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)

George Molnar’s contention that some dispositional properties are displayed without the aid of any activating conditions poses a challenge to the conditional analysis of dispositions. Since the invocation of activating conditions is regarded as a crucial feature of the analysis, spontaneous dispositions are believed to expose its inadequacy by eluding its scope. The challenge goes to the very heart of the conditional approach to dispositions, allegedly revealing a deep flaw in all its incarnations. Granting that there may be spontaneously manifestable (...) dispositions, I argue that the conditional analysis can successfully accommodate them by elevating the potential causal relation between a disposition and its manifestation. (shrink)

What are ceteris paribus laws? Which disciplines appeal to cp laws and which semantics, metaphysical underpinning, and epistemological dimensions do cp law statements have? Firstly, we give a short overview of the recent discussion on cp laws, which addresses these questions. Secondly, we suggest that given the rich and diverse literature on cp laws a broad conception of cp laws should be endorsed which takes into account the different ways in which laws can be non-universal . Finally, we provide an (...) overview of the special issue on that basis and describe the individual contributions to the special issue according to the issues they address: the range of applications of cp laws as well as the semantics, metaphysics, and epistemology pertaining to cp law statements. (shrink)

Fodor argue that Darwinism cannot be true on the grounds that there are no laws of selection to support counterfactuals about why traits are selected-for. Darwinian explanations, according to this objection, amount to mere ‘plausible historical narratives’. I argue that the objection is predicated on two problematic assumptions: A nomic-subsumption account of causation and causal explanation, and a fine-grained view of the individuation of selected-for effects. Against the former, I argue that Darwinian explanations are a historical species of mechanistic explanation (...) and that mechanisms are causally productive and counterfactual supporting in the absence of appropriate laws. Once this mechanistic framework is in place, the demand for laws of selection vanishes and the historical cum causal coherence of Darwinism is restored. As for the second assumption, I argue that it is an artefact of the teleosemantic program with no basis in evolutionary biology and that properly understood, Darwinian evolutionary biology shows just why teleosemantics cannot succeed. (shrink)

Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes (“shocks”) that ultimately account for change in the model. In nonstationary models, such shocks accumulate (...) so that variables have discernible trends. Econometricians have conceived of variables that trend in sympathy with each other (so-called “cointegrated variables”) as sharing one or more of these unobserved trends as a common cause. It is possible for estimates of the values of both the otherwise unobservable individual shocks and the otherwise unobservable common trends to be backed-out of cointegrated systems of equations. The issue addressed in this paper is whether and in what circumstances these values can be regarded as observations of real entities rather than merely artifacts of the representation of variables in the model. The issue is related, on the one hand, to practical methodological problems in the use of SVARs for policy analysis—e.g., does it make sense to estimate of shocks or trends in one model and then use them as measures of variables in a conceptually distinct model? The issue is also related to debates in the philosophical analysis of causation—particularly, whether we are entitled, as assumed by the developers of Bayes-net approaches, to rely on the causal Markov condition (a generalization of Reichenbach’s common-cause condition) or whether cointegration generates a practical example of Nancy Cartwright’s “byproducts” objection to the causal Markov condition. (shrink)

Craig Callender, Jonathan Cohen and Markus Schrenk have recently argued for an amended version of the best system account of laws – the better best system account (BBSA). This account of lawhood is supposed to account for laws in the special sciences, among other desiderata. Unlike David Lewis's original best system account of laws, the BBSA does not rely on a privileged class of natural predicates, in terms of which the best system is formulated. According to the BBSA, a contingently (...) true generalization is a law of a special science S iff the generalization is an axiom (or a theorem) of the best system relative to the set of predicates used by special science S. We argue that the BBSA is, at best, an incomplete theory of special science laws, as it does not account for typical features of special science laws, such as attached ceteris paribus conditions and the idealized character of law statements in these disciplines. (shrink)

Earman and Roberts claim that there is neither a persuasive account of the truth-conditions of ceteris paribus laws, nor of how such laws can be confirmed or disconfirmed. I will give an account of the truth conditions of ceteris paribus laws in physics in terms of dispositions. It will meet the objections standardly raised against such an account. Furthermore I will elucidate how ceteris paribus laws can be tested in physics. The essential point is that physics provides methodologies for dealing (...) with disturbing factors. For this reason disturbing factors need not be listed explicitly in law-statements. In virtue of the methodologies it is possible to test how systems would behave if the disturbing factors were absent. I will argue that this suffices to establish the tenability of the dispositional account of ceteris paribus laws. (shrink)

Since early modernity, it has often been assumed that miracles are incompatible with the existence of the natural laws utilized in the sciences. This paper argues that this assumption is largely an artifact of empiricist accounts of laws that should be rejected for reasons internal to philosophy of science, and that no such incompatibility arises on the most important alternative interpretations, which treat laws as expressions of forces, dispositions, or causal powers.

It is common in psychiatry and other sciences to describe an individual or a type of individual in terms of its disposition to manifest specific effects in a particular range of circumstances. According to one understanding, dispositions are statistical regularities of an individual or type of individual in specific circumstances. According to another understanding, dispositions are properties of individuals in virtue of which such regularities hold. This entry considers a number of ways of making each of these senses of disposition (...) more precise while discussing a number of dangers lurking in careless use of the concept of a disposition. (shrink)

This article reviews the recent literature on idealization, specifically idealization in the course of scientific modeling. We argue that idealization is not a unified concept and that there are three different types of idealization: Galilean, minimalist, and multiple models, each with its own justification. We explore the extent to which idealization is a permanent feature of scientific representation and discuss its implications for debates about scientific realism.

In this paper we focus on two claims, put forward by Feyerabend in his later writings , which constitute the metaphysical core of his view of scientific inquiry. The first, that we call the pliability thesis, is the claim that the world can be described by indefinitely many conceptual systems, none of them enjoying a privileged status. The second, that we call the resistance thesis, is the claim that the pliability of the world is limited, i.e., not all the different (...) conceptual systems that can be used to describe the world will be equally successful: the world offers resistance to some attempts to describe it. We show that, in spite of the later Feyerabend’s notorious antirealist leanings, the pliability thesis is fully compatible with a robustly realist view of science, and we suggest that, surprisingly, Feyerabend’s insights concerning the limited pliability of the world turn out to be those of a potential ally of sophisticated versions of scientific realism. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

The 1994 US spectrum auction is now a paradigmatic case of the successful use of microeconomic theory for policy-making. We use a detailed analysis of it to review standard accounts in philosophy of science of how idealized models are connected to messy reality. We show that in order to understand what made the design of the spectrum auction successful, a new such account is required, and we present it here. Of especial interest is the light this sheds on the issue (...) of progress in economics. In particular, it enables us to get clear on exactly what has been progressing, and on exactly what theory has – and has not – contributed to that. This in turn has important implications for just what it is about economic theory that we should value. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

In what follows, I will give examples of the sorts of step that can be taken towards spelling out the intuition that, after all, good models might be true. Along the way, I provide an outline of my account of models as ontologically and pragmatically constrained representations. And I emphasize the importance of examining models as functionally composed systems in which different components play different roles and only some components serve as relevant truth bearers. This disputes the standard approach that (...) proceeds by simply counting true and false elements in models in their entirety and concludes that models are false since they contain so many false elements. I call my alternative the functional decomposition approach. (shrink)

Der Begriff ‘Modell’ leitet sich vom Lateinischen ‘modulus’ (das Maß) ab, im Italienischen existiert seit dem 16. Jh. ‘modello’ und R. Descartes verwendet im 17. Jh. ‘modèlle’. Während der Begriff in Architektur und Kunst schon seit der Renaissance gängig ist, wird er in den Naturwissenschaften erst im 19. Jh. verwendet.1 Dort greifen wissenschaftliche Modelle die für eine gegebene Problemstellung als wesentlich erachteten Charakteristika (Eigenschaften, Beziehungen, etc.) eines Untersuchungsgegenstandes heraus und machen diesen so einem Verständnis bzw. einer weiterführenden Untersuchung zugänglich. Es (...) ist üblich, zwischen Skalenmodellen, Analogmodellen und theoretischen Modellen zu unterscheiden. (shrink)

The ArgumentWhile there has been muchattention given to experiment in modern science studies, there has been astoundingly little concern spared over the practice ofquanitataivemeasurment.Thus myths about the unreasonable effectiveness of mathematice in science still abound. This paper presents: An explicit mathematical model of the stabilization of quantitative constants in a mathematical science to rival older Bayesian and classical accounts;a framework for writing a history of pracitces with regard to treatment of quantitative measurement erroe; resourece for the comparative sociology of differing (...) discipliness in this regard;and a prolegonmena to a critique of orthodox economics and accounting theories. The key to all these diverse themes is the realization that no one individual alone is capable of fixing the magnitude of a quantitative error estimate, and therefore the social construction of error must be given a more precise meaning, an therefore the social construction of error must be given a more precise menaing, and that this occurs through the istrumentality of meta-analysis. (shrink)

Neuropragmatism is a research program taking sciences about cognitive development and learning methods most seriously, in order to reevaluate and reformulate philosophical issues. Knowledge, consciousness, and reason are among the crucial philosophical issues directly affected. Pragmatism in general has allied with the science-affirming philosophy of naturalism. Naturalism is perennially tested by challenges questioning its ability to accommodate and account for knowledge, consciousness, and reason. Neuropragmatism is in a good position to evaluate those challenges. Some ways to defuse them are suggested (...) here, along with recommendations about the specific kind of naturalism, a pluralistic and perspectival naturalism, that neuropragmatism should endorse. (shrink)

Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...) examined Ned Hall’s distinction between two concepts of causality: production and dependence. In another recent paper, Illari examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising. (shrink)

Renormalization group (RG) methods are an established strategy to explain how it is possible that microscopically different systems exhibit virtually the same macro behavior when undergoing phase-transitions. I argue – in agreement with Robert Batterman – that RG explanations are non-causal explanations. However, Batterman misidentifies the reason why RG explanations are non-causal: it is not the case that an explanation is non- causal if it ignores causal details. I propose an alternative argument, according to which RG explanations are non-causal explanations (...) because their explanatory power is due to the application mathematical operations, which do not serve the purpose of representing causal relations. (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)

Tun und Können erläutert und diskutiert den Gründungstext der Modalontologie: das neunte Buch der Metaphysik des Aristoteles. Aristoteles' Thesen und Argumente werden zum ersten Mal in Gänze mit formalen analytischen Mitteln rekonstruiert und auf ihre Kohärenz und Gültigkeit geprüft. Erstmals verwendet der Autor dazu eine adverbiale Analyse von Ausdrücken des Könnens und des Vermögens als Prädikatmodifikatoren. Das Buch zeigt, dass Aristoteles' Theorie der Vermögen nicht nur eine konsistente, sondern auch eine leistungsfähige Analyse von Dispositionen und Dispositionsprädikaten bietet. -/- Die Neuausgabe (...) wurde vollständig durchgesehen und um weiterführende Anhänge ergänzt. -/- Der Inhalt: Können, Tun und Möglichkeit. Eine Einführung • Die kausale Dimension von Vermögen • Die ontologische Dimension von Vermögen• Eine notwendige Bedingung für Vermögen • Hindernisse und Verwirklichung • Prioritätsfragen • Aristotle’s Theory of Dispositions • Das Problem des Neuen • Planners, Deciders, Performers. (shrink)

An attempt is made to defend realism and the absence of space-like causation in quantum mechanics, by invoking indeterminism and a new necessary condition for stochastic causality, we term robustness. This condition is defended against recent critical attacks by Cartwright and Jones, and by Healey, and the violation of the robustness condition in Bell-type correlation experiments is shown to follow if an appropriate interpretation of the state vector is employed.

Woodward’s interventionist theory of causation is beset by a problem of circularity: the analysis of causes is in terms of interventions, and the analysis of interventions is in terms of causes. This is not in itself an argument against the correctness of the analysis. But by requiring us to have causal knowledge prior to making any judgements about causation, Woodward’s theory does make it mysterious how we can ever start acquiring causal knowledge. We present a solution to this problem by (...) showing how the interventionist notion of causation can be rationally generated from a more primitive agency notion of causation. The agency notion is easily and non-circularly applicable, but fails when we attempt to capture causal relations between non-actions. We show that the interventionist notion of causation serves as an appropriate generalisation of the agency notion. Furthermore, the causal judgements based on the latter generally remain true when rephrased in terms of the former, which allows one to use the causal knowledge gained by applying the agency notion as a basis for applying Woodward’s interventionist theory. We then present an overview of relevant empirical evidence from developmental psychology which shows that our proposed rational reconstruction lines up neatly with the actual development of causal reasoning in children. This gives additional plausibility to our proposal. The article thus provides a solution to one of the main problems of interventionism while keeping Woodward’s analysis intact. (shrink)

In this chapter I investigate the prospects of integrated history and philosophy of science, by examining how philosophical issues raised by “hidden entities”, entities that are not accessible to unmediated observation, can enrich the historical investigation of their careers. Conversely, I suggest that the history of those entities has important lessons to teach to the philosophy of science. Hidden entities have played a crucial role in the development of the natural sciences. Despite their centrality to past scientific practice, however, several (...) of them (e.g., phlogiston, caloric, and the ether) turned out to be fictitious. For this reason, they have figured prominently in recent debates on scientific realism. The issues I explore in this paper are entangled with those debates. I argue that our understanding of hidden entities and their role in experimental practice can be enhanced by adopting an integrated historical-cum-philosophical approach. On the one hand, philosophical reflection on the reality of those entities has a lot to gain by examining historically how they were ntroduced and investigated. On the other hand, the historical reconstruction of the careers of those entities may profit from philosophical reflection on their existence. (shrink)

There is good reason to believe that scientific realism requires a commitment to the objective modal structure of the physical world. Causality, equilibrium, laws of nature, and probability all feature prominently in scientific theory and explanation, and each one is a modal notion. If we are committed to the content of our best scientific theories, we must accept the modal nature of the physical world. But what does the scientific realist’s commitment to physical modality require? We consider whether scientific realism (...) is compatible with Humeanism about the laws of nature, and we conclude that it is not. We specifically identify three major problems for the best-systems account of lawhood: its central concept of strength cannot be formulated non-circularly, it cannot offer a satisfactory account of the laws of the special sciences, and it can offer no explanation of the success of inductive inference. In addition, Humeanism fails to be naturalistically motivated. For these reasons, we conclude that the scientific realist must embrace natural necessity. (shrink)

Este documento analiza las siguientes cuestiones: 1) La metodología de la economía y su actual institucionalización. 2) La definición de Economía. 3) Las perspectivas de los economistas acerca de la Economía, sus métodos y justificación. 4) Comprobación y progreso: Popper y Lakatos.5) Los modelos y sus supuestos. 6) Persuasión retórica y verdad. 7) La Economía como un recurso para la Filosofía de la Ciencia. 8) Expansionismo explicativo y relaciones interdisciplinares.

My philosophical intuitions are those of a scientific realist. In addition to being realist in its philosophical outlook, my philosophy of economics also aspires to be realistic in the sense of being descriptively adequate, or at least normatively non-utopian, about economics as a scientific discipline. The special challenge my philosophy of economics must meet is to provide a scientific realist account that is realistic of a discipline that deals with a complex subject matter and operates with highly unrealistic models. Unrealisticness (...) in economic models must not constitute an obstacle to realism about those models. What follows is a selective and somewhat abstract summary of my thinking about economics, outlined from two perspectives: first historical and autobiographical, then systematic and comparative. The first angle helps understand motives and trajectories of ideas against their backgrounds in intellectual history. My story turns out to have both unique and generalizable aspects. The second approach outlines some of the key concepts and arguments as well as their interrelations in my philosophy of economics, with occasional comparisons to other views. More space will be devoted to this second perspective than to the first. (shrink)

This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...) turn implies the importance of studying the scientific methods employed by researchers. Finally, by way of providing an overview of each chapter in the volume, this chapter demonstrates that biology and economics are two fertile fields for the philosophy of science and shows how biological and economic mechanisms and causality can be synthesized. (shrink)

The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...) philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based. (shrink)

After a brief survey of the literature on ceteris paribus clauses and ceteris paribus laws (1), the problem of exceptions, which creates the need for cp laws, is discussed (2). It emerges that the so-called skeptical view of laws of nature does not apply to laws of any kind whatever. Only some laws of physics are plagued with exceptions, not THE laws (3). Cp clauses promise a remedy, which has to be located among the further reactions to the skeptical view (...) (4). After inspecting various translations of the Latin term 'ceteris paribus' (5), the paper arrives at the conclusion that, on the most reasonable translation, there are no such things as cp laws, for reasons of logical form. Cp clauses have an indexical content, so that they need singular propositions as their habitat, not general ones. Cp clauses and the universal generalizations they are supposed to modify are not fit for each other (6). (shrink)

Proponents of evidence-based medicine and some philosophers of science seem to agree that knowledge of mechanisms can help solve the problem of applying results of controlled studies to target populations (‘the problem of extrapolation’). We describe the problem of extrapolation, characterize mechanisms, and outline how mechanistic knowledge might be used to solve the problem. Our main thesis is that there are four often overlooked problems with using mechanistic knowledge to solve the problem of extrapolation. First, our understanding of mechanisms is (...) often (and arguably, likely to remain) incomplete. Secondly, knowledge of mechanisms is not always applicable outside the tightly controlled laboratory conditions in which it is gained. Thirdly, mechanisms can behave paradoxically. Fourthly, as Daniel Steel points out, using mechanistic knowledge faces the problem of the ‘extrapolator’s circle’. At the same time, when the problems with mechanistic knowledge have been addressed, such knowledge can and should be used to mitigate (nothing can entirely solve) the problem of extrapolation. (shrink)

This paper considers the applicability of standard accounts of causation to living systems. In particular it examines critically the increasing tendency to equate causal explanation with the identification of a mechanism. A range of differences between living systems and paradigm mechanisms are identified and discussed. While in principle it might be possible to accommodate an account of mechanism to these features, the attempt to do so risks reducing the idea of a mechanism to vacuity. It is proposed that the solution (...) to this problem requires the development of a philosophical account of process adequate to apply to living systems. (shrink)

Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in (...) a way that prevents those hypotheses from being false by virtue of their constituent idealizations. (shrink)

Embodied cognitive science has argued that cognition is embodied principally in virtue of grossmorphological and sensorimotor features. This thesis argues that cognition is also internally embodied in affective and fine-grained physiological features whose transformative roles remain mostly unnoticed in contemporary cognitive science. I call this ‘proper embodiment’. I approach this larger subject by examining various emotion theories in philosophy and psychology. These tend to emphasise one of the many gross components of emotional processes, such as ‘feeling’ or ‘judgement’ to the (...) detriment of the others, often leading to an artificial emotion-cognition distinction even within emotion science itself. Attempts to reconcile this by putting the gross components back together, such as JessePrinz’s “embodied appraisal theory”, are, I argue, destined to failure because the vernacular concept of emotion which is used as the explanandum is not a natural kind and is not amenable to scientific explication.I examine Antonio Damasio’s proposal that emotion is involved in paradigmatic ‘cognitive’ processing such as rational decision making and argue (1) that the research he discusses does not warrant the particular hypothesis he favours, and (2) that Damasio’s account, though in many ways a step in the right direction, nonetheless continues to endorse a framework which sees affect and cognition as separate (though now highly interacting) faculties. I further argue that the conflation of ‘affect’ and 'emotion' may be the source of some confusion in emotion theory and that affect needs to be properly distinguished from ‘emotion’. I examine some dissociations in the pain literature which give us further empirical evidence that, as with the emotions, affect is a distinct component along with more cognitive elements of pain. I then argue that affect is distinctive in being grounded in homeostatic regulative activity in the body proper. With the distinction between affect, emotion, and cognition in hand, and the associated grounding of affect in bodily activity, I then survey evidence that bodily affect is also involved in perception and in paradigmatic cognitive processes such as attention and executive function. I argue that this relation is not ‘merely’ casual. Instead, affect (grounded in fine-grained details of internal bodily activity) is partially constitutive of cognition, participating in cognitive processing and contributing to perceptual and cognitive phenomenology. Finally I review some work in evolutionary robotics which reaches a similar conclusion, suggesting that the particular fine details of embodiment, such as molecular signalling between both neural and somatic cells matters to cognition. I conclude that cognition is properly embodied’ in that it is partially constituted by the many fine-grained bodily processes involved in affect (as demonstrated in the thesis) and plausibly by a wide variety of other fine-grained bodily processes that likewise tend to escape the net of contemporary cognitive science. (shrink)

In medicine and the social sciences, researchers must frequently integrate the findings of many observational studies, which measure overlapping collections of variables. For instance, learning how to prevent obesity requires combining studies that investigate obesity and diet with others that investigate obesity and exercise. Recently developed causal discovery algorithms provide techniques for integrating many studies, but little is known about what can be learned from such algorithms. This article argues that there are causal facts that one could learn by conducting (...) a large study but which could not be learned by combining many smaller studies. Moreover, I characterize the frequency with which combining many studies increases underdetermination and exactly how much information is lost. 1 Introduction2 Causal Inference from Observational Data3 Piecemeal Causal Inference4 The Extent and Frequency of the Problem of Piecemeal Induction5 Conclusion. (shrink)