. This paper finds the evidence for that conclusion wanting. I undertake to examine the context and meaning of all Darwin’s known uses of the phrase vera causa, documenting in particular Darwin’s resistance to the pressure to prove natural selection a vera causa in letters written early in 1860. His resistance underlines the logical dependence of natural selection, an unobservable phenomenon, on the causal processes producing the observable events captured by the laws of inheritance, variation, and the struggle for existence, established in Chapters 1–3 of Origin. (shrink)

There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical hopes (...) for a certain order in nature cannot be fulfilled. Natural kinds crosscut one another, ubiquitously so, and this crosscutting spells the end of the hierarchical dream. (shrink)

In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

Many philosophers take mind-independence to be criterial for realism about kinds. This is problematic when it comes to psychological and social kinds, which are unavoidably mind-dependent. But reflection on the case of artificial or synthetic kinds shows that the criterion of mind-independence needs to be qualified in certain ways. However, I argue that none of the usual variants on the criterion of mind-dependence is capable of distinguishing real or natural kinds from non-real kinds. Although there is a way of modifying (...) the criterion of mind-independence in such a way as to rule in artificial kinds but rule out psychological and social kinds, this does not make the latter non-real. I conclude by proposing a different way of distinguishing real from non-real kinds, which does not involve mind-independence and does not necessarily exclude psychological and social kinds. (shrink)

Perhaps there has been no greater opportunity than in this “VOLUME FIFTEEN of our Death And Anti-Death set of anthologies” to write about how might think about life and how to avoid death. There are two reasons to discuss “life”, the first being enhancing our understanding of who we are and why we may be here in the Universe. The second is more practical: how humans meet the physical challenges brought about by the way they have interacted with their environment. (...) Many persons discussing “life” beg the question about what “life” is. Surely, when one discusses how to overcome its opposite, death, they are not referring to another “living” thing such as a plant. There seems to be a commonality, though, and it is this commonality is one needing elaboration. It ostensibly seems to be the boundary condition separating what is completely passive (inert) from what attempts to maintain its integrity, as well as fulfilling other conditions we think “life” has. In our present discussion, there will be a reminder that it by no means has been unequivocally established what life really is by placing quotes around the word, namely, “life”. Consider it a tag representing a bundle of philosophical ideas that will be unpacked in this paper. (shrink)

The ArgumentFocusing on the celebrations of Newton and his work, this article investigates the use of the concept of genius and its connection with debates on the methodology of science and the morality of great discoverers. During the period studied, two areas of tension developed. Firstly, eighteenth-century ideas about the relationship between genius and method were challenged by the notion of scientific genius as transcending specifiable rules of method. Secondly, assumptions about the nexus between intellectual and moral virtue were threatened (...) by the emerging conception of genius as marked by an extraordinary personality – on the one hand capable of breaking with established methods to achieve great discoveries, on the other, likely to transgress moral and social conventions. The assesments of Newton by nineteenth-century scientists such as Brewster, Whewell, and De Morgan were informed by these tensions. (shrink)

The aim of this article is to elucidate the notions of explanation and mechanism, in particular of the social kind. A mechanism is defined as what makes a concrete system tick, and it is argued that to propose an explanation proper is to exhibit a lawful mechanism. The so-called covering law model is shown to exhibit only the logical aspect of explanation: it just subsumes particulars under universals. A full or mechanismic explanation involves mechanismic law statements, not purely descriptive ones (...) such as functional relations and rate equations. Many examples from the natural, biosocial, and social sciences are examined. In particular, macro-micro-micro-macro social relations are shown to explain other wise puzzling macro-macro links. The last part of the article relates the author's progress, over half a century, toward understanding mechanism and explanation. (shrink)

The probabilistic corroboration of two or more hypotheses or series of observations may be performed additively or multiplicatively . For additive corroboration (e.g. by Laplace's rule of succession), stochastic independence is needed. Inferences, based on overwhelming numbers of observations without unexplained counterinstances permit hyperinduction , whereby extremely high probabilities, bordering on certainty for all practical purposes may be achieved. For multiplicative corroboration, the error probabilities (1 - Pr) of two (or more) hypotheses are multiplied. The probabilities, obtained by reconverting the (...) product, are valid for both of the hypotheses and indicate the gain by corroboration.. This method is mathematically correct, no probabilities > 1 can result (as in some conventional methods) and high probabilities with fewer observations may be obtained, however, semantical independence is a prerequisite. The combined method consists of (1) the additive computation of the error probabilities (1 - Pr) of two or more single hypotheses, whereby arbitrariness is avoided or at least reduced and (2) the multiplicative procedure . The high reliability of Empirical Counterfactual Statements is explained by the possibility of multiplicative corroboration of "all-no" statements due to their strict semantical independence. (shrink)

In the first half of this dissertation, I develop a heuristic methodology for analyzing scientific solutions to the problem of underdetermination. Heuristics are rough-and-ready procedures used by scientists to construct models, design experiments, interpret evidence, etc. But as powerful as they are, heuristics are also error-prone. Therefore, I argue that they key to prudently using a heuristic is the articulation of meta-heuristics---guidelines to the kinds of problems for which a heuristic is well- or ill-suited. Given that heuristics will introduce certain (...) errors into our scientific investigations, I emphasize the importance of a particular category of meta-heuristics involving the search for robust evidence. Robustness is understood to be the epistemic virtue bestowed by agreement amongst multiple modes of determination. The more modes we have at our disposal, and the more these confirm the same result, the more confident can we be that a result is not a mere artifact of some heuristic simplification. Through an analysis of case-studies in the philosophy of biology and clinical trials, I develop a principled method for modeling and evaluating heuristics and robustness claims in a qualitative problem space. The second half of the dissertation deploys the heuristic methodology to address ethical and epistemological issues in the science of clinical trials. To that end, I develop a network model for the problem space of clinical research, capable of representing the various kinds of experiments, epistemic relationships, and ethical justifications intrinsic to the domain. I then apply this model to ongoing research with the antibacterial agent, moxifloxacin, for the treatment of tuberculosis, tracking its development from initially successful and promising in vitro and animal studies to its disappointing and discordant performance across five human efficacy trials. Given this failure to find a robust result with moxifloxacin across animal and human studies, what should researchers now do? While my final analysis of this case does not definitively answer that question, I demonstrate how my methodology, unlike a statistical meta-analysis, helps to clarify the directions for further research. (shrink)

This paper aims to reassess the philosophical puzzle of the “applicability of mathematics to physical sciences” as a misunderstood disciplinary interplay. If the border isolating mathematics from the empirical world is based on appropriate criteria, how does one explain the fruitfulness of its systematic crossings in recent centuries? An analysis of the evolution of the criteria used to separate mathematics from experimental sciences will shed some light on this question. In this respect, we will highlight the historical influence of three (...) major disciplinary paradigms. According to the Aristotelian classification of the sciences, the separation of mathematics from physics is based on their respective objects of study. The Baconian system distinguishes these sciences by the type of knowledge involved in each field. Finally, the Whewellian disciplinary layout categorises these disciplines by their respective methods. In this paper, we argue that the cascading effect of such disciplinary categorisations—based successively on ontological, epistemological, and heuristic criteria—resulted in a profound redefinition of the border between mathematics and physics, with the consequence of obscuring the foundations of the interplay between these fields. Our approach intends to put forward such a mechanism as a constitutive piece of the puzzle of the applicability of mathematics. (shrink)

In The Inference That Makes Science, Ernan McMullin recounts the clear historical progress he saw toward a vision of the sciences as conclusions reached rationally on the basis of empirical evidence. Distinctive of this vision was his view of science as driven by a specific form of inference, retroduction. To understand this properly, we need to disentangle the description of retroductive inference from the claims made on its behalf. To end I will suggest that the real rival to McMullin's vision (...) of science is not the methodologies he criticizes so successfully but a more radical empiricist alternative in epistemology. (shrink)

The paper offers a new understanding of induction in the empirical sciences, one which assimilates it to induction in geometry rather than to statistical inference. To make the point a system of notions, essential to logically sound induction, is defined. Notable among them are arbitrary object and particular property. A second aim of the paper is to bring to light a largely neglected set of assumptions shared by both induction and deduction in the empirical sciences. This is made possible by (...) appealing to the logic of common nouns and applying it to the logic of natural-kind terms.This strategy yields a new insight into the concept of natural kinds. While the strategy reveals deep affinity between empirical induction and deduction it also reveals two problems peculiar to induction. This helps to explain the intuition that induction is the more problematic of the two. The paper does not set out ‘to solve the problem of induction’. 1The paper has benefited from the support and critical comments of several friends: Steven Davis, Kevin Dunbar, Anil Gupta, Michael Hallett, Ray Jackendoff and Storrs McCall. Two friends, however, deserve special thanks, Michael Makkai and Gonzalo Reyes. Many of the points made in the paper, otherwise unacknowledged, are due to their generosity and patience. In fact, the paper can be seen as an application of the logic of kinds on which Gonzalo Reyes has been working for several years. (shrink)