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)

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)

Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these (...) two views with respect to four points regarding ontological assumptions: (1) the origin of ontological assumptions, (2) the relation of such assumptions to the formal models of the same theory, (3) their use in integrating and negotiating different formal models of distinct theories, and (4) their employment in explanatory activity. Dialectical is here used in both its Hegelian–Marxist sense of opposition and tension between alternative positions and in its Platonic sense of dialogue between advocates of distinct theories. I investigate three case studies, from Levins and Lewontin as well as from a recent paper of mine, that show the relevance and power of the dialectical understanding of theorizing and modeling. (shrink)

This paper explores some connections between competing conceptions of scientific laws on the one hand, and a problem in the foundations of statistical mechanics on the other. I examine two proposals for understanding the time asymmetry of thermodynamic phenomenal: David Albert's recent proposal and a proposal that I outline based on Hans Reichenbach's “branch systems”. I sketch an argument against the former, and mount a defense of the latter by showing how to accommodate statistical mechanics to recent developments in the (...) philosophy of scientific laws. (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)

Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of its parts if it depends upon their mode of organization-a view consistent with reduction. Emergence is a failure of aggregativity, in which ``the whole is nothing more than the sum of its parts''. Aggregativity requires four conditions, giving powerful tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different degrees, the structural conditions (...) can provide evaluation criteria for choosing decompositions, ``natural kinds'', and detecting functional localization fallacies, approximations, and various biases of vulgar reductionisms. This analysis of emergence and use of these conditions as heuristics is consistent with a broader reductionistic methodology. (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)

Do component forces exist in conjoined circumstances? Cartwright (1980) says no; Creary (1981) says yes. I'm inclined towards Cartwright's side in this matter, but find several problems with her argumentation. My primary aim here is to present a better, distinctly causal, argument against component forces: very roughly, I argue that the joint posit of component and resultant forces in conjoined circumstances gives rise to a threat of causal overdetermination, avoidance of which best proceeds via eliminativism about component forces. A secondary (...) aim is to show that rejecting component forces does not require, pace Cartwright, rejecting certain attractive theses about what laws of nature express and the role such laws play in scientific explanations. (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)

Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...) what consequences those tradeoffs have for theoretical practice. (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)

Roald Hoffmann and other theorists claim that we ought to use highly idealized chemical models (“qualitative models”) in order to increase our understanding of chemical phenomena, even though other models are available which make more highly accurate predictions. I assess this norm by examining one of the tradeoffs faced by model builders and model users—the tradeoff between precision and generality. After arguing that this tradeoff obtains in many cases, I discuss how the existence of this tradeoff can help us defend (...) Hoffmann's norm for modelling. (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)

Quantum mechanics, and classical mechanics, are framework theories that incorporate many different concrete theories which in general cannot be arranged in a neat hierarchy, but discussion of ‘the ontology of quantum mechanics’ tends to proceed as if quantum mechanics were a single concrete theory, specifically the physics of nonrelativistically moving point particles interacting by long-range forces. I survey the problems this causes and make some suggestions for how a more physically realistic perspective ought to influence the metaphysics of quantum mechanics.

Quantum mechanics, and classical mechanics, are framework theories that incorporate many different concrete theories which in general cannot be arranged in a neat hierarchy, but discussion of ‘the ontology of quantum mechanics’ tends to proceed as if quantum mechanics were a single concrete theory, specifically the physics of nonrelativistically moving point particles interacting by long-range forces. I survey the problems this causes and make some suggestions for how a more physically realistic perspective ought to influence the metaphysics of quantum mechanics.

Personalised medicine has been discussed as a medical paradigm shift that will improve health while reducing inefficiency and waste. At the same time, it raises new practical, regulatory, and ethical challenges. In this paper, we examine PM strategies epistemologically in order to develop capacities to address these challenges, focusing on a recently proposed strategy for developing patient-specific models from induced pluripotent stem cells so as to make individualised treatment predictions. We compare this strategy to two main PM strategies—stratified medicine and (...) computational models. Drawing on epistemological work in the philosophy of medicine, we explain why these two methods, while powerful, are neither truly personalised nor, epistemologically speaking, novel strategies. Both are forms of correlational black box. We then argue that the iPSC models would count as a new kind of black box. They would not rely entirely on mechanistic knowledge, and they would utilise correlational evidence in a different way from other strategies—a way that would enable personalised predictions. In arguing that the iPSC models would present a novel method of gaining evidence for clinical practice, we provide an epistemic analysis that can help to inform the practical, regulatory, and ethical challenges of developing an iPSC system. (shrink)

Is a policy-friendly philosophy of science possible? In order to respond this question, I consider a particular instance of contemporary philosophy of science, the semantic view of scientific theories, by placing it in the broader methodological landscape of the integration of philosophy of science into STS (Science and Technology Studies) as a component of the overall contribution of the latter to science policy. In that context, I defend a multi-disciplinary methodological integration of the special discipline composing STS against a reductionist (...) interdisciplinary unification, arguing that if STS wants to contribute to policy advising by constructing narratives of science practice feasible for science policy both in terms of descriptive completeness and intelligibility, then it must avoid the explanatory reductionism tendencies of special disciplines in interdisciplinary contexts. This would favour, at the same time, a relaxation of esoteric language. On this basis, it seems that the semantic view is one right candidate among other approaches in the philosophy of science for facilitating the integration of the methodologically different contributions to STS toward policy objectives. In fact, besides offering a more realistic and descriptively complete picture of science practice with respect to its predecessor in the philosophy of science, namely the syntactic view, the semantic view is also able to capture some aspects of science practice that elude even sociological approaches to STS, thus inviting different perspective on the same subject matter. (shrink)

For several decades now philosophers have discussed apparent examples of internally inconsistent scientific theories. However, there is still much controversy over how exactly we should conceive of scientific theories in the first place. Here I argue for a new approach, whereby all of the truly important questions about inconsistency in science can be asked and answered without disagreements about theories and theory-content getting in the way. Three examples commonly described as ‘internally inconsistent theories’ are analysed in the light of this (...) approach. In the process, the question ‘Is the theory inconsistent or not?’ is identified as a bad, or at least unimportant, question. (shrink)

The anticipation of the typical under the assumption of the non-occurrence of the atypical is the experiential schema governing the individuation of ordinary enduring objects and their properties. Against this background, a primitive form of “if-and-only-if” consciousness is implicit in our everyday perceptual intentions. The thematization of the fact that perception operates under this proto-tentative structure occurs at the level of reflection and is expressed by defeasible judgments of the form “if p, then q, unless r,” or “if p, then (...) q provided that not-r”. Here I will argue that what is made thematic by judgments containing such restrictive clauses is the structure of unpredictability inherent in what Husserl calls the horizon of latency and, indirectly, the world as background of normality. (shrink)

Modal dispositionalism is the view that possibilities are a matter of the dispositions of individual objects: it is possible that p if and only if something has a disposition for p to be the case. We raise a problem for modal dispositionalism: nothing within the theory rules out that there could be necessary, perfect masks, which make the manifestation of a disposition impossible. Unless such necessary perfect masks are ruled out, modal dispositionalism runs the risk of failing to provide a (...) sufficient condition for possibility, and indeed of engendering contradictions. But to rule them out, modal dispositionalism would have to revise a crucial tenet of the view, its localism. (shrink)