In this essay, it is argued that naturalism of an even moderate sort speaks strongly against a certain widely held thesis about the human mental (and cognitive) architecture: that it is divided into two distinct levels, the personal and the subpersonal, about the former of which we gain knowledge in a manner that effectively insulates such knowledge from the results of scientific research. -/- An empirically motivated alternative is proposed, according to which the architecture is, so to speak, flattened from (...) above. On this flattened view, although the states and processes typically associated with the personal level likely appear in our best models of the production of human behavior, they appear alongside states and processes normally associated with the subpersonal level. Moreover, the success of such models depends nowise on a levels-based distinction between the various causal contributors. It is argued that the flattened view has methodological implications of significant import. (shrink)

This expository paper presents a general framework for representing levels and inter-level relations. The framework is intended to capture both epistemic and ontological notions of levels and to clarify the sense in which levels of explanation might or might not be related to a levelled ontology. The framework also allows us to study and compare different kinds of inter-level relations, especially supervenience and reduction but also grounding and mereological constitution. This, in turn, enables us to explore questions such as whether (...) supervenience implies explanatory reducibility and whether there can be irreducible higher-level explanations or even “emergent” higher-level properties. The paper finally discusses some further philosophical applications: to the free-will debate, the determinism-indeterminism distinction, indexicality and consciousness, and the relationship between positive and normative facts. (shrink)

Laws of nature take center stage in philosophy of science. Laws are usually believed to stand in a tight conceptual relation to many important key concepts such as causation, explanation, confirmation, determinism, counterfactuals etc. Traditionally, philosophers of science have focused on physical laws, which were taken to be at least true, universal statements that support counterfactual claims. But, although this claim about laws might be true with respect to physics, laws in the special sciences (such as biology, psychology, economics etc.) (...) appear to have—maybe not surprisingly—different features than the laws of physics. Special science laws—for instance, the economic law “Under the condition of perfect competition, an increase of demand of a commodity leads to an increase of price, given that the quantity of the supplied commodity remains constant” and, in biology, Mendel's Laws—are usually taken to “have exceptions”, to be “non-universal” or “to be ceteris paribus laws”. How and whether the laws of physics and the laws of the special sciences differ is one of the crucial questions motivating the debate on ceteris paribus laws. Another major, controversial question concerns the determination of the precise meaning of “ceteris paribus”. Philosophers have attempted to explicate the meaning of ceteris paribus clauses in different ways. The question of meaning is connected to the problem of empirical content, i.e., the question whether ceteris paribus laws have non-trivial and empirically testable content. Since many philosophers have argued that ceteris paribus laws lack empirically testable content, this problem constitutes a major challenge to a theory of ceteris paribus laws. (shrink)

Emergence is a notorious philosophical term of art. A variety of theorists have appropriated it for their purposes ever since George Henry Lewes gave it a philosophical sense in his 1875 Problems of Life and Mind. We might roughly characterize the shared meaning thus: emergent entities (properties or substances) ‘arise’ out of more fundamental entities and yet are ‘novel’ or ‘irreducible’ with respect to them. (For example, it is sometimes said that consciousness is an emergent property of the brain.) Each (...) of the quoted terms is slippery in its own right, and their specifications yield the varied notions of emergence that we discuss below. There has been renewed interest in emergence within discussions of the behavior of complex systems and debates over the reconcilability of mental causation, intentionality, or consciousness with physicalism. (shrink)

Cognitive science is the interdisciplinary investigation of mind and intelligence, embracing psychology, neuroscience, anthropology, artificial intelligence, and philosophy. There are many important philosophical questions related to this investigation, but this short chapter will focus on the following three. What is the nature of the explanations and theories developed in cognitive science? What are the relations among the five disciplines that comprise cognitive science? What are the implications of cognitive science research for general issues in the philosophy of science? I will (...) argue that cognitive theories and explanations depend on representations of mechanisms and that the relations among the five disciplines, especially psychology and neuroscience, depend on relations between kinds of mechanisms. These conclusions have implications for central problems in general philosophy of science such as the nature of theories, explanations, and reduction between theories at different levels. (shrink)

Over the past three decades, philosophy of science has grown increasingly “local.” Concerns have switched from general features of scientific practice to concepts, issues, and puzzles specific to particular disciplines. Philosophy of neuroscience is a natural result. This emerging area was also spurred by remarkable recent growth in the neurosciences. Cognitive and computational neuroscience continues to encroach upon issues traditionally addressed within the humanities, including the nature of consciousness, action, knowledge, and normativity. Empirical discoveries about brain structure and function suggest (...) ways that “naturalistic” programs might develop in detail, beyond the abstract philosophical considerations in their favor. -/- The literature distinguishes “philosophy of neuroscience” and “neurophilosophy.” The former concerns foundational issues within the neurosciences. The latter concerns application of neuroscientific concepts to traditional philosophical questions. Exploring various concepts of representation employed in neuroscientific theories is an example of the former. Examining implications of neurological syndromes for the concept of a unified self is an example of the latter. In this entry, we will assume this distinction and discuss examples of both. (shrink)

The systems studied in the special sciences are often said to be causally autonomous, in the sense that their higher-level properties have causal powers that are independent of the causal powers of their more basic physical properties. This view was espoused by the British emergentists, who claimed that systems achieving a certain level of organizational complexity have distinctive causal powers that emerge from their constituent elements but do not derive from them. More recently, non-reductive physicalists have espoused a similar view (...) about the causal autonomy of special-science properties. They argue that since these properties can typically have multiple physical realizations, they are not identical to physical properties, and further they possess causal powers that differ from those of their physical realisers. Despite the orthodoxy of this view, it is hard to find a clear exposition of its meaning or a defence of it in terms of a well-motivated account of causation. In this paper, we aim to address this gap in the literature by clarifying what is implied by the doctrine of the causal autonomy of special-science properties and by defending the doctrine using a prominent theory of causation from the philosophy of science. (shrink)

The current view of the relationship between areas of the mind-brain sciences is one where cross-disciplinary collaboration is required to advance claims about the mind-brain that stand on firm epistemic footing. My goal in this dissertation is to analyze what it means for information from different areas of science to fit together to produce strong epistemic claims by addressing how and to what extent claims about the mind-brain are corroborated in scientific practice. Philosophers of science have advanced various concepts of (...) the notion of fitting together information from different areas of science and its relation to scientific progress (e.g., Bickle, 1998, 2003, 2006; Darden and Maull, 1977; Mitchell, 2002, 2003; Mitchell and Dietrich, 2006; Nagel 1949, 1970, 1979; Piccinini and Craver, 2011; and Roskies, 2010). However, each concept of fitting together is vague and subject to multiple clarificatory questions. To get a handle on the notion of fitting together, I introduce the term ‘interdisciplinary corroboration’ as a placeholder for the various accounts of fitting together to facilitate my investigation of how claims about the mind-brain are corroborated in scientific practice. I argue review papers are a good place to begin analyzing interdisciplinary corroboration; accordingly, I conduct a two-part analysis of a review paper by Eichenbaum (2013) entitled ‘Memory on Time’. I use the lessons from my analysis to develop and advance a methodology for philosophers of science interested in knowledge production for evaluating review papers for corroboration in the mind-brain sciences. (shrink)

Mechanisms have become much-discussed, yet there is still no consensus on how to characterise them. In this paper, we start with something everyone is agreed on – that mechanisms explain – and investigate what constraints this imposes on our metaphysics of mechanisms. We examine two widely shared premises about how to understand mechanistic explanation: (1) that mechanistic explanation offers a welcome alternative to traditional laws-based explanation and (2) that there are two senses of mechanistic explanation that we call ‘epistemic explanation’ (...) and ‘physical explanation’. We argue that mechanistic explanation requires that mechanisms are both real and local. We then go on to argue that real, local mechanisms require a broadly active metaphysics for mechanisms, such as a capacities metaphysics. (shrink)

Tim Crane's ‘Cosmic Hermeneutics vs. Emergence: The Challenge of the Explanatory Gap’ claims that non‐reductive physicalism must either close the explanatory gap, addressing the challenge famously posed by Levine's argument, or become identical to emergentism. Since no way to close the gap is available, the result is that there can be no interesting philosophical position intermediate between physicalism and emergentism. This chapter argues that if we look at the relation between physicalism and emergentism from the vantage point of reduction, Crane's (...) analysis is rather persuasive. However, if we switch from reduction to causality, its conclusions appear more disputable. In particular, if we shift from ‘novelty and explanation’ to ‘novelty and causality’ as key features of emergent properties, we may introduce a distinction between two kinds of emergentism (moderate and radical) based on their attitude towards the causal inheritance principle. If the causal inheritance principle is accepted (some versions of) moderate emergentism may be considered as non‐trivial forms of non‐reductive physicalism. (shrink)

The Linda paradox is a key topic in current debates on the rationality of human reasoning and its limitations. We present a novel analysis of this paradox, based on the notion of verisimilitude as studied in the philosophy of science. The comparison with an alternative analysis based on probabilistic confirmation suggests how to overcome some problems of our account by introducing an adequately defined notion of verisimilitudinarian confirmation.

Many philosophers of science believe that empirical psychology can contribute little to the philosophical investigation of explanations. They take this to be shown by the fact that certain explanations fail to elicit any relevant psychological events (e.g., familiarity, insight, intelligibility, etc.). We report results from a study suggesting that, at least among those with extensive science training, a capacity to render an event intelligible is considered a requirement for explanation. We also investigate for whom explanations must be capable of rendering (...) events intelligible and whether or not accuracy is also viewed as a requirement. (shrink)

En este trabajo me propongo desarrollar un estudio crítico de la concepción mecanicista de la explicación científica. En primer lugar, argumento que la caracterización mecanicista de los modelos fenoménicos (no explicativos) es inadecuada, pues no ofrece un análisis aceptable de los conceptos de modelo científico y similitud, que son fundamentales para la propuesta. En segundo lugar, sostengo que la caracterización de los modelos mecanicistas (explicativos) es igualmente inadecuada, pues los análisis disponibles de la relación explicativa de relevancia constitutiva implican una (...) tesis metafísica que es rechazada por los mismos mecanicistas. Concluyo que el mecanicismo no ofrece todavía una elucidación aceptable de la explicación científica. In this paper, I offer a critical assessment of the mechanicist approach to scientific explanation. Firstly, I argue that the mechanicist characterization of (non explanatory) phenomenological models is inadequate, since it does not develop an explication of the concepts of scientific model and similarity, which are indispensable to the approach. Secondly, I claim that the mechanicist conception of (explanatory) mechanicist models is inadequate as well, since all the available analices of the explanatory relation of constitutive relevance imply a metaphysical thesis that is rejected by the mechanicists themselves. I conclude that mechanicism needs to be emended if it aims to be considered as a genuinely illuminating approach to scientific explanation. (shrink)

Debates about evolution and creation inevitably raise philosophical issues about the nature of scientific knowledge. What is a theory? What is an explanation? How is science different from non- science? How should theories be evaluated? Does science achieve truth? The aim of this chapter is to give a concise and accessible introduction to the philosophy of science, focusing on questions relevant to understanding evolution by natural selection, creation, and intelligent design. For the questions just listed, I state what I think (...) is the best available answer and show how it applies to debates about evolution and creationism. I also indicate alternative answers that are preferred by other philosophers. I hope that the result will be useful for science educators and anyone else involved in controversies about evolution and creation. (shrink)

Much of the philosophical discussion of explanations has centered around two broad conceptions of what sorts of ‘things’ explanations are – namely, the descriptive and ontic conceptions. Defenders of each argue that scientific psychology has at best little to contribute to the study of explanations. These anti-psychologistic arguments come in two main varieties, the metaphysical and the epistemic. Both varieties trace back to Hempel and recur in the more recent writings of prominent mechanists. The metaphysical arguments attempt to combat psychologism (...) about explanation by doubly dissociating explanations themselves from the commonly associated phenomenology of explanation. The epistemic arguments attempt to combat psychologism by doubly dissociating the good-making features of explanations from the CAPE. I focus on the metaphysical arguments here, for only they directly concern the nature of, as opposed to the evaluation conditions for, explanations. The metaphysical arguments are all shown to equivocate over ‘explanation’, and thus they are no threat to the proposal that sometimes explanations just are psychological events. Such arguments do, nonetheless, gesture towards something important – namely, that the CAPE is neither necessary nor sufficient for explanation in any sense. Similar considerations lead another latter-day mechanist to conclude that no phenomenology of any sort is essential for explanation. What all of these thinkers overlook, however, is that there is another important phenomenological correlate of explanation – namely, finding a happening intelligible or understanding how or why-possibly – and it may well be of the very essence of explanation, at least in the psychological sense. I propose a psychomechanistic theory of intelligibility that accounts for how we can, through finite means, make boundless, endlessly qualified inferences about the implications of our explanations. In closing I note that, although finding a happening intelligible does sometimes engender an unjustified confidence in correctness, we should not overlook how attaining this state does at least put us in a kind of epistemic base camp. I also hint at how intelligibility could turn out to be the ultimate source of the descriptive and ontic conceptions of explanation. (shrink)

Proponents of mechanistic explanation have argued that dynamical models are mere phenomenal models, in that they describe rather than explain the scientific phenomena produced by complex systems. I argue instead that dynamical models can, in fact, be explanatory. Using an example from neuroscientific research on epilepsy, I show that dynamical models can meet the explanatory demands met by mechanistic models, and as such occupy their own unique place within the space of explanatory scientific models.

The current technoscientific progress has led to a sectorization in the philosophy of science. Today the philosophy of science isn't is informal interested in studying old problems about the general characteristics of scientific practice. The interest of the philosopher of science is the study of concepts, problems and riddles of particular disciplines. Then, within this progress of philosophy of science, neuroscientific research stands out, because it invades issues traditionally addressed by the humanities, such as the nature of consciousness, action, knowledge, (...) normativity, etc. As a result, the new area of interdisciplinary study of neuroscience and philosophy arises: neurophilosophy. This emerging area applies neuroscientific concepts to traditional philosophical questions, limiting their responses to neuroscientific revelations about nervous systems. Neurophilosophy research focuses on problems related to the indirect nature of mind and brain, computational or representative analysis of brain process, relationships between psychological and neuroscientific research, adequate adaptations of physical and philosophical concepts in neuroscience and the place of cognitive functions. Now, the temporal representation of conscious experience and the types of the neural architecture to represent objects in time have aroused scientific interest. Under these interests, we focus on the studies on the temporary triadic structure of phenomenological consciousness in Dan Lloyd and Rick Grush. From Grush’s studies, the importance of Kantian ideas for cognitive neuroscience emerges, due to the active way in which Kant conceived space and time as forms of intuition, within which the mind interprets its experience. Under this perspective, the theoretical arguments of Dennett-Kinsbourne and Eagleman-Sejnowski represent winks in the direction of Kant-Husserl within the neuroscientific goal while considering that the contents provided by the mind included space, objects and perception of causal relationships. Then, theories of cognitive neuroscience are beginning to suggest that these elements are also, as Kant argued, interpretative elaborations provided by mind / brain, and not only content received from outside. In other words, current cognitive neuroscientific theories try to pass from its Humean phase to a Kantian phase. So, the challenge has been to explain that these elements are provided by the mind and the world itself, and how they have the content they have come from. These are lacking in current studies. Filling this gap helps to involve the analysis of the scientist’s experience in his theoretical attitude. In this sense, an investigation under the Kantian-Husserlian approach that involves pure intuitions a priori with the experience of the scientific and neuroscientific concepts represents a ground-breaking. At present, a neurophilosophical study about this does not exist. In this sense, one feasible proposal for research would be based on the application of neuroscientific results of Moser-Britt to philosophical problems of foundational notions in relativistic physics: space, time, space-time, field, etc., under the Kantian-Husserlian approach, which allows to demonstrate the multidisciplinary link between neurophilosophy and physics. This represents a ground-breaking area in current interests in scientific research, with a positive impact in the field of neuroscience, and contributing to the study of abstraction emphasizing the importance of Kant’s Copernican turn and Husserl’s phenomenological ideas in the construction of physical theories. -/- . (shrink)

Neuroscience and cognitive science seek to explain behavioral regularities in terms of underlying mechanisms. An important element of a mechanistic explanation is a characterization of the operations of the parts of the mechanism. The challenge in characterizing such operations is illustrated by an example from the history of physiological chemistry in which some investigators tried to characterize the internal operations in the same terms as the overall physiological system while others appealed to elemental chemistry. In order for biochemistry to become (...) successful, researchers had to identify a new level of operations involving operations over molecular groups. Existing attempts at mechanistic explanation of behavior are in a situation comparable to earlier approaches to physiological chemistry, drawing their inspiration either from overall psychology activities or from low-level neural processes. Successful mechanistic explanations of behavior require the discovery of the appropriate component operations. Such discovery is a daunting challenge but one on which success will be beneficial to both behavioral scientists and cognitive and neuroscientists. (shrink)

Ordinary Language Philosophy has largely fallen out of favour, and with it the belief in the primary importance of analyses of ordinary language for philosophical purposes. Still, in their various endeavours, philosophers not only from analytic but also from other backgrounds refer to the use and meaning of terms of interest in ordinary parlance. In doing so, they most commonly appeal to their own linguistic intuitions. Often, the appeal to individual intuitions is supplemented by reference to dictionaries. In recent times, (...) Internet search engine queries for expressions of interest have become quite popular. Apparently, philosophers attempt to surpass the limits of their own linguistic intuitions by appealing to experts or to factual uses of language. I argue that this attempt is commendable but that its execution is wanting. Instead of appealing to dictionaries or Internet queries, philosophers should employ computer-based linguistic corpora in order to confirm or falsify hypotheses about the factual use of language. This approach also has some advantages over methods employed by experimental philosophers. If the importance of ordinary language is stressed, the use of linguistic corpora is hardly avoidable. (shrink)

Distributive egalitarians believe that distributive justice is to be explained by the idea of distributive equality (DE) and that DE is of intrinsic value. The socio-relational critique argues that distributive egalitarianism does not account for the “true” value of equality, which rather lies in the idea of “equality as a substantive social value” (ESV). This paper examines the socio-relational critique and argues that it fails because – contrary to what the critique presupposes –, first, ESV is not conceptually distinct from (...) DE, and second, the idea of ESV cannot serve as a “foundation” or “root” of distributive egalitarianism. (shrink)

The use of "levels of abstraction" in philosophical analysis (levellism) has recently come under attack. In this paper, we argue that a refined version of epistemological levellism should be retained as a fundamental method, which we call the method of abstraction. After a brief introduction, in section two we make clear the nature and applicability of the (epistemological) method of levels of abstraction. In section three, we show the fruitfulness of the new method by applying it to five case studies: (...) the concept of agenthood, the Turing test, the definition of emergence, quantum observation and decidable observation. In section four, we further characterise and support the method by distinguishing it from three other forms of "levellism": (i) levels of organisation; (ii) levels of explanation and (iii) conceptual schemes. In this context, we also briefly address the problems of relativism and antirealism. In the conclusion, we indicate some of the work that lies ahead, two potential limitations of the method and some results that have already been obtained by applying the method to some long-standing philosophical problems. (shrink)

Evo-Devo exhibits a plurality of scientific “cultures” of practice and theory. When are the cultures acting—individually or collectively—in ways that actually move research forward, empirically, theoretically, and ethically? When do they become imperialistic, in the sense of excluding and subordinating other cultures? This chapter identifies six cultures – three /styles/ (mathematical modeling, mechanism, and history) and three /paradigms/ (adaptationism, structuralism, and cladism). The key assumptions standing behind, under, or within each of these cultures are explored. Characterizing the internal structure of (...) the cultures is necessary for understanding how they collaborate or compete, and how they are fragmented or integrated, in the rich interdisciplinary /trading zone/ (Galison 1997) of Evo-Devo. Evo-Devo is an important example of how science can progress through a radical plurality of perspectives and cultures. (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)

At the interface of developmental biology and evolutionary biology, the very criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena. This dissertation compares two recent research projects in which researchers jointly use the two kinds (...) of models. I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis. I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

Nature is complex, exceedingly so. A repercussion of this “complex world constraint” is that it is, in practice, impossible to connect words to the world in a foolproof manner. In this paper I explore the ways in which the complex world constraint makes vagueness, or more generally imprecision, in language in practice unavoidable, illuminates what vagueness comes to, and guides us to a sensible way of thinking about truth. Along the way we see that the problem of ceteris paribus laws (...) is exactly the problem of vagueness and susceptible to similar treatment. (shrink)

Alexander Gebharter has recently proposed to use Bayesian network causal discovery methods to identify the constitutive dependencies that underwrite mechanistic explanations. The proposal depends on using the assumptions of the causal Bayesian network framework to implicitly define mechanistic constitution as a kind of deterministic direct causal dependence. The aim of this paper is twofold. In the first half, we argue that Gebharter’s proposal incurs severe conceptual problems. In the second half, we present an alternative way to bring Bayesian network tools (...) to bear on the issue of understanding mechanistic constitution. More precisely, our proposal interprets constitution as the relation explaining why a target phenomenon has its characteristic causal role in terms of the causal roles of some of its spatiotemporal parts---where the notion of causal role is probabilistically understood. (shrink)

Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Understanding other people’s actions is called action understanding, and it can transcend differences in race, gender, culture, age, and social and historical circumstances. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual (...) information about the behavior with knowledge about the immediate and sociocultural contexts of the action and with one’s own experience. Scholars are increasingly dissatisfied with monodisciplinary approaches to understanding human action. Such one-sidedness can rest upon various motives. For example, “hermeneutic interpretations” of action understanding tend to emphasize historical and cultural influences while overlooking that ultimately such influences depend upon individual cognitive processes. This has provoked criticism of the corresponding assumption that humans are born as a “blank slate” and that culture is solely responsible for all cognitive contents. However, such critique in turn easily slides into an overemphasis on the biology of human nature and a denial of sociocultural influences on cognition (Pinker, 2003). Fortunately, recent interdisciplinary endeavors have shown that an interdisciplinary approach is preferable when investigating complex functions like action understanding. The purpose of this chapter is to propose a “mechanism-based explanation” of action understanding that will provide a theoretical framework for integrating various and often conflicting disciplinary insights. (shrink)

This paper discusses the representation and explanation of relationships between phenomena that are important in psychiatric contexts. After a general discussion of complexity in the philosophy of science, I distinguish zooming-out approaches from zooming-in approaches. Zooming-out has to do with seeing complex mental illnesses as abstract models for the purposes of both explanation and reduction. Zooming-in involves breaking complex mental illnesses into simple components and trying to explain those components independently in terms of specific causes. Connections between existing practice and (...) zooming-out are drawn, and zooming-in is criticised. (shrink)

In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be complemented (...) with semantic considerations, and in many cases, it actually should. (shrink)

The concept of technical function is a key concept to describe technical artifacts and artifacts-to-be-designed. Engineers often give such descriptions in terms of functional decomposition models, which represent relationships between functions and sets of other functions. Despite the importance of the concept of function there is no consensus among engineers about its meaning. Models of functional decomposition are likewise conceptually divergent. Although this conceptual diversity hampers information exchange between engineers, they accept and maintain it. Engineers do not, by and large, (...) engage in a focused debate to establish commonly shared functional conceptualizations. This contrasts with science where both debates on the adequacy of key conceptualizations and convergence toward shared conceptualizations are common. This book investigates the side-by-side usage of different functional decomposition models in engineering. It explains this phenomenon by applying and extending the analysis of theory choice in terms of methodological incommensurability to engineering functional decomposition, rather than to science. This analysis shows that engineers’ usage of competing functional decomposition models is rational from a practical point of view. This book furthermore investigates the communication problems that the side-by-side usage of different models engenders and presents a strategy that supports the exchange and re-use of functional information between engineers. (shrink)

Philosophical discussions of mechanisms and mechanistic explanation have often been framed by contrast to laws and deductive-nomological explanation. A more adequate conception of lawfulness and nomological necessity, emphasizing the role of modal considerations in scientific reasoning, circumvents such contrasts and enhances understanding of mechanisms and their scientific significance. The first part of the paper sketches this conception of lawfulness, drawing upon Haugeland, Lange, and Rouse. This conception emphasizes the role of lawful stability under relevant counterfactual suppositions in scientific reasoning across (...) the sciences, in place of traditional conceptions of law that are primarily confined to the physical sciences. It also extends lawful stability beyond verbally or mathematically expressed law-statements, to encompass other ways of conjoining patterns in the world with scientific pattern recognition. The remainder of this paper shows how and why mechanisms constructively exemplify this conception of lawfulness in scientific practice: • Mechanisms are robust, counterfactually stable and inductively projectible patterns, even though they are not exceptionless “laws of nature”. • Mechanistic explanations often take non-verbal forms, which consequently resist philosophical inclinations to semantic ascent, but understanding lawfulness in terms of counterfactually stable pattern recognition accounts for these ways in which scientific understanding outruns the expressive capacities of natural languages; • Mechanisms are sometimes characterized as real patterns in the world, and sometimes as epistemic representations; understanding mechanisms as modal patterns shows why both conceptions are needed, as mutually supportive. • Mechanisms are typically open-ended, and only partially specified, in ways open to and directive toward further articulation and revision. Understanding mechanisms as modal patterns incorporates this aspect of mechanistic understanding within a broader conception of scientific understanding as embedded in research practice, rather than in bodies of knowledge extracted from it. • Mechanistic explanation has often been placed on the causal side of an opposition between causal and nomological explanation, but understanding mechanisms as modal patterns helps overcome that opposition, and contributes to a pluralist conception of causal relations and their characteristic forms of counterfactual invariance. • The recognition of mechanisms as modal patterns allows for a new way to think about the relations among distinct levels of a mechanistic hierarchy, and the broader scientific significance of mechanistic understanding. (shrink)

The introduction to the volume and the overview of the idea of naturalizing the mind.

The aim of this paper lies in characterizing the explanations and models used in the field of evolutionary developmental biology throughout its history. While manipulative experiments in controlled conditions have been useful to set the bases of the discipline and are still routinely performed, this approach supposes a tension between the reliability and the representativity of the conclusions. Given the recent changes in the understanding of evolutionary phenomena, different authors currently emphasize the need of avoiding excessive simplifications in experimental approaches, (...) incorporating the complexity of the analyzed systems as a relevant trait in the study of biological diversity. On the other hand, the fragile and contingent nature of evolutionary processes and the impossibility of intervening some of these phenomena underscore the importance of non-manipulative models that allow the elucidation of how-possibly mechanisms. We argue that a pluralism characterized by the integration of different kinds of explanations, models and metaphors used in evo-devo allows to exploit their respective advantages, favours interdisciplinarity and can contribute to form a representative description of evolutionary processes without relinquishing the local and detailed study of actual mechanisms. (shrink)

Leuridan (2011) questions whether mechanisms can really replace laws at the heart of our thinking about science. In doing so, he enters a long-standing discussion about the relationship between the mech-anistic structures evident in the theories of contemporary biology and the laws of nature privileged especially in traditional empiricist traditions of the philosophy of science (see e.g. Wimsatt 1974; Bechtel and Abrahamsen 2005; Bogen 2005; Darden 2006; Glennan 1996; MDC 2000; Schaffner 1993; Tabery 2003; Weber 2005). In our view, Leuridan (...) misconstrues this discussion. His weak positive claim that mechanistic sciences appeal to generalizations is true but uninteresting. His stronger claim, that all causal claims require laws, is unsupported by his arguments. Though we proceed by criticizing Leuridan’s arguments, our greater purpose is to embellish his arguments in order to show how thinking about mechanisms enriches and transforms old philosophical debates about laws in biology and provides new insights into how generalizations afford prediction, explanation and control. (shrink)

This dissertation starts with a concise overview of what philosophers of science have written about unification and its role in scientific explanation during the last 50 years to provide the reader with some background knowledge. In order to bring unification back into the picture, I have followed two strategies, resulting respectively in Parts I and II of this dissertation. In Part I the idea of unification is used to refine and enrich the dominant causalmechanist and causal-interventionist accounts of scientific explanation. (...) In this part of the dissertation I bracket the classical ideas about unification: deduction and derivation. I do grant, for the sake of argument, that explanations are causal and argue that unification is important from within this causalist perspective. In Part II I continue my strategy of digging into scientific practice to find cases of ontological unification. But here I distance myself from the dominant literature that all explanations must be causal. I will investigate whether explanatory unification is possible in non-causal explanations. Part III contains some further reflections and conclusions. I will formulate my primary results, and I will elaborate on their implications for thinking about unification and explanation. The different forms of ontological unification were quite diverse. This relates to the method I have used. Throughout this dissertation the types of unification that were discussed emerged from digging into scientific practice. This philosophy-of-science-practice approach steered me towards a pluralistic view on unification and on explanation. In this dissertation I do not try to develop a new model of explanation and compare it to existing models. The aim is to show that there are important types of explanatory practice which cannot be properly analyzed if we neglect unification as a desideratum for explanations. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not ameliorate more (...) general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2012.

There are three main approaches to scientific explanation in the philosophical literature. The unification approach claims that science explains by fitting the particular facts and events within a general theoretical framework. The mechanistic approach claims that science explains by identifying mechanisms. According to the manipulationist approach an explanation ought to be such that it can be used to answer a “what-if-things-had-been-different question.” The article examines whether these three approaches are compatible or not in the case of the social sciences, and (...) it concludes by defending explanatory pluralism. (shrink)

Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell us about which (...) inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (shrink)

The notion of ‘causal web’ emerged in the epidemiological literature in the early Sixties and had to wait until the Nineties for a thorough critical appraisal. Famously, Nancy Krieger argued that such a notion isn’t helpful unless we specify what kind of spiders create the webs. This means, according to Krieger, (i) that the role of the spiders is to provide an explanation of the yarns of the web and (ii) that the sought spiders have to be biological and social. (...) This paper contributes to the development of the notion of causal web, elaborating on the two following points: (i) to catch the spiders we need multi-fold evidence—specifically, mechanistic and difference-making—and (ii) for the eco-social to be explanatory, the web has to be mechanistic in a sense to be specified. (shrink)

In the recent philosophical literature, two questions have arisen concerning the status of natural selection: (1) Is it a population-level phenomenon, or is it an organism-level phenomenon? (2) Is it a causal process, or is it a purely statistical summary of lower-level processes? In an earlier work (Millstein, Br J Philos Sci, 57(4):627–653, 2006), I argue that natural selection should be understood as a population-level causal process, rather than a purely statistical population-level summation of lower-level processes or as an organism-level (...) causal process. In a 2009 essay entitled “Productivity, relevance, and natural selection,” Stuart Glennan argues in reply that natural selection is produced by causal pro- cesses operating at the level of individual organisms, but he maintains that there is no causal productivity at the population level. However, there are, he claims, many population-level properties that are causally relevant to the dynamics of evolution- ary processes. Glennan’s claims rely on a causal pluralism that holds that there are two types of causes: causal production and causal relevance. Without calling into question Glennan’s causal pluralism or his claims concerning the causal relevance of natural selection, I argue that natural selection does in fact exhibit causal production at the population level. It is true that natural selection does not fit with accounts of mechanisms that involve decomposition of wholes into parts, such as Glennan’s own. However, it does fit with causal production accounts that do not require decomposition, such as Salmon’s Mark Transmission account, given the extent to which populations act as interacting “objects” in the process of natural selection. (shrink)