This article aims to answer what I call the “constitution question of engineering modeling”: in virtue of what does an engineering model model its target system? To do so, I will offer a category-theoretic, structuralist account of design, using the olog framework. Drawing on this account, I will conclude that engineering and scientific models are not only cognitively but also representationally indistinguishable. I will finally propose an axiological criterion for distinguishing scientific from engineering modeling.

Regarding the dichotomy between applied science and pure science, there are two apparently paradoxical facts. First, they are distinguishable. Second, the outcomes of pure sciences (e.g. scientific theories and models) are applicable to producing the outcomes of applied sciences (e.g. technological artefacts) and vice versa. Addressing the functional roles of applied and pure science, i.e. to produce design representation and science representation, respectively, I propose a new characterisation of the dichotomy that explains these two facts.

Given the diversity of explanatory practices that is typical of the sciences a healthy pluralism would seem to be desirable where theories of explanation are concerned. Nevertheless, I argue that explanations are only unifying in Kitcher's unificationist sense if they are backed by the kind of understanding of underlying mechanisms, dispositions, constitutions, and dependencies that is central to a causalist account of explanation. This case can be made through analysis of Kitcher's account of the conditions under which apparent improvements in (...) unifying power may be judged spurious. But to clarify what is at issue I consider an archaeological case in which debate about the merits of an ambitious explanatory account reproduces exactly the intuitions that divide Salmon and Kitcher. The case in question is the “demic-diffusion” account of contemporary linguistic diversity advanced by Renfrew in the late 1980s: the thesis that the diffusion of agricultural populations, itself attributed to demographic pressure, was responsible for the spread of the ancestral root languages (e.g., proto-Indo-Eurpoean) that account for the existence and distribution of linguistic macrofamilies. The credibility of this powerfully unifying argument pattern depends entirely on the plausibility of its claims about the conditions and mechanisms actually responsible for the explanandum, the spread of agriculture, and not on an elaboration of its unificationist virtues. (shrink)

I reconstruct the discovery of the Higgs boson by the ATLAS collaboration at CERN as the application of a series of inferences from effects to causes. I show to what extent such diagnostic causal inferences can be based on well established knowledge gained in previous experiments. To this extent, causal reasoning can be used to infer the existence of entities, rather than just causal relationships between them. The resulting account relies on the principle of causality, attributes only a heuristic role (...) to the theory’s predictions, and shows how, and to what extent, data selection can be used to exclude alternative causes, even “unconceived” ones. (shrink)

The anti-realist argument from underconsideration focuses on the fact that, when scientists evaluate theories, they only ever consider a subset of the theories that can account for the available data. As a result, when scientists judge one theory to be superior to competitor theories, they are not warranted in drawing the conclusion that the superior theory is likely true with respect to what it says about unobservable entities and processes. I defend the argument from underconsideration from the objections of Peter (...) Lipton. I argue that the inconsistency that Lipton claims to find in the argument vanishes once we understand what the anti-realist means when she claims that scientists are reliable. I also argue that collapsing the distinction between relative and absolute evaluations, as Lipton recommends, has its costs. Finally, I briefly examine Richard Boyd's influential defence of realism. (shrink)

I take another look at the history of science and offer some fresh insights into why the history of science is filled with discarded theories. I argue that the history of science is just as we should expect it to be, given the following two facts about science: theories are always only partial representations of the world, and almost inevitably scientists will be led to investigate phenomena that the accepted theory is not fit to account for. Together these facts suggest (...) that most scientific theories are apt to be discarded sometime, superseded by new theories that better serve scientists’ new research interests. Consequently, it is reasonable to expect that many of the theories we currently accept, despite their many impressive successes, will be discarded sometime in the future. But I also argue that discarded theories are not always aptly characterized as a sign of failure or as a sign of some sort of shortcoming with science. Theories are discarded because scientists are making advances in their pursuit of knowledge. Thus, discarded theories are often a sign of the good health of science. Scientists are responding to their changing research interests. (shrink)

In this paper I criticize the commonly accepted idea that the generalizations of the special sciences should be construed as ceteris paribus laws. This idea rests on mistaken assumptions about the role of laws in explanation and their relation to causal claims. Moreover, the major proposals in the literature for the analysis of ceteris paribus laws are, on their own terms, complete failures. I sketch a more adequate alternative account of the content of causal generalizations in the special sciences which (...) I argue should replace the ceteris paribus conception. (shrink)

This paper explores the idea that laws express relationships between properties or universals as defended in Michael Tooley's recent book Causation: A Realist Approach. I suggest that the most plausible version of realism will take a different form than that advocated by Tooley. According to this alternative, laws are grounded in facts about the capacities and powers of particular systems, rather than facts about relations between universals. The notion of lawfulness is linked to the notion of invariance, rather than to (...) the metaphysical notion of a necessary connection. (shrink)

This paper discusses some procedures developed in recent work in machine learning for inferring causal direction from observational data. The role of independence and invariance assumptions is emphasized. Several familiar examples including Hempel’s flagpole problem are explored in the light of these ideas. The framework is then applied to problems having to do with explanatory direction in non-causal explanation.

Ethical discourse and fallacy theory come together in a natural way over concepts such as bias, prejudice, preconceived opinion, prototypical and stereotypical thinking, dogmatism and loyalty. By and large, these are concepts that have not been sufficiently worked up to bear the theoretical weight either of ethics or of logic. The present paper seeks to ameliorate this situation. It proposes that situations describable by any such concepts partition into (a) the rationally and morally regrettable and (b) the rationally and morally (...) impeccable, and in any event, unavoidable. Finding (b) will come as a surprise to some theorists. (shrink)

A standard line in the contemporary philosophical literature has it that physical theories are equivalent only when they agree on their empirical content, where this empirical content is often understood as being encoded in the equations of motion of those theories. In this article, we question whether it is indeed the case that the empirical content of a theory is exhausted by its equations of motion, showing that (for example) considerations of boundary conditions play a key role in the empirical (...) equivalence (or otherwise) of theories. Having argued for this, we show that philosophical claims made by Weatherall (2016) that electromagnetism in the Faraday tensor formalism is equivalent to electromagnetism in the vector potential formalism, and by Knox (2011) that general relativity is equivalent to teleparallel gravity, can both be called into question. We then show that properly considering the role of boundary conditions in theory structure can potentially restore these claims of equivalence and close with some remarks on the pragmatics of adjudications on theory identity. (shrink)

This paper was written with two aims in mind. A large part of it is just an exposition of Tarski's theory of truth. Philosophers do not agree on how Tarski's theory is related to their investigations. Some of them doubt whether that theory has any relevance to philosophical issues and in particular whether it can be applied in dealing with the problems of philosophy (theory) of science.In this paper I argue that Tarski's chief concern was the following question. Suppose a (...) language L belongs to the class of languages for which, in full accordance with some formal conditions set in advance, we are able to define the class of all the semantic interpretations the language may acquire. Every interpretation of L can be viewed as a certain structure to which the expressions of the language may refer. Suppose that a specific interpretation of the language L was singled out as the intended one. Suppose, moreover, that the intended interpretation can be characterized in a metalanguage L +. If the above assumptions are satisfied, can the notion of truth for L be defined in the metalanguage L + and, if it can, how can this be done? (shrink)

The ArgumentThe societal context within which science is pursued generally acts as a productive force in the generation of knowledge. To analyze this action it is helpful to consider particular modes of mediation through which societal concerns are projected into the very local and esoteric concerns of a particular domain of research. One such mode of mediation occurs through material systems. Here I treat two such systems – the steam engine and the electric telegraph – in the natural philosophy of (...) William Thomson (Lord Kelvin).The steam engine illustratesconceptualmediation. It simultaneously instantiates “labor value” in political economy and “work” in engineering mechanics, thereby identifying the two concepts in the region of their common reference. The partial identification carries with it a structural analogy between a network of concepts from political economy and a similar network in natural philosophy, providing a potent heuristic for the reformulation and further development of dynamics.The electric telegraph illustratesmethodologicalmediation. It projects the interests of engineering and industry into the interests of electromagnetic theory and vice versa, thereby establishing, in Thomson's view, a Baconian unity of truth and utility. As the common reference of theory and practice, the telegraph locates the truth of theoretical knowledge in its utility and the utility of practical knowledge in its truth.These particular cases of conceptual and methodological mediation indicate how the local practices, concepts, and interests of a research specialty, or subculture, draw on and are adapted to those of the larger culture within which they develop. Thus the analysis of mediation leads to an ecological model of the social construction of scientific knowledge. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...) of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

Schaffner’s model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner’s model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical (...) structures in theoretical biology. A reconstructed Schaffnerian model could therefore shed light on mathematical theory development in the biological sciences and on the epistemology of mathematical practices more generally. *Received November 2006; revised March 2009. †To contact the author, please write to: Philosophy Department, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064; e‐mail: [email protected]. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a "number crunching" technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories (and ascribes (...) that capacity instead to models) and more emphasis on the role of theory in guiding (rather than determining) the construction of models. (shrink)

Methodological reductionists practice ‘wannabe reductionism’. They claim that one should pursue reductionism, but never propose how. I integrate two strains in prior work to do so. Three kinds of activities are pursued as “reductionist”. “Successional reduction” and inter-level mechanistic explanation are legitimate and powerful strategies. Eliminativism is generally ill-conceived. Specific problem-solving heuristics for constructing inter-level mechanistic explanations show why and when they can provide powerful and fruitful tools and insights, but sometimes lead to erroneous results. I show how traditional metaphysical (...) approaches fail to engage how science is done. The methods used do so, and support a pragmatic and non-eliminativist realism. (shrink)

Richard Levins’ distinction between aggregate, composed and evolved systems acquires new significance as we recognize the importance of mechanistic explanation. Criteria for aggregativity provide limiting cases for absence of organization, so through their failure, can provide rich detectors for organizational properties. I explore the use of failures of aggregativity for the analysis of mechanistic systems in diverse contexts. Aggregativity appears theoretically desireable, but we are easily fooled. It may be exaggerated through approximation, conditions of derivation, and extrapolating from some conditions (...) of decomposition illegtimately to others. Evolved systems particularly may require analyses under alternative complementary decompositions. Exploring these conditions helps us to better understand the strengths and limits of reductionistic methods. (shrink)

This paper explores the relationship between common-sense psychology (CSP) and scientific psychology (SP) — which we could call the mind-mind problem. CSP has come under much attack recently, most of which is thought to be unjust or misguided. This paper's first section examines the many differences between the aims, interests, explananda, explanantia, methodology, conceptual frameworks, and relationships to the neurosciences, that divide CSP and SP. Each of the two is valid within its own territory, and there is no competition between (...) them — primarily because CSP is not, and has no interest in being, a scientific theory. In the second section some implications are drawn. First, neither CSP nor SP has the mind-body problem in its familiar form. Second, CSP, for excellent reasons, is not equipped to handle irrational or non-rational behaviour; there are some grounds for believing that this can and should be the task of SP. Third, philosophical psychology, or armchair theories of action, perception, etc., are doomed to failure. And, fourth, the realm of the psychological is so heterogeneous that no single model for either CSP or SP is likely to succeed. (shrink)

Typicality is routinely invoked in everyday contexts: bobcats are typically short-tailed; people are typically less than seven feet tall. Typicality is invoked in scientific contexts as well: typical gases expand; typical quantum systems exhibit probabilistic behaviour. And typicality facts like these support many explanations, both quotidian and scientific. But what is it for something to be typical? And how do typicality facts explain? In this paper, I propose a general theory of typicality. I analyse the notion of a typical property. (...) I provide a formalism for typicality explanations, and I give an account of why typicality explanations are explanatory. Along the way, I show how typicality facts explain a variety of phenomena, from everyday phenomena to the statistical mechanical behaviour of gases. Finally, I argue that typicality is not the same thing as probability. (shrink)

Recent work in the philosophy of science has been debunking theory and acclaiming practice. Recent work in philosophical psychology has been neglecting practice and emphasizing theory, suggesting that common?sense psychology is in all essential respects like any scientific theory. The marriage of these two strands of thought would serve to make science and common sense virtually indistinguishable. My paper resists this conflation. The main target is the attempt to assimilate everyday psychology to a scientific theory; I argue that this is (...) badly mistaken, and does a disservice both to scientific and to common?sense psychology. A secondary aim is to argue that some of the new pragmatism in the philosophy of science is overstated. The suggested conflation would have interesting implications, as would its denial; in a concluding section, some of these implications are briefly explored. (shrink)

Don Ihde has recently launched a sweeping attack against Husserl’s late philosophy of science. Ihde takes particular exception to Husserl’s portrayal of Galileo and to the results Husserl draws from his understanding of Galilean science. Ihde’s main point is that Husserl paints an overly intellectualistic picture of the “father of modern science”, neglecting Galileo’s engagement with scientific instruments such as, most notably, the telescope. According to Ihde, this omission is not merely a historiographical shortcoming. On Ihde’s view, it is only (...) on the basis of a distorted picture of Galileo that Husserl can “create“ the division between Lifeworld and the “world of science“, a division that is indeed fundamental for Husserl’s overall position. Hence, if successful, Ihde’s argument effectively undermines Husserl’s late philosophy of science. The aim of this paper is to show that Ihde’s criticism does not stand up to closer historical or philosophical scrutiny. (shrink)

Husserl’s early picture of explanation in the sciences has never been completely provided. This lack represents an oversight, which we here redress. In contrast to currently accepted interpretations, we demonstrate that Husserl does not adhere to the much maligned deductive-nomological (DN) model of scientific explanation. Instead, via a close reading of early Husserlian texts, we reveal that he presents a unificationist account of scientific explanation. By doing so, we disclose that Husserl’s philosophy of scientific explanation is no mere anachronism. It (...) is, instead, tenable and relevant. We discuss how Husserl and other contemporary thinkers draw theoretical inspiration from the same source—namely, Bernard Bolzano. Husserl’s theory of scientific explanation shares a common language and discusses the same themes as, for example, Phillip Kitcher and Kit Fine. To advance our novel reading, we discuss Husserl’s investigations of grounding, inter-lawful explanation, intra-mathematical explanation, and scientific unification. (shrink)

Inductive logic admits a variety of semantics (Haenni et al., 2011, Part 1). This paper develops semantics based on the norms of Bayesian epistemology (Williamson, 2010, Chapter 7). §1 introduces the semantics and then, in §2, the paper explores methods for drawing inferences in the resulting logic and compares the methods of this paper with the methods of Barnett and Paris (2008). §3 then evaluates this Bayesian inductive logic in the light of four traditional critiques of inductive logic, arguing (i) (...) that it is language independent in a key sense, (ii) that it admits connections with the Principle of Indifference but these connections do not lead to paradox, (iii) that it can capture the phenomenon of learning from experience, and (iv) that while the logic advocates scepticism with regard to some universal hypotheses, such scepticism is not problematic from the point of view of scientific theorising. (shrink)

Traditional nomological accounts of scientific explanation have assumed that a good scientific explanation consists in the derivation of the explanandum’s description from theory (plus antecedent conditions). But in more recent philosophy of science the adequacy of this approach has been challenged, because the relation between theory and phenomena in actual scientific practice turns out to be more intricate. This critique is here examined for an explanatory paradigm that was groundbreaking for 20th century physics and chemistry (and their interrelation): Bohr’s first (...) model of the atom and its explanatory relevance for the spectrum of hydrogen. First, the model itself is analysed with respect to the principles and assumptions that enter into its premises. Thereafter, the origin of the model’s explanandum is investigated. It can be shown that the explained “phenomenon” is itself the product of a host of modelling accomplishments that stem from an experimental tradition related to 19th century chemistry, viz. spectroscopy. The relation between theory and phenomenon is thus mediated in a twofold way: by (Bohr’s) theoretical model and a phenomenological model from spectroscopy. In the final section of the paper an account is outlined that nevertheless permits us to acknowledge this important physico-chemical achievement as a case of (nomological) explanation. (shrink)

I put forward several desiderata that a philosophical theory of causality should satisfy: it should account for the objectivity of causality, it should underpin formalisms for causal reasoning, it should admit a viable epistemology, it should be able to cope with the great variety of causal claims that are made, and it should be ontologically parsimonious. I argue that Nancy Cartwright’s dispositional account of causality goes part way towards meeting these criteria but is lacking in important respects. I go on (...) to argue that my epistemic account, which ties causal relationships to an agent’s knowledge and ignorance, performs well in the light of the desiderata. Such an account, I claim, is all we require from a theory of causality. (shrink)

Dispositions can combine as vector sums. Recent authors on dispositions, such as George Molnar and Stephen Mumford, have responded to this feature of dispositions by introducing a distinction between effects and contributions to effects, and by identifying disposition-manifestations with the latter. But some have been sceptical of the reality or knowability of component vectors; Jennifer McKitrick (forthcoming) presses these concerns against the conception of manifestations as contributions to effects. In this paper, I aim to respond to McKitrick's arguments and to (...) defend the metaphysical and epistemological propriety of component vectors. My strategy appeals to varying kinematic frames of reference. By transforming to the appropriate non-inertial frame, component acceleration vectors can be transformed into resultant acceleration vectors, and in such frames they become directly observable. Being a component acceleration vector and being a resultant acceleration vector are both frame-dependent properties of properties; they are not to be thought of as intrinsic or fundamental properties of an acceleration vector, but as artefacts of our frame-dependent notation for representing vector quantities. To conclude the paper, I defend the view proposed against two styles of objection. The first objection resurrects scepticism about component vectors as scepticism about fundamental component vectors. The second objection questions the need for reference frames in the explanation by invoking a 'counterfactual' theory of contributions. (shrink)

How could the initial, drastic decisions to implement “lockdowns” to control the spread of COVID-19 infections be justifiable, when they were made on the basis of such uncertain evidence? We defend the imposition of lockdowns in some countries by first, and focusing on the UK, looking at the evidence that undergirded the decision, second, arguing that this provided us with sufficient grounds to restrict liberty given the circumstances, and third, defending the use of poorly-empirically-constrained epidemiological models as tools that can (...) legitimately guide public policy. (shrink)

It has been argued that the fundamental laws of physics do not face a ‘problem of provisos’ equivalent to that found in other scientific disciplines (Earman, Roberts and Smith 2002) and there is only the appearance of exceptions to physical laws if they are confused with differential equations of evolution type (Smith 2002). In this paper I argue that even if this is true, fundamental laws in physics still pose a major challenge to standard Humean approaches to lawhood, as they (...) are not in any obvious sense about regularities in behaviour. A Humean approach to physical laws with exceptions is possible, however, if we adopt a view of laws that takes them to be the algorithms in the algorithmic compressions of empirical data. When this is supplemented with a distinction between lossy and lossless compression, we can explain exceptions in terms of compression artefacts present in the application of the lossy laws. (shrink)

Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...) Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

Three contrasting approaches to the epistemology of argument are presented. Each one is naturalistic, drawing upon successful practices as the basis for epistemological virtue. But each looks at very different sorts of practices and they differ greatly as to the manner with which relevant practices may be described. My own contribution relies on a metamathematical reconstruction of mature science, and as such, is a radical break with the usual approaches within the theory of argument.

In this article it is argued that a complex model that includes Toulmin's functional account of argument, the pragma-dialectical stage analysis of argumentation offered by the Amsterdam School, and criteria developed in critical thinking theory, can be used to account for the normativity and field-dependence of argumentation in science. A pragma-dialectical interpretation of the four main elements of Toulmin's model, and a revised account of the double role of warrants, illuminates the domain specificity of scientific argumentation and the restrictions to (...) which the confrontation and opening stages of scientific critical discussions are subjected. In regard to the argumentation stage, examples are given to show that a general account of argumentation, as advocated by informal logicians, is not applicable to arguments in science. Furthermore, although patterns of inference differ in various scientific practices, deductive validity is argued to be a crucial notion in the assessment of scientific arguments. Finally, some remarks are made concerning the burden of proof and the concluding stage of scientific argumentation. (shrink)

In this paper I adduce a new argument in support of the claim that IBE is an autonomous form of inference, based on a familiar, yet surprisingly, under-discussed, problem for Hume’s theory of induction. I then use some insights thereby gleaned to argue for the claim that induction is really IBE, and draw some normative conclusions.

Although most philosophical accounts about model/world relations focus on structural mappings such as isomorphism, similarity has long been discussed as an alternative account. Despite its attractions, proponents of the similarity view have not provided detailed accounts of what it means that a model is similar to a real-world target system. This article gives the outlines of such an account, drawing on the work of Amos Tversky.

Simulation and Similarity: Using Models to Understand the World is an account of modeling in contemporary science. Modeling is a form of surrogate reasoning where target systems in the natural world are studied using models, which are similar to these targets. My book develops an account of the nature of models, the practice of modeling, and the similarity relation that holds between models and their targets. I also analyze the conceptual tools that allow theorists to identify the trustworthy aspects of (...) models. Taken as a whole, I try to account for the ways that modeling is actually practiced by theorists, while abstracting sufficiently to understand the similarities and differences among examples of concrete, mathematical, and computational modeling.I am grateful to Wendy Parker, Jay Odenbaugh, and Bill Wimsatt for their careful and interesting reading of my book, as well as their constructive criticisms. Although I naturally disagree with some of their critiques, I have learned much .. (shrink)

A seemingly plausible application of Bayesian decision-theoretic reasoning to determine one's rational degrees of belief yields a paradoxical conclusion: one ought to jettison one's intermediate credences in favour of more extreme (opinionated) ones. I discuss various attempts to solve the paradox, those involving the acceptance of the paradoxical conclusion, and those which attempt to block its derivation.

A worldview has six components. We concentrate on the first two: the descriptive world model and the explanatory world model. In the first half of the paper we make some general remarks on the methodology of world construction. In the second part, we discuss inconsistencies in world models. Adding new fragments to our world model can lead to inconsistencies. Three strategies are distinguished: (i) a partial return to instrumentalism, (ii) paraconsistency, and (iii) the adaptive option. The latter option is elaborated (...) by means of several historical examples and by means of the EPR paradox. (shrink)

In the current literature on scientific explanation unification became unfashionable in favour of causal approaches. We want to bring unification back into the picture. In this paper we demonstrate that resemblance questions do occur in scientific practice and that they cannot be properly answered without unification. Our examples show that resemblance questions about particular facts demand what we call causal network unification, while resemblance questions about regularities require what we call mechanism unification. We clarify how these types of unification relate (...) to Philip Kitcher’s account, but also to causal and mechanistic accounts of explanation. (shrink)

In this paper we discuss three interrelated questions. First: is explanation in mathematics a topic that philosophers of mathematics can legitimately investigate? Second: are the specific aims that philosophers of mathematical explanation set themselves legitimate? Finally: are the models of explanation developed by philosophers of science useful tools for philosophers of mathematical explanation? We argue that the answer to all these questions is positive. Our views are completely opposite to the views that Mark Zelcer has put forward recently. Throughout this (...) paper, we show why Zelcer’s arguments fail. (shrink)

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models – the representation of a hypothesis about a target system – are distinguished from several other relationships also termed “modelling” in discussions of scientific explanation. Seven dimensions on which (...) simulation models can differ are defined and distinctions between them discussed: 1. Relevance: whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments. Key Words: animal behaviour; levels; models; neuroethology; realism; robotics; simulation. (shrink)

I give two arguments for the claim that all events which occur at the actual world and are such that they could be caused, are also such that they must actually be caused. The first argument is an improvement of a similar argument advanced by Alexander Pruss, which I show to be invalid. It uses Pruss’s Brouwer Analog for counterfactual logic, and, as a consequence, implies inconsistency with Lewis’s semantics for counterfactuals. While (I suggest) this consequence may not be objectionable, (...) the argument founders on the fact that Pruss’s Brouwer Analog has a clear counterexample. I thus turn to a second, “Lewisian” argument, which requires only an affirmation of one element of Lewis’s analysis of causation and one other, fairly weak possibility claim about the nature of wholly contingent events. The final section of the paper explains how both arguments escape objections from supposed indeterminacy in quantum physics. (shrink)

I offer an explanation of why inertial and gravitational mass are equal in Newtonian gravitation. I then argue that this is an example of a kind of explanation that is not captured by standard philosophical accounts of scientific explanation. Moreover, this form of explanation is particularly important, at least in physics, because demands for this kind of explanation are used to motivate and shape research into the next generation of physical theories. I suggest that explanations of the sort I describe (...) reveal something important about one way in which physical theories may be related diachronically. (shrink)

Phylogenetic models traditionally represent the history of life as having a strictly-branching tree structure. However, it is becoming increasingly clear that the history of life is often not strictly-branching; lateral gene transfer, endosymbiosis, and hybridization, for example, can all produce lateral branching events. There is thus motivation to allow phylogenetic models to have a reticulate structure. One proposal involves the reconciliation of genealogical discordance. Briefly, this method uses patterns of disagreement – discordance – between trees of different genes to add (...) lateral branching events to phylogenetic trees of taxa, and to estimate the most likely cause of these events. I use this practice to argue for: (1) a need for expanded accounts of multiple-models idealization, (2) a distinction between automatic and manual de-idealization, and (3) recognition that idealization may serve the meso-level aims of science in a different way than hitherto acknowledged. (shrink)

Nancy Cartwright begins her recent book, Hunting Causes and Using Them, by noting that while a few years ago real causal claims were in dispute, nowadays “causality is back, and with a vengeance.” In the case of the social sciences, Keith Morrison writes that “Social science asks ‘why?’. Detecting causality or its corollary—prediction—is the jewel in the crown of social science research.” With respect to the health sciences, Judea Pearl writes that the “research questions that motivate most studies in the (...) health sciences are causal in nature.” However, not all data used by people interested in making causal claims come from experiments that use random assignment to control and treatment groups. Indeed, much research in the social and health science depends on non-experimental, observational data. Thus, one of the most important problems in the social and health sciences concerns making warranted causal claims using non-experimental, observational data; viz., “Can observational data be used to make etiological inferences leading to warranted causal claims?” This paper examines one method of warranting causal claims that is especially widespread in epidemiology and the health sciences generally—the use of causal criteria. It is argued that cases of complex causation generally, and redundant causation—both causal overdetermination and causal preemption—specifically, undermine the use of such criteria to warrant causal claims. (shrink)

Sean B. Carroll’s new book, The Serengeti Rules: The Quest to Discover How Life Works and Why it Matters, is a well-written mix of history of science and philosophy of biology. In his book, Carroll articulates a set of ecological generalisations, the Serengeti Rules, which are supposed to make salient the structures in ecosystems that ensure the persistence of those ecosystems. In this essay review, I evaluate Carroll’s use of the controversial concept of regulation and his thesis that ecosystems have (...) a natural balance comparable to that of human bodies. My conclusion is optimistic. Carroll’s generalisations provide a tool-kit for building relatively simple models that are accurate enough to be widely applied in experimental ecology and conservation science, guiding interventions upon unhealthy ecosystems. (shrink)