Philosophers of science have examined The Theory of Island Biogeography by Robert MacArthur and E. O. Wilson (1967) mainly due to its important contribution to modeling in ecology, but they have not examined it as a representative case of ecological explanation. In this paper, I scrutinize the type of explanation used in this paradigmatic work of ecology. I describe the philosophy of science of MacArthur and Wilson and show that it is mechanistic. Based on this account (...) and in light of contributions to the mechanistic conception of explanation due to Craver (2007), and Bechtel and Richardson (1993), I argue that MacArthur and Wilson use a mechanistic approach to explain the species-area relationship. In light of this examination, I formulate a normative account of mechanistic explanation in ecology. Furthermore, I argue that it offers a basis for methodological unification of ecology and solves a dispute on the nature of ecology. Lastly, I show that proposals for a new paradigm of biogeography appear to maintain the norms of mechanistic explanation implicit in The Theory of Island Biogeography. (shrink)

The rise of the mechanistic worldview in the seventeenth century had a major impact on views of biological generation. Many seventeenth century naturalists rejected the old animist thesis. However, the alternative view of gradual mechanistic formation in embryology didn’t convince either. How to articulate the peculiarity of life? Researchers in the seventeenth century proposed both “animist” and mechanistic theories of life. In the eighteenth century again a controversy in biology arose regarding the explanation of generation. Some (...) adhered to the view that life is a physical property of matter (e.g. Buffon), others saw living entities as the result of the development of pre-existing germs (e.g. Bonnet). Naturalists, lacked a convincing account that could guide their research. In interaction with leading naturalists of his time Immanuel Kant articulated an approach to explaining generation. Kant’s account, delineated in his Kritik der Urteilskraft (Critique of the power of judgment) (1790), is a combination of Newtonian non-reductionist mechanism in explanation, and a concept of natural end comparable to Stahl’s formal conception of organic bodies. It consists of two claims: a) in biology only mechanical explanation is explanatory, and b) living entities contain some original organisation, which is mechanically unexplainable. In the nineteenth century this approach influenced naturalists as Müller, Virchow, and Von Baer, in their physiological research. Dissatisfied with a sheer mechanistic or, on the other hand, a sheer teleological approach, they appreciated the Kantian account of mechanical explanation of natural ends. In Germany, in the second halve of the nineteenth century, Ernst Haeckel reopened the debate about abiogenesis, which still continuous. (shrink)

There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.

When you type the word “serendipity” in a word-processor application such as Microsoft Word, the autocorrection engine suggests you choose other words like “luck” or “fate”. This correcting act turns out to be incorrect. However, it points to the reality that serendipity is not a familiar English word and can be misunderstood easily. Serendipity is a very much scientific concept as it has been found useful in numerous scientific discoveries, pharmaceutical innovations, and numerous humankind’s technical and technological advances. Therefore, there (...) have been many books written around the concept. So why do we need this additional book? This is not just another book about serendipity. It has evolved from the Editor’s question lingering for a decade after finishing his widely cited article (coauthored with Prof. Nancy K. Napier of Boise State University, ID, USA) “Serendipity as a strategic advantage?” in T. Wilkinson’s edited volume Strategic Management in the 21st Century, published by Praeger. The Editor and contributing authors have tried to achieve the following in this title. Demystifying the Serendipity Myth The phenomenon of serendipity has always been thought of as a “miracle”. It is the mystery of human innovation and one of the ultimate secrets of our society. But serendipity is not just a lucky coincidence nor any hidden conspiracy. This book explores the science of the information process behind this seemingly miraculous phenomenon. It connects human society with nature, going back to the root of our existence and looking at the flame of survival to discover the harmony in making creativity. Presenting the nuts and bolts of being an adventurer of science The authors present their conceptual investigations into serendipity’s nature and its mechanism by examining interesting real events and stories. The content is thought-provoking, and readers are led to question and explore their own life stories and problems along the journey of reading this book. Catching an elusive high-value target requires great strategies and efforts. But there are no dark secrets here because this is the “way of nature” – how we humans have always strived for innovation without realizing the blueprints behind such processes. Unlike other books on serendipity, this book will show you that a powerful “secret” is closer than you think. Delivering practical uses for different audiences By understanding the conditionality and survival drivers of serendipity, individuals or organizations can make better decisions on creating the right environment to facilitate the encounter and attainment of this valuable phenomenon. For scientists: With clear explanations of the information processes underlying serendipity, flexible theoretical frameworks of mindsponge and the 3D principle of creativity, researchers are provided with the tools they need to dig deeper into their own fields of study and find practical applications, be it psychology, economics, sociology, or anything that involves innovation (which is, in fact, every scientific discipline). For curious casual readers: Everybody needs innovation to make breakthroughs or spice up one’s life. If you think great ideas come to people randomly from an unknown fairy place, this book will convince you otherwise without taking away that awe and wonder. But above all, you will know how to become more creative, scientifically and straightforwardly, with no snake oil and no weird tricks. For ambitious business people: The flame that brought about great successes throughout human history is within you. But you can only use it if you understand it. While others wait for serendipity to come, you will be able to actively hunt for those precious moments. As it has always been: the best hunters triumph, not the passive wanderers. And in this age of information chaos, finding the golden fruits is not easy. Those from information technology know this problem well, and this book is the treasure map that they have been seeking to navigate that stormy ocean looking for jewels. Like a kingfisher tracking its prey through the water, waiting to gracefully strike, with serendipity, a person seizes the prize of creativity amid the chaos of life. ¤ ¤ ¤ Official introduction: The book explores the nature, underlying causes, and the information processing mechanism of serendipity. It proposes that natural or social survival demands drive serendipity, and serendipity is conditional on the environment and the mindset, on both individual and collective levels. From Darwin's evolution theory to Sun Tzu's war tactics, major innovations throughout human history are unified by this key concept. In the rapidly changing world, information is abundant but rather chaotic. The adaptive power of serendipity allows people to notice treasures within this wild sea, but only for those who understand how it works. To increase the probability of encountering and attaining serendipity, one should employ the mindsponge mechanism and the 3D process of creativity, for without these frameworks, serendipity is truly an elusive target. The book also discusses methods to build environments and cultures rich in navigational and useful information to maximize the chance of finding and capitalizing on serendipity. As a skill, serendipity has a resemblance to how kingfishers observe and hunt their prey. (shrink)

Borsboom and colleagues have recently proposed a “network theory” of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an “extended” network theory provide? The aim of this article is to critically examine what explanatory strategies the (...) network theory that includes both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward’s interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations. (shrink)

I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems (...) involves only weak structural constraints, is not enough to save the standard mechanistic view of computation—it trivialises the appeal to mechanism, and thus makes the account collapse into a purely functional view. I claim, however, that the objection can be put to rest once the account is appropriately amended: computational individuation is indeed functional, while mechanistic explanation plays a role in accounting for computational implementation. Since individuation and implementation are crucial elements in a satisfying account of computation in physical systems, mechanism keeps its central importance in the theory of concrete computation. Finally, I argue that my version of the mechanistic view helps to provide a convincing reply to a powerful objection against non-semantic theories of concrete computation: the argument from the multiplicity of computations. (shrink)

A mechanistic explanation is a desired outcome in many studies of perception. Such explanations require discovering the processes that contribute to the realization of a perceptual phenomenon at different levels of information processing. The present analysis aims at investigating the obstacles to develop such mechanistic explanations and their potential solutions in the context of psychopathology. Geometric-Optical Illusions (GOIs) are among perceptual phenomena that have been studied to understand psychopathology in various clinical populations. In the present analysis, the (...) GOIs will be discussed as a methodological tool in the investigation of the mechanistic approach to understanding perception in such populations. I will argue that the fact that most such studies are mainly focused on the investigation of susceptibility to GOIs can only lead to classifying such phenomena or to reporting some correlations between different aspects of such phenomena with certain brain activities, without formulating a mechanistic explanation. The investigation of the variables that mediate perceptual phenomena at earlier stages of information processing is required for the formulation of such explanations. Thus, the objective of the present analysis is twofold: 1) showing how ignoring such variables have prevented the formulation of mechanistic explanations of responses to GOIs in clinical populations, such as schizophrenia and autism, 2) analyzing the methodological aspects of an effective approach in which a top-down guidance based on phenomenological insights (the first-person data) along with the insights provided by the existing theories help overcome obstacles in developing mechanistic explanations of GOIs. (shrink)

As a promising Social Science Methodology, Structural/Mechanism Explanation (SME) retains the advantages of mechanism-based explanation (ME), particularly its focus on “identifying causal patterns from micro-level social phenomena.” It also acknowledging the role of “structure”—seen as “macro-level conditions”—in incentivizing or disincentivizing key mechanisms, thus proving valuable for forecasting their emergence and decline. This article explores the theory of SME and applies it to examine how a revitalized “Legalist political structure coupled with a Confucianist ideological structure” can forecast the (...) mechanisms by which China’s National Social Credit System disciplines and punishes the citizens. This is observed across domains of legislation, administration, judiciary, and propaganda. (shrink)

Resurgent interest in both mechanistic and counterfactual theories of explanation has led to a fair amount of discussion regarding the relative merits of these two approaches. James Woodward is currently the pre-eminent counterfactual theorist, and he criticizes the mechanists on the following grounds: Unless mechanists about explanation invoke counterfactuals, they cannot make sense of claims about causal interactions between mechanism parts or of causal explanations put forward absent knowledge of productive mechanisms. He claims that these shortfalls can (...) be offset if mechanists will just borrow key tenets of his counterfactual theory of causal claims. What mechanists must bear in mind, however, is that by pursuing this course they risk both the assimilation of the mechanistic theories of explanation into Woodward’s own favored counterfactual theory, and they risk the marginalization of mechanistic explanations to a proper subset of all explanations. An outcome more favorable to mechanists might be had by pursuing an actualist-mechanist theory of the contents of causal claims. While it may not seem obvious at first blush that such an approach is workable, even in principle, recent empirical research into causal perception, causal belief, and mechanical reasoning provides some grounds for optimism. (shrink)

There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that (...) individual models do not provide mechanistic explanations by themselves. Instead, individual models are always used to complement a huge body of background information and pre-existing models about the target system. With this in mind, I argue that mechanistic explanations are distributed across sets of different, and sometimes contradictory, scientific models. Each of these models contributes limited, but essential, information to the same mechanistic explanation, but none can be considered a mechanistic explanation in isolation of the others. (shrink)

In this article, I present a novel approach to the scientific understanding of consciousness. It is based on the hypothesis that the full range of phenomenal qualities is built into the frequency spectrum of a ubiquitous background field and proceeds on the assumption that conscious systems employ a universal mechanism by means of which they are able to extract phenomenal nuances selectively from this field. I set forth that in the form of the zero-point field (ZPF) physics can offer a (...) promising candidate that is qualified for playing the dual role as both the carrier of energy and consciousness. The appropriate mechanism, which rests upon the principle of dynamical coupling of ZPF modes, is a unique feature of quantum systems, suggesting that the dividing line between conscious and non-conscious systems is defined by the differentiation between quantum systems and classical systems. The presence of this mechanism in the brain is supported by the neurophysiological body of evidence, leading to a consistent explanation of the dynamical properties of the neural correlates of consciousness. Building on these findings, I lay the foundations for the conceptually coherent integration of consciousness into the physical worldview, derive an indicator for the quantity of consciousness of a given system, and outline the further steps toward a theory of consciousness. (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)

A new evolutionary concept is presented, based on the principle of biological diversity by organismal adaptation, more specifically the origin of the first variations and the process leading to speciation. The article suggests the mechanism of stimulation as the major promoter of genetic variation, making an overall assessment and accurate to the natural phenomenon responsible for this evolutionary step. Constantly, environmental forces interact with the organism, favoring changes to the organs toward adaptation. Stimulation focuses on this action?reaction between organism and (...) environment, trying to decipher the causes/consequences resulting. The article also addresses possible relationships and constraints with neo-Darwinism. (shrink)

The master-module theory of consciousness is considered in the light of experimental evidence that has emerged since the model was first published. It is found that these new results tend to strengthen the original hypothesis. It is also argued that the master module is involved in generation of the schemata previously postulated to be associated with consciousness . The recent discovery of attention-related activity in the thalamic intralaminar nuclei is taken to indicate that these structures constitute an important part (...) of the feedback loop which the theory conjectured to mediate thought. The theory is shown to lead to a remarkably simple rationalization of the cerebral cortex, and it offers explanations of attention, binocular rivalry and qualia. It also makes the surprising prediction that Broca's area might not exclusively serve speech. (shrink)

A thought-provoking resource detailing why causal theory is useful in geographical enquiry and how it can be developed through mechanism-based thinking. Includes a multitude of approaches and concepts in human geography today, covering important caveats, key considerations, and a synthetic approach Details contemporary geographical thought, covering theory in Marxism, poststructuralism and post-phenomenology/posthumanism, and feminism and postcolonialism Explores relationality and relational thought in contemporary human geography, plus moving towards a relational theory for the 2020s and beyond Discusses mechanism (...) and process in causal explanation, covering causal theory and actors, neoliberalization, and the process-mechanism distinction of neoliberalism Essential reading for academics, geographers, and scholars seeking unique perspective on an important facet of the field. (shrink)

Philosophical accounts of scientific explanation are broadly divided into ontic and epistemic views. This paper explores the idea that the lexical ambiguity of the verb to explain and its nominalisation supports an ontic conception of explanation (Salmon 1989; Craver 2007). I analyse one argument which challenges this strategy by criticising the claim that explanatory talk is lexically ambiguous (Wright, European Journal of Philosophy of Science 2(3), 375–394, 2012). I propose that the linguistic mechanism of transfer of meaning (Nunberg, (...) Journal of Semantics 12(2), 109–132, 1995) provides a better account of the lexical alternations that figure in the systematic polysemy of explanatory talk, and evaluate the implications of this proposal for the debate between ontic and epistemic conceptions of scientific explanation. (shrink)

Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological (...) explanations and then explains why topological explanations and mechanisms are different in principle. Then it shows that they are pervasive both in the study of networks—whose importance has been increasingly acknowledged at each level of the biological hierarchy—and in contexts where the notion of selective neutrality is crucial; this allows me to capture the difference between mechanisms and topological explanations in terms of practical modelling practices. The rest of the paper investigates how in practice mechanisms and topologies are combined. They may be articulated in theoretical structures and explanatory strategies, first through a relation of constraint, second in interlevel theories, or they may condition each other. Finally, I explore how a particular model can integrate mechanistic informations, by focusing on the recent practice of merging networks in ecology and its consequences upon multiscale modelling. (shrink)

Abstract“Selfish” gene theories have offered invaluable insight into eukaryotic genome evolution, but they can also be misleading. The “selfish mitochondrion” hypothesis, developed in the 90s explained uniparental organelle inheritance as a mechanism of conflict resolution, improving cooperation between genetically distinct compartments of the cell. But modern population genetic models provided a more general explanation for uniparental inheritance based on mutational variance redistribution, modulating the efficiency of both purifying and adaptive selection. Nevertheless, as reviewed here, “selfish” conflict theories still dominate (...) the literature. While these hypotheses are rich in metaphor and highly intuitive, selective focus on only one type of mitochondrial mutation limits the generality of our understanding and hinders progress in mito‐nuclear evolution theory. Recognizing that uniparental inheritance may have evolved—and is maintained across the eukaryotic tree of life—because of its influence on mutational variance and improved selection will only increase the generality of our evolutionary reasoning, retaining “selfish” conflict explanations as a special case of a much broader theory. (shrink)

In the previous issue of Analyse & Kritik (2020, vol. 42, issue 1) Alexander Vostroknutov (3-39) aims at a ‘synthesis’ of economics with ‘psychology, sociology, and evolutionary human biology.’ This paper argues that his approach needs to be complemented at least by work from sociologists and social psychologists. Starting with problems of defining and measuring norms it is then claimed that a theory of norms should address the origin, change and effects of norms and model micromacro processes. This should (...) also be the goal of a theory of institutions (which are defined here as sets of norms-norms in the sense of accepting oughtness statements). We show how the social psychological value expectancy theory can be applied to model the variety of incentives that could play a role in explaining the effects of norms. Regarding the origin Coleman’s theory of norms is applied to show how Vostroknutov’s dissatisfaction-norms hypothesis can be improved. (shrink)

De Vries' mutation theory has not stood the test of time. The supposed mutations of Oenothera were in reality complex recombination phenomena, ultimately explicable in Mendelian terms, while instances of large-scale mutations were found wanting in other species. By 1915 the mutation theory had begun to lose its grip on the biological community; by de Vries' death in 1935 it was almost completely abandoned. Yet, as we have seen, during the first decade of the present century it achieved (...) an enormous popularity. As this paper has tried to suggest, one of the principal reasons for this was that de Vries' theory served as a banner around which a whole crowd of disaffected Darwinians or anti-Darwinians could rally. However, not all of those who favored de Vries did so for quite the same reasons. Underlying the multitude of views ran several common threads: a dissatisfaction with current Darwinian theory born out of misunderstanding natural selection, a general misunderstanding of the nature of species, and a prejudice against speculative, nontestable theories in biology.Supporters of de Vries were not the only opponents of Darwinism, nor was the mutation theory the only alternative to natural selection. In the early twentieth century a number of theories had been proposed to explain away the problems which Darwin had left unsolved. There was the idea of orthogenesis, championed by the American paleontologists Cope, Osborn and others; organic selection (or orthoplasy) was championed by M. M. Baldwin and C. Lloyd Morgan; there were the concepts of convergent evolution proposed by Hermann Friedmann, the theory of physiological selection by John George Romanes, and the concepts of reproductive divergence by H. M. Vernon. Virtually none of these men either accepted or were strong supporters of the de Vriesian theory, for each had his own particular ‘ism” to advocate as the major factor in evolution. The existence of a large number of such theories, each purporting to be the explanation, was characteristic of evolutionary theory at the turn of the century. It is to a large extent the emphasis on such fragmentary concepts that retarded development of the comprehensive theory of evolution which emerged in the 1920's and 1930's. For the historian, however, a study of these alternative theories is instructive in trying to understand the inherent difficulties which Dawwinian theory posed to biologists at the time. De Vries' mutation theory serves historically as a mirror to reflect the critical mood of a generation hostile to the theory of natural selection.It has often been claimed that it was impossible to understand the mechanism of natural selection until it could be placed in genetic and mathematical terms. It is certainly true that great strides have been made in population genetics and the treatment of evolutionary concepts with mathematical tools in the last forty years. But the very people who developed the genetical and mathematical approach to evolution were already convinced of the essential correctness of Darwinian theory before they started. Advances in an understanding of Mendelian heredity aided greatly in solving one important issue for evolutionists: the origin of variations. And the rigor with which selection acted could best be studied by observing changes in gene frequencies (calculated mathematically) over a number of generations. But as this paper has shown, two of the basic problems which biologists faced in evaluating Darwinian theory at the turn of the century-the nature of species, and the criteria of what constituted an acceptable explanation in biological science-could not be answered directly by mathematics. What mathematical and genetical theory did do was to help convince the skeptics of the validity of the Darwinian proposition.The change in explanatory criteria which many hailed as de Vries' most important contribution to evolutionary theory seems to have been part of a general emergence of twentieth-century biology from the domination of theorizers in the nineteenth. It also marked the emergence of America from the domination of biological, and particularly evolutionary, influence of Europeans. The change occurred in three areas: in the kinds of questions asked: testable versus non-testable; in the kind of data sought: quantitative versus qualitative; and in the kinds of theories proposed: analytical and reductive—the attempt to see complex processes in terms of simpler components-as opposed to synthetic and speculative. Although ultimately wrong in his idea, de Vries and his theories rode high on the wave of “experimentalism” which was the harbinger of a new era in evolutionary theory. (shrink)

Upshot: The computational theory of mind has been elaborated in many different ways throughout the last decades. In Explaining the Computational Mind, Milkowski defends his view that the mind can be explained as computational through his defense of mechanistic explanation. At no point in this book is there explicit mention of constructivist approaches to this topic. We will, nevertheless, argue that it is interesting for constructivist readers.

The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory (...) subscribes to the same theses of the dynamical hypothesis and that it affords covering-law explanations. This however exposes the theory to the mere description worry and generates a puzzle about the role of representations. I then argue that the sensorimotor theory is compatible with a mechanistic framework, and show how this can overcome the mere description worry and solve the problem of the explanatory role of representations. By doing so, it will be shown that the theory should be understood as an enrichment of the orthodoxy, rather than an alternative. (shrink)

The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. (...) Therefore, contemporary dynamicist research reveals the need for a more sophisticated account of mechanistic explanation. (shrink)

One of the most important contributions of Einstein to the philosophy of science is the distinction between two types of scientific theories: ‘principle’ and ‘constructive’ theories. More recently, Flores proposed a more general distinction, classifying scientific theories by their functional role into ‘framework’ and ‘interaction’ theories, attempting to solve some inadequacies in Einstein’s proposal. Here, based on an epistemic criterion, we present a generalised distinction which is an improvement over Flores approach. In this work (i) we evaluate the shortcomings related (...) to Flores’s proposal, (ii) we present an epistemological criterion that opens the door for a more general classification of any scientific theory in all of the natural science into two distinct groups, which we call ‘mechanistic theories’ and ‘structural theories’, and (iii) we show that such a criterion is connected to Flores’ proposal while overcoming issues of all previous approaches. (shrink)

This paper argues that there is no single universal conception of scientific explanation that is consistently employed throughout the whole domain of Higgs physics—ranging from the successful experimental search for a standard model Higgs particle and the hitherto unsuccessful searches for any particles beyond the standard model, to phenomenological model builders in the Higgs sector and theoretical physicists interested in how the core principles of quantum field theory apply to spontaneous symmetry breaking and the Higgs mechanism. Yet the (...) coexistence of deductive-statistical, unificationist, model-based, and statistical-relevance explanations does not amount to a fragmentation of the discipline, but allows elementary particle physicists to simultaneously pursue a plurality of research strategies and keep the field together by joint convictions about the SM and shared explanatory ideals. These convictions include that the SM both represents a successful explanation of the available particle data and contains aspects in need of further explanation. Especially in the domain of BSM physics, explanatory ideals typically appear as stories motivating the different models and linking them to the whole of the discipline. (shrink)

If the decades of the forties through the sixties were dominated by discussion of Hempel's “covering law“ explication of explanation, that of the seventies was preoccupied with Salmon's “statistical relevance” conception, which emerged as the principal alternative to Hempel's enormously influential account. Readers of Wesley C. Salmon's Scientific Explanation and the Causal Structure of the World, therefore, ought to find it refreshing to discover that its author has not remained content with a facile defense of his previous investigations; (...) on the contrary, Salmon offers an original account of different kinds of explications, advances additional criticisms of various alternative theories, and elaborates a novel “two-tiered“ analysis of explanation that tacitly depends upon a “two-tiered” account of homogeneity. Indeed, if the considerations that follow are correct, Salmon has not merely refined his statistical relevance account but has actually abandoned it in favor of a “causal/mechanistic“ construction. This striking development suggests that the theory of explanation is likely to remain as lively an arena of debate in the eighties as it has been in the past. (shrink)

Van Fraassen explains rejections and asymmetries in science in terms of his contextual theory of explanation in the same way that scientists explain observable phenomena in the world in terms of scientific theories. I object that van Fraassen’s skeptical view regarding inference to the best explanation together with the English view of rationality jointly imply that the contextual theory is not rationally compelling, so van Fraassen and his epistemic colleagues can rationally disbelieve it. Prasetya replies that (...) the truth of the contextual theory coincides with its empirical adequacy, so the contextual theory is compelling. He also replies that the contextual theory is compelling, provided that van Fraassen’s argument for it instantiates a compelling subset of IBE. I argue that Prasetya’s replies either fail or help scientific realism. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content (...) about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient (e.g., mental) properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

Two welcome extensions of evolutionary thinking have come to prominence over the last thirty years: the so-called ’extended evolutionary synthesis’ (EES) and debate about biological kinds and individuals. These two agendas have, however, remained orthogonal to one another. The EES has mostly restricted itself to widening the explanations of adaptation offered by the preceding ’modern evolutionary synthesis’ by including additional mechanisms of inheritance and variation; while discussion of biological kinds has turned toward philosophical questions of essential vs. contingent properties of (...) life forms and realist vs. epistemological approaches to categorization and classification. Here we attempt to broaden the explanatory scope of evolutionary theory by linking these two agendas. We expand on the mechanistic orientation of the EES, using new understandings of networked systems of components in order to engage the distinct intellectual challenge of the origination of “historical kinds”. With this phrase we designate a subset of natural kinds that acquires, through evolutionary processes, a quasi-independent lineage-history. Such kinds emerge in both biology and culture, and we enlarge the limited number of historical kinds that have thus far been recognized in evolutionary biology in a series of paradigmatic exemplars, from genes and cell types to rituals and music. For each exemplar we discern specific mechanisms by which it arose and persists; comparing these, we suggest a general unity in the ways in which diverse historical kinds originate. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content (...) about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

In this paper, I discuss the differences between ontic and epistemic conceptions of scientific explanation, mainly in relation to the so-called new mechanical philosophy. I emphasize that the debate on conceptions of scientific explanation owes much to Salmon’s ontic/epistemic distinction, although much has changed since his formulations. I focus on the interplay between ontic and epistemic norms and constraints in providing mechanistic explanations. My conceptual analysis serves two aims. Firstly, I formulate some suggestions for recognising that both (...) sets of norms and constraints, ontic and epistemic, are necessary for scientific theorising. Secondly, I emphasize that there are multiple dimensions involved in scientific explanation, rather than clear-cut alternatives between ontic and epistemic aspects. I conclude with a general observation that although contextual aspects of explanations are unavoidable, the epistemic-relativity of our categories, explanations and models can in fact be compatible with their objectivity. Instead of making hastily drawn ontological implications from our theories or models, we should carefully scrutinize them from the ontic-epistemic perspective. (shrink)

This paper argues that in some explanations mathematics are playing an explanatory rather than a representational role, and that this feature unifies many types of non-causal or non-mechanistic explanations that some philosophers of science have been recently exploring under various names. After showing how mathematics can play either a representational or an explanatory role by considering two alternative explanations of a same biological pattern—“Bergmann’s rule”—I offer an example of an explanation where the bulk of the explanatory job is (...) done by a mathematical theorem, and where mechanisms involved in the target systems are not explanatorily relevant. Then I account for the way mathematical properties may function in an explanatory way within an explanation by arguing that some mathematical propositions involving variables non directly referring to the target system features constitute constraints to which a whole class of systems should comply, provided they are describable by a mathematical object concerned by those propositions. According to such “constraint account”, those mathematical facts are directly entailing the explanandum, as a consequence of such constraints. I call those explanations “structural”, because here properties of mathematical structures are accounting for the explanandum; various kinds of mathematical structures thereby define various types of structural explanations. (shrink)

This paper discusses the prospect of the "new social history" guided by the recent work of Charles Tilly on the methodology of social and historical explanation. Tilly advocates explanation by mechanisms as the alternative to the covering law explanation. Tilly's proposals are considered to be the attempt to reshape the practices of social and historical explanation following the example set by the explanatory practices of molecular biology, neurobiology, and other recent "success stories" in the life sciences. (...) Recent work in the philosophy of science on these practices by Peter Machamer, Lindley Darden, Carl Craver and others is used as the foil to disclose the difficulties of Tilly's project. Most important among them is the dilemma of specification: if diagrams (standard forms of the representation of mechanisms) are intended as representations of robust causal processes, they cannot be specific enough to provide complete mechanism schemata, and are bound to remain mechanism sketches. If mechanism sketches are elaborated in detail by tracing particular causal processes, they provide representations of fragile causal processes, which cannot be considered as mechanisms comparable to those in advanced life and other special sciences. Tilly's work on the explanation of mechanisms can be considered as symptomatic for the recent trend to visualize the forms of historical representation. As far as diagrams seem to be able to communicate stories in a direct way (without narrative discourse), this trend is a challenge for the theory of historical representation. The new theories of scientific explanation focusing on the explanatory practices of the life sciences can provide examples and be the source of inspiration for the work on the theory of historical and social explanation, going beyond the confines of the received framework of the covering law model of explanation. (shrink)

Cognitive science, as an interdisciplinary research endeavour, seeks to explain mental activities such as reasoning, remembering, language use, and problem solving, and the explanations it advances commonly involve descriptions of the mechanisms responsible for these activities. Cognitive mechanisms are distinguished from the mechanisms invoked in other domains of biology by involving the processing of information. Many of the philosophical issues discussed in the context of cognitive science involve the nature of information processing. For philosophy of science, a central question is (...) what counts as a scientific explanation. But what is a mechanistic explanation and how does it work, how can philosophy of science use it as a solution for the problem of integration in cognitive science? By answering these questions and merging my answers with discussion of concepts of philosophy, normativity and generality, I will investigate the following claim. -/- I claim that philosophy by using strength concepts such as normativity, generality, and a mechanistic philosophy of explanations, can be a most important contributor to cognitive science. I also investigate how philosophy of science could be (can be) a bridge between psychology and neuroscience. We need a distinction between philosophy of cognitive science and philosophy in cognitive science; I am talking about the latter. -/- This claim is very important for the integration and the future of the interdisciplinary field known as cognitive science. -/- Philosophy as a true cognitive science -/- When the Cognitive Science Society was founded, in the late 1970s, philosophy, neuroscience, and anthropology were playing smaller roles. The three disciplines that formed the core group were artificial intelligence, psychology, and linguistics. The curious thing is that George Miller, a psychologist and an important founder of cognitive sciences in a hexagon diagram that he presented, put philosophy at the top of the diagram and neuroscience at the very bottom. There is enough agreement now that neuroscience is the most important contributor to cognitive science and there are fair connections between philosophy and neuroscience. In that diagram there was almost no connection between philosophy and neuroscience. -/- The developments and rise of cognitive science in the last half-century has been accompanied by considerable amount of philosophical activity. Perhaps no other area within analytic philosophy in the second half of that period has attracted more attention or produced more publications. (Bechtel and Graham, 1998. Rumelhart and Bly 1999. Bechtel, Mandik, Mundale 2001. Thagard, 2007. Bennett and Dennett et al, 2007. Bennett and Hacker, 2008. Andler, 2009. Frankish and Ramsey, 2012.) -/- Many philosophers of science offer conclusions that have a direct bearing on cognitive science and its practitioners can profit from closer engagement with the rest of cognitive science. For example, William Bechtel has discussed three projects, two in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years, that he contends, can make theoretical and methodological contributions to cognitive science (Bechtel, 2009). Paul Thagard is another example of the mentioned emerging school of philosophers of science that define cognitive science as the interdisciplinary investigation of mind and intelligence (Thagard, 2006). Thagard by presenting some general but important philosophical questions such as, “What is the nature of the explanations and theories developed in cognitive science?”, and by providing answers to these central questions has showed how philosophy of science can help cognitive science by the advantage of its generality. Andrew Brook, however, believes that philosophical approaches have never had a settled place in cognitive science but he is listed in a group of the philosophers of science that they are contributing very closely the cognitive science (Brook, 2009). Daniel Dennett , as well as being a member the mentioned naturalistic philosophers of science, believes that there is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science. -/- What are mechanisms? Let us begin abstractly before considering an example. Mechanisms are collections of entities and activities organized together to do something (cf. Machamer, Darden, & Craver, 2000; Craver & Darden, 2001; Bechtel &Richardson, 1993; Glennan, 1996). These explanations are known as ‘mechanistic explanations’. By using and developing these mechanistic explanations of philosophy of science one can draw normative consequences for cognitive science. Paul Thagard (Thagard, 2006 and 2009), William Bechtel (Bechtel, 2008 and 2009), Andrew Brook (Brook, 2008) investigated and promoted using the ‘normativity’ in philosophy to show a better and crucial role for philosophy of science in an interdisciplinary known as cognitive science. Some philosophers have thought that, in order to pursue this normative function, philosophy must distance itself from empirical matters, but there are examples where the investigations of descriptive and normative issues go hand in hand. ( Thagard, 2009). -/- I will investigate how we can reduce a higher-level science such as psychology to neuroscience without the problems of reductionism but via mechanistic explanations. By problem I mean psychology does not lose its autonomy. -/- Conclusion -/- If cognitive science is all about understanding the human mind, or if cognitive science is the interdisciplinary investigation of mind and intelligence, since the whole life of philosophy was involving with the ways of knowing (epistemology) and conceptions of reality (metaphysics), also philosophy has considered the so-called mind-body problem ( identity theory, functionalism, and heuristic identity theory) , then philosophy could be the most deserved discipline to be a most contributor in cognitive science. I tried to discuss this by using the three advantages in philosophy, normativity, and generality and by introducing an emerging school of mechanistic (not mechanical) philosophers. One thing left, as cognitive science is a two-way street, philosophers need also to stop in a station of cognitive science and learn from the most important advances in brain and neuroscience. -/- . (shrink)

The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by (...) computer simulations and mathematical representations in the epistemic practices of mechanism discovery and mechanism description. These examples also indicate that the scope of mechanistic explanation must be re-examined: With new and increasingly powerful methods of discovery and description comes the possibility of describing mechanisms far more complex than traditionally assumed. (shrink)

Intentionalism is a research program that seeks to explain facts about meaning and communication in psychological terms, with our capacity for intention recognition playing a starring role. My aim here is to recommend a methodological reorientation in this program. Instead of a focus on intuitive counterexamples to proposals about necessary-and-sufficient conditions, we should aim to investigate the psychological mechanisms whose activities and interactions explain our capacity to communicate. Taking this methodologi- cal reorientation to heart, I sketch a theory of (...) the cognitive architecture underlying language use that I have defended elsewhere. I then show how this theory can be used to give an account of non-communicative language use—a phenomenon that has long posed a challenge to intentionalism. (shrink)

The sexual revolution that took place in the late 1960s and early 1970s is one of the most profound social changes during the second half of the twentieth century in America. Before the revolution, there existed a norm proscribing premarital sex (PS norm); premarital sex was not accepted. After the sexual revolution, the PS norm no longer existed; premarital sex became accepted. In the literature on how premarital sex became accepted, little attention is given to the institutional change that transpired—the (...) collapse of a sexual norm. This study specifies one micro-mechanism of this social change. Specifically, adopting methodological individualism and the prisoner's dilemma game, I develop a theory that explains how a technological innovation for contraception triggered a change in individuals' perception of premarital sex, which led to their behavioral change. As a result, premarital sex became accepted, and the norm proscribing premarital sex collapsed. I use General Social Survey data to test the hypothesized micro-mechanism of the institutional change. The empirical analysis supports the hypothesis derived from the theory. Based on the above analyses, I discuss two alternative explanations and the issue of teenage pregnancy. (shrink)

According to the computational theory of mind (CTM), mental capacities are explained by inner computations, which in biological organisms are realized in the brain. Computational explanation is so popular and entrenched that it’s common for scientists and philosophers to assume CTM without argument.

In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation (CTE) captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and (...) the explanans. I support this claim by illustrating that CTE is applicable to Euler’s explanation (an example of a non-causal scientific explanation) and Loewer’s explanation (an example of a non-causal metaphysical explanation). (shrink)

In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the (...) explanans. I support this claim by illustrating that CTE is applicable to Euler’s explanation and Loewer’s explanation. (shrink)

Some 20 years ago Todd and colleagues proposed that rhythm perception is mediated by the conjunction of a sensory representation of the auditory input and a motor representation of the body (Todd, 1994a, 1995 ), and that a sense of motion from sound is mediated by the vestibular system (Todd, 1992a, 1993b ). These ideas were developed into a sensory-motor theory of rhythm and beat induction (Todd et al., 1999 ). A neurological substrate was proposed which might form the (...) biological basis of the theory (Todd et al., 2002 ). The theory was implemented as a computational model and a number of experiments conducted to test it. In the following time there have been several key developments. One is the demonstration that the vestibular system is primal to rhythm perception, and in related work several experiments have provided further evidence that rhythm perception is body dependent. Another is independent advances in imaging, which have revealed the brain areas associated with both vestibular processing and rhythm perception. A third is the finding that vestibular receptors contribute to auditory evoked potentials (Todd et al., 2014a, b ). These behavioral and neurobiological developments demand a theoretical overview which could provide a new synthesis over the domain of rhythm perception. In this paper we suggest four propositions as the basis for such a synthesis. (1) Rhythm perception is a form of vestibular perception; (2) Rhythm perception evokes both external and internal guidance of somatotopic representations; (3) A link from the limbic system to the internal guidance pathway mediates the “dance habit”; (4) The vestibular reward mechanism is innate. The new synthesis provides an explanation for a number of phenomena not often considered by rhythm researchers. We discuss these along with possible computational implementations and alternative models and propose a number of new directions for future research. (shrink)

The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7–12 month-old-infants. In Piaget's classic “A-not-B error,” infants who have successfully uncovered a toy at location “A” continue to reach to that location even after they watch the toy hidden in a nearby location “B.” Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects (...) or other static mental structures. Instead, we demonstrate that the A-not-B error and its previously puzzling contextual variations can be understood by the coupled dynamics of the ordinary processes of goal-directed actions: looking, planning, reaching, and remembering. We offer a formal dynamic theory and model based on cognitive embodiment that both simulates the known A-not-B effects and offers novel predictions that match new experimental results. The demonstration supports an embodied view by casting the mental events involved in perception, planning, deciding, and remembering in the same analogic dynamic language as that used to describe bodily movement, so that they may be continuously meshed. We maintain that this mesh is a pre-eminently cognitive act of “knowing” not only in infancy but also in everyday activities throughout the life span. Key Words: cognitive development; dynamical systems theory; embodied cognition; infant development; motor control; motor planning; perception and action. (shrink)

Inference to the Best Explanation is usually employed in the Scientific Realism debates. As far as particular scientific theories are concerned, its most ready usage seems to be that of a theory of confirmation. There are however more uses of IBE, namely as an epistemological theory of testimony and as a means of categorising and justifying the sources of evidence. In this paper, I will present, develop and exemplify IBE as a theory of the quality of (...) evidence - taking examples from medicine and showing that IBE can thereby provide the epistemological underpinning and justify the criteria of grading quality of mechanistic evidence that have been recently provided in the Clarke et al. paper on how evidence of medical mechanisms is to be construed alongside population studies. (shrink)

The easy problems of consciousness are those that seem directly susceptible to the standard methods of cognitive science, whereby a phenomenon is explained in terms of computational or neural mechanisms. The hard problems are those that seem to resist those methods. The easy problems are easy precisely because they concern the explanation of cognitive abilities and functions. Once we have specified the neural or computational mechanism that performs the function of verbal report, for example, the bulk of our work (...) in explaining reportability is over. Baars theory of cognitive accessibility addresses many aspects of human cognition and shows promise as a theory of awareness, the functional correlate of conscious experience, but an explanation of experience itself is not on offer. The key is the conceptual point that the explanation of functions does not suffice for the explanation of experience. (shrink)

In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal models, showing that Woodward and Rescorla conflate these problems. Finally, we (...) argue that the temptation to pit mechanistic and interventionist theories of explanation against one another occludes important and scientifically relevant research questions. (shrink)

The Einstellung effect occurs when the first idea that comes to mind, triggered by familiar features of a problem, prevents a better solution being found. It has been shown to affect both people facing novel problems and experts within their field of expertise. We show that it works by influencing mechanisms that determine what information is attended to. Having found one solution, expert chess players reported that they were looking for a better one. But their eye movements showed that they (...) continued to look at features of the problem related to the solution they had already thought of. The mechanism which allows the first schema activated by familiar aspects of a problem to control the subsequent direction of attention may contribute to a wide range of biases both in everyday and expert thought - from confirmation bias in hypothesis testing to the tendency of scientists to ignore results that do not fit their favoured theories. (shrink)

P. Kitcher's unification theory of explanation appears to endorse a reductionistic view of scientific explanation that is inconsistant with scientific practice. In this paper, I argue that this appearance is illusory. The existence of multiply realizable generalizations enable the unification theory to also count many high-level accounts as explanatory.

Introduction: One of the most influential theories of scientific explanation to have emerged in the past two decades is Salmon's causal/mechanical theory (Salmon 1984). According to this account, scientific explanations describe a network of causal processes and interactions. In this paper, I will use an example from evolutionary biology to argue that the causal nexus, as characterized by Salmon, is not rich enough to account for many causal explanations in the sciences.