My response is organized into three sections. The first revisits the theme of the target article, the explanatory power of sexual selection versus social role theory. The second considers the range and scope of sexual selection, and its application to human sex differences. Two topics are examined in more detail: (1) the paternity uncertainty theory of partner violence; (2) evolution of inter-group aggression. Section 4 covers ultimate and proximal explanations and their integration within an ethological approach. I consider the development (...) of sex differences in aggression, and their causal mechanisms, within this framework. (shrink)

Philosophy of mind is, and for a long while has been, 99% metaphysics and 1% epistemology. But the fundamental question cognitive ethologists face is epistemological: what count as evidence that a creature has a mind, and if the creature does have a mind, what evidence is relevant to deciding which mental state should be attributed to it? The usual answer that cognitive ethologists give is that one’s explanation should be “conservative”. It recommends a two-part plausibility ordering: mindless is preferred (...) to minded, and first-order intentionality is preferred to second-order intentionality. I argue that the principle of conservatism is not a parsimony principle, and it doesn’t have any justification. What is needed is observational test. I also suggest a strategy for designing experiments in the future. What I offered here is a methodological version of naturalism. (shrink)

Philosophy of mind is, and for a long while has been, 99% metaphysics and 1% epistemology. Attention is lavished on the question of the nature of mind, but questions concerning how we know about minds are discussed much less thoroughly. University courses in philosophy of mind routinely devote a lot of time to dualism, logical behaviourism, the mind/brain identity theory, and functionalism. But what gets said about the kinds of evidence that help one determine what mental states, if any, an (...) individual occupies? Well, Skinner's puritanical disdain for postulating mental states gets raked over the coals, the problem of other minds gets solved by a perfunctory invocation of the principle of inference to the best explanation, and the Turing test gets discussed, mainly in order to emphasize that it can lead to mistaken answers. (shrink)

This article deals with a type of functional explanation, viability explanation, that has been overlooked in recent philosophy of science. Viability explanations relate traits of organisms and their environments in terms of what an individual needs to survive and reproduce. I show that viability explanations are neither causal nor historical and that, therefore, they should be accounted for as a distinct type of explanation.

Cognitive ethologists are in need of a good theoretical framework for attributing intentional states. Heyes and Dickinson (1990) present criteria that they claim are necessary for an intentional explanation of behavior to be justified. They suggest that questions of intentionality can only be investigated under controlled laboratory conditions and they apply their criteria to laboratory experiments to argue that the common behavior of approaching food is not intentional in most animals. We dispute the details of their argument and interpretation (...) of the laboratory experiments. While criteria such as those suggested have a role to play in comparative studies of cognition, both laboratory and field studies are important for assessing the applicability of intentional explanations across different taxa. (shrink)

Classical ethology encourages a causal approach to animal behaviour, using Tinbergen's four questions concerning evolution, function, mechanism and development of behaviour. It sets aside the study of mental processes, which could otherwise help to unify our picture of the relationships between animal and environment. Here the steps in research focused on the psychological meaning of a peculiar behaviour in the mouse — carrying its tail — and what this implies regarding the mouse's cognitive world are given. Initial empirical observations (...) suggested epistemic choices concerning space and object notions in the mouse; this led us to go beyond the first stage in exploring the significance of this behaviour. Later experiments showed the limitations of an explanation based on a cause-effect relationship. An interpretative model integrating a phenomenological conceptual framework is proposed. (shrink)

I analyze the theoretical tenets of early ethology and the criticisms leveled against it from comparative psychology. Early ethology had a clear research object, the study of behavioral adaptedness. Adaptedness was explained by the functional rules and programs that underlie the relation between a given organism and its natural environment (the function cycle). This research object was lost during the redefinition of ethology that took place after the Second World War, a redefinition that led to an emphasis (...) on physiological and evolutionary explanations instead of functional ones. This loss happened because early ethologists did not make their aims sufficiently clear and because of fundamental epistemological and semantic misunderstandings between ethologists and comparative psychologists. I argue that the behavioral explanation of adaptedness is different from both physiological and ecological research and that it needs functional concepts similar to the ones of early ethology. I defend the idea of function cycles and causal centers defined in terms of perceptual selection and behavioral response tendencies and I try to show that these functional concepts may be fruitfully combined with learning theories. I suggest calling this line of research Comparative Behavioral Ethology. (shrink)

Human technological capabilities have been analyzed as a distinctive feature of the species. However, recent discoveries in the field of ethology show that other species besides humans are also able to use and make tools. Ihde and Malafouris (2019) have suggested analyzing nonhuman animals’ technical capabilities using an enactivist framework, as they do for humans. This paper explores a pragmatist approach, combining gradual evolutionary continuity with enactivism. I will characterize nonhuman animals’ technical capacities using John Dewey’s notions of experience, (...) problematic situation, accommodation, adaptation, and inquiry. The technical capabilities of nonhuman animals are better explained in a non-dichotomic fashion, avoiding anthropocentric explanations. (shrink)

The apparent incompatibility of mental states with physical explanations has long been a concern of philosophers of psychology. This incompatibility is thought to arise from the intentionality of mental states. But, Brentano notwithstanding, intentionality is an ordinary feature of higher order behavior patterns in the classical literature of ethology.

From the Supreme Court to the bedroom, privacy is an intensely contested interest in our everyday lives and privacy law. Some people appeal to privacy to protect such critical areas as abortion, sexuality, and personal information. Yet, privacy skeptics argue that there is no such thing as a right to privacy. I argue that we cannot abandon the concept of privacy. If we wish to avoid extending this elusive concept to cover too much of our lives or shrinking it to (...) cover too little, we must come to understand it. After exploring the privacy arguments of philosophers and constitutional and tort privacy law, I argue for a new definition of privacy and an explanation of its value that clarifies and resolves many of our conflicts. Privacy is critical because it allows us to protect a realm in which we can have intimate relations with others. (shrink)

Tinbergen’s classic “On Aims and Methods of Ethology” (_Zeitschrift für Tierpsychologie, 20_, 1963) proposed four levels of explanation of behavior, which he thought would soon apply to humans. This paper discusses the need for multilevel explanation; Huxley and Mayr’s prior models, and others that followed; Tinbergen’s differences with Lorenz on “the innate”; and Mayr’s ultimate/proximate distinction. It synthesizes these approaches with nine levels of explanation in three categories: phylogeny, natural selection, and genomics (ultimate causes); maturation, sensitive (...) period effects, and routine environmental effects (intermediate causes); and hormonal/metabolic processes, neural circuitry, and eliciting stimuli (proximate causes), as a respectful extension of Tinbergen’s levels. The proposed classification supports and builds on Tinbergen’s multilevel model and Mayr’s ultimate/proximate continuum, adding intermediate causes in accord with Tinbergen’s emphasis on ontogeny. It requires no modification of Standard Evolutionary Theory or The Modern Synthesis, but shows that much that critics claim was missing was in fact part of Neo-Darwinian theory (so named by J. Mark Baldwin in _The American Naturalist_ in 1896) all along, notably reciprocal causation in ontogeny, niche construction, cultural evolution, and multilevel selection. Updates of classical examples in ethology are offered at each of the nine levels, including the neuroethological and genomic findings Tinbergen foresaw. Finally, human examples are supplied at each level, fulfilling his hope of human applications as part of the biology of behavior. This broad ethological framework empowers us to explain human behavior—eventually completely—and vindicates the idea of human nature, and of humans as a part of nature. (shrink)

Cognitive ethology is the comparative study of animal cognition from an evolutionary perspective. As a sub-discipline of biology it shares interest in questions concerning the immediate causes and development of behavior. As a part of ethology it is also concerned with questions about the function and evolution of behavior. I examine some recent work in cognitive ethology, and I argue that the notions of mental content and representation are important to enable researchers to answer questions and state (...) generalizations about the function and volution of behavior. (shrink)

How far should our realism extend? For many years philosophers of mathematics and philosophers of ethics have worked independently to address the question of how best to understand the entities apparently referred to by mathematical and ethical talk. But the similarities between their endeavours are not often emphasised. This book provides that emphasis. In particular, it focuses on two types of argumentative strategies that have been deployed in both areas. The first—debunking arguments—aims to put pressure on realism by emphasising the (...) seeming redundancy of mathematical or moral entities when it comes to explaining our judgements. In the moral realm this challenge has been made by Gilbert Harman and Sharon Street; in the mathematical realm it is known as the 'Benacerraf-Field' problem. The second strategy—indispensability arguments—aims to provide support for realism by emphasising the seeming intellectual indispensability of mathematical or moral entities, for example when constructing good explanatory theories. This strategy is associated with Quine and Putnam in mathematics and with Nicholas Sturgeon and David Enoch in ethics. Explanation in Ethics and Mathematics addresses these issues through an explicitly comparative methodology which we call the 'companions in illumination' approach. By considering how argumentative strategies in the philosophy of mathematics might apply to the philosophy of ethics, and vice versa, the papers collected here break new ground in both areas. For good measure, two further companions for illumination are also broached: the philosophy of chance and the philosophy of religion. Collectively, these comparisons light up new questions, arguments, and problems of interest to scholars interested in realism in any area. (shrink)

In this review of Allen & Bekoff's Species of Mind, underlying theoretical assumptions of cognitive ethology are examined from a biological and philosophical viewpoint. In particular, the aim of the book to constitute a foundational concept for cognitive ethology is addressed. The ambiguity of theory-of-mind approaches in animal cognition is discussed as a major problem for causal explanations in behavioural biology.

Are moral properties intellectually indispensable, and, if so, what consequences does this have for our understanding of their nature, and of our talk and knowledge of them? Are mathematical objects intellectually indispensable, and, if so, what consequences does this have for our understanding of their nature, and of our talk and knowledge of them? What similarities are there, if any, in the answers to the first two questions? Can comparison of the two cases shed light on which answers are most (...) plausible in either case? This chapter – the introduction to the volume Explanation in Ethics and Mathematics – elucidates these questions and sketches their history. (shrink)

Lorenz proposed in his (1935) articulation of a theory of behavioral instincts that the objective of ethology is to distinguish behaviors that are “innate” from behaviors that are “learned” (or “acquired”). Lorenz’s motive was to open the investigation of certain “adaptive” behaviors to evolutionary theorizing. Accordingly, since innate behaviors are “genetic”, they are open to such investigation. By Lorenz’s light an innate/acquired or learned dichotomy rested on a familiar Darwinian distinction between genes and environments. Ever since Lorenz, ascriptions of (...) innateness have become widespread in the cognitive, behavioral, and biological sciences. The trend continues despite decades of strong arguments that show, in particular, the dichotomy that Lorenz invoked in his theory of behavioral instincts is literally false: no biological trait is the product of genes alone. Some critics suggest that the failure of Lorenz’s account shows that innateness is not well-defined in biology and the practice of ascribing innateness to various biological traits should be dropped from respectable science. Elsewhere (Ariew 1996) I argued that despite the arguments of critics, there really is a biological phenomenon underlying the concept of innateness. On my view, innateness is best understood in terms of C.H. Waddington’s concept of “canalization”, i.e. the degree to which a trait is innate is the degree to which its developmental outcome is canalized. The degree to which a developmental outcome is canalized is the degree to which the developmental process is bound to produce a particular endstate despite environmental fluctuations both in the development’s initial state and during the course of development. The canalization account differs in many ways to the traditional ways that ethologists such as Konrad Lorenz originally understood the concept of innateness. Most importantly, on the canalization account the distinction between innate and acquired is not a dichotomy, as Konrad Lorenz had it, but rather a matter of degree difference that lies along a spectrum with highly canalized development outcomes on the one end and highly environmentally sensitive development outcomes on the other end. Nevertheless, I justified the canalization account on the basis of a set of desiderata or criteria that I suggested falls-out of what seemed uncontroversial about Lorenz’s account of innateness (briefly): innateness is a property of a developing individual, innateness denotes environmental stability, and innate-ascriptions are useful in certain natural selection explanations (more below). From that same set of desiderata I argued (in my 1996) that neither the concept of heritability nor of norms of reactions—two concepts from population genetics—suffice to ground innateness. In this essay, I wish to provide further support of the canalization account in two ways. First, I wish to better motivate the desiderata by revisiting a debate between Konrad Lorenz and Daniel Lehrman over the meaning and explanatory usefulness of innate ascriptions in ethology. Second, I wish to compare my canalization account of innateness with accounts proposed by contemporary philosophers, one by Stephen Stich (1975), another by Elliott Sober (forthcoming), and a third by William Wimsatt (1986). (shrink)

Machine generated contents note: Part 1 - The Constituent Disciplines of Cognitive Science -- Philosophical Epistemology -- Glossary -- 1.0 What is Philosophical Epistemology? -- 1.1 The reduced history of Philosophy Part I - The Classical Age -- 1.2 Mind and World - The problem of objectivity -- 1.3 The reduced history of Philosophy Part II - The twentieth century -- 1.4 The philosophy of Cognitive Science -- 1.5 Mind in Philosophy: summary -- 1.6 The Nolanian Framework (so far) -- (...) Psychology -- 2.0 Why is Psychology so difficult? -- 2.1 A brief history of Experimental Psychology -- 2.2 Methodologies in Psychology -- 2.3 Perception -- 2.4 Memory -- 2.5 Mind in Psychology -- Linguistics -- 3.0 Introduction -- 3.1 Why Linguistics? -- 3.2 Computation and Linguistics -- 3.3 The main grammatical theories -- 3.4 Language development and linguistics -- 3.5 Toward a definition of context -- 3.6 The multifarious uses of Language -- 3.7 Linguistics and Computational Linguistics -- 3.8 Language and other symbol systems -- 3.9 On the notion of context -- 3.10 Mind in Linguistics: summary -- Neuroscience -- 4.0 The constituent disciplines of Neuroscience -- 4.1 The methodology of Neuroscience -- 4.2 Gross Neuroanatomy -- 4.3 Some relevant findings -- 4.4 Connectionism (PDP) -- 4.5 The victory of Neuroscience? -- 4.6 Mind in Neuroscience: summary -- Artificial Intelligence -- 5.0 Introduction -- 5.1 Al and Cognitive Science -- 5.2 Skeptics and their techniques -- 5.3 Al as Computer Science -- 5.4 Al as software -- 5.5 The current methodological debate -- 5.6 Context, syntax and semantics -- 5.7 Mind in Al -- 5.8 Texts on Al -- Etholoqy and Ethnoscience -- 6.1 Etology -- 6.2 Ethnoscience -- 6.3 Mind in Ethology arid Ethnoscience -- Part II - A New Foundation for Cognitive Science -- - Symbol Systems -- 7.1 Characteristics of symbol systems -- 7.2 Context and the layers of symbol systems -- 7.3 Mind and symbol systems -- Consciousness and Selfhood -- 8.0 Introduction -- 8.1 Cognitive views -- 8.2 What is at stake? -- 8.3 Consciousness as treated in Philosophy -- 8.4 The Development of Selfhood -- 8.5 The minimal requirements for this theory -- 8.6 Self as a filter -- 8.7 Self and motivation -- 8.8 Conclusions -- 8.9 Recent developments -- Cognitive Science and the Search for Mind -- 9.1 Introduction -- 9.2 Review -- 9.3 A Theory of Mind anyone? -- 9.4 Foundational considerations -- 9.5 Coda: the Nolanian Framework. (shrink)

This feels like a time of environmental and moral crisis without parallel.... Not only do human beings seem not to believe in anything but, despite exponential advances in information production, we do not appear to know much either. This book is a guide for everyone who feels understandably perplexed. The book considers issues as diverse as: the lure of alternative religions and belief systems; the use of the rhetoric of economics to justify amoral decisionmaking; green politics and genetically-modified crops; new (...) technology's power to preserve the status quo; and the true impetus behind the Human Genome Project. Presenting an explanation of recent findings in science and their relationship with society and politics, the book seeks to give guidance towards responsible political action. Starting from themes developed in the companion volume The Search for Mind, the author attempts to provide intellectual roots for the 'anti-capitalist' or 'anti-globalization' movement and, in particular, treats social protest as a form of knowledge-seeking. The author brings to very topical and controversial concerns some much-needed clarity. Complete with reader-friendly summaries of current thought in the biological, physical, and social sciences, this book is designed primarily for the popular market but will also appeal to those working or studying in these fields. (shrink)

Table of Contents Perspectives on Animal Cognition Chapter 1 The Myth of Anthropomorphism John Andrew Fisher Chapter 2 Gendered Knowledge? Examining Influences on Scientific and Ethological Inquiries Lori Gruen Chapter 3 Interpretive Cognitive Ethology Hugh Wilder Chapter 4 Concept Attribution in Nonhuman Animals: Theoretical and Methodological Problems in Ascribing Complex Mental Processes Colin Allen and Marc Hauser Cognitive and Evolutionary Explanations Chapter 5 On Aims and Methods of Cognitive Ethology Dale Jamieson and Marc Bekoff Chapter 6 Aspects of (...) the Cognitive Ethology of an Injury-Feigning Bird, The Piping Plover Carolyn Ristau Chapter 7 Tradition in Animals: Field Observations and Laboratory Analysis Bennett G. Galef Chapter 8 The Study of Adaptation Randy Thornhill Chapter 9 The Units of Behavior in Evolutionary Explanations Sandra D. Mitchell Chapter 10 Levels of Analysis and the Functional Significance of Helping Behavior Walter D. Koenig and Ron Mumme Recognition, Choice, Vigilance, and Play Chapter 11 The Ubiquitous Concept of Recognition with Special Reference to Kin Andrew R. Blaustein and Richard H. Porter Chapter 12 Do Animals Choose Habitats? Michael Rosenzweig Chapter 13 The Influence of Models on the Interpretation of Vigilance Steven L. Lima Chapter 14 Is There an Evolutionary Biology of Play? Alex Rosenberg Chapter 15 Intentionality, Social Play, and Definition Colin Allen and Marc Bekoff Communication and Language Chapter 16 Communication and Expectations: A Social Process and the Cognitive Operation It Depends upon and Influences W. John Smith Chapter 17 Animal Communication and Social Evolution Michael Philips and Steven Austad Chapter 18 Animal Language: Methodological and Interpretive Issues Sue Savage-Rumbaugh and Karen E. Brakke Chapter 19 Knowledge Acquisition and Asymmetry between Language Comprehension and Production: Dolphins and Apes as General Models for Animals Louis M. Herman and Palmer Morrel-Samuels Animal Minds Chapter 20 Evolution and Psychological Unity Roger Crisp Chapter 21 The Mental Lives of Nonhuman Animals John Dupré Chapter 22 Inside the Mind of a Monkey Robert M. Seyfarth and Dorothy L. Cheney Chapter 23 Science and Our Inner Lives: Birds of Prey, Bats, and the Common Bi-ped Kathleen Akins Chapter 24 Afterword: Ethics and the Study of Animal Cognition. (shrink)

Lorenz proposed in his (1935) articulation of a theory of behavioral instincts that the objective of ethology is to distinguish behaviors that are “innate” from behaviors that are “learned” (or “acquired”). Lorenz’s motive was to open the investigation of certain “adaptive” behaviors to evolutionary theorizing. Accordingly, since innate behaviors are “genetic”, they are open to such investigation. By Lorenz’s light an innate/acquired or learned dichotomy rested on a familiar Darwinian distinction between genes and environments. Ever since Lorenz, ascriptions of (...) innateness have become widespread in the cognitive, behavioral, and biological sciences. The trend continues despite decades of strong arguments that show, in particular, the dichotomy that Lorenz invoked in his theory of behavioral instincts is literally false: no biological trait is the product of genes alone. Some critics suggest that the failure of Lorenz’s account shows that innateness is not well-defined in biology and the practice of ascribing innateness to various biological traits should be dropped from respectable science. Elsewhere (Ariew 1996) I argued that despite the arguments of critics, there really is a biological phenomenon underlying the concept of innateness. On my view, innateness is best understood in terms of C.H. Waddington’s concept of “canalization”, i.e. the degree to which a trait is innate is the degree to which its developmental outcome is canalized. The degree to which a developmental outcome is canalized is the degree to which the developmental process is bound to produce a particular endstate despite environmental fluctuations both in the development’s initial state and during the course of development. The canalization account differs in many ways to the traditional ways that ethologists such as Konrad Lorenz originally understood the concept of innateness. Most importantly, on the canalization account the distinction between innate and acquired is not a dichotomy, as Konrad Lorenz had it, but rather a matter of degree difference that lies along a spectrum with highly canalized development outcomes on the one end and highly environmentally sensitive development outcomes on the other end. Nevertheless, I justified the canalization account on the basis of a set of desiderata or criteria that I suggested falls-out of what seemed uncontroversial about Lorenz’s account of innateness (briefly): innateness is a property of a developing individual, innateness denotes environmental stability, and innate-ascriptions are useful in certain natural selection explanations (more below). From that same set of desiderata I argued (in my 1996) that neither the concept of heritability nor of norms of reactions—two concepts from population genetics—suffice to ground innateness. In this essay, I wish to provide further support of the canalization account in two ways. First, I wish to better motivate the desiderata by revisiting a debate between Konrad Lorenz and Daniel Lehrman over the meaning and explanatory usefulness of innate ascriptions in ethology. Second, I wish to compare my canalization account of innateness with accounts proposed by contemporary philosophers, one by Stephen Stich (1975), another by Elliott Sober (forthcoming), and a third by William Wimsatt (1986). (shrink)

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...) the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly. (shrink)

Most theories of semantic competence in natural language implicitly assume the Language of Thought Hypothesis. According to this hypothesis, all human cognition consists in the deployment of a language of thought. This language of thought is supposed to be independent of natural language, yet at the same time, it is supposed to be semantically isomorphic with natural language. Given this assumption, it is easy to answer basic questions regarding semantic competence in natural language. What are semantic properties of natural language, (...) and how did they originate? Natural language inherits the semantic properties of the language of thought it is used to express. What does semantic competence consist in? It consists in knowing how to translate items in one's language of thought into a public medium. ;The starting point of this dissertation is the rejection, by some prominent paradigms in cognitive science, of the view that human cognition consists in the deployment of a language of thought that is, at the same time, independent of natural language, yet semantically isomorphic with it. The dissertation constitutes a fledgling attempt to explore an alternative approach to explaining semantic competence in natural language, an approach that is compatible with this rejection of the Language of Thought Hypothesis. ;Rather than conceive of natural language as a tool for expressing items in a pre-existing, semantically isomorphic, language of thought, I urge that language be conceived of as a norm-governed social practice. On this view, the semantic properties of natural language are determined by the inferential norms governing linguistic performances. In order to explain the origin of its semantic properties, one must explain the origin of the inferential norms that govern language. In order to explain what semantic competence consists in, one must explain how individuals learn to abide by these inferential norms. The bulk of the dissertation is devoted to showing that neither of these explanatory projects requires endorsing the Language of Thought Hypothesis. I do this by sketching the form that such explanations might take, and showing that they are consistent with much current research in ethology, comparative psychology, developmental psychology, and evolutionary biology. (shrink)

Explanation in biology has long been characterized as being very different from explanation in other scientific disciplines, very much so from explanation in physics. One of the reasons was the existence in biology of explanation types that were unheard of in the physical sciences: teleological explanations (e.g. Hull 1974), evolutionary explanations (e.g. Mayr 1988), or even functional explanations (e.g. Neander 1991). More recently, and owing much to the rise of molecular biology, biological explanations have been depicted (...) as mechanisms (e.g; Machamer, Darden and Craver 2000). The aim of this volume is to shed some new light on the diversity of explanation types in biology. What are the different types of explanation that occur in biology? Are these types of explanation specific to particular sub-disciplines of biology, or to particular types of problems across biology? How do they relate to each another? Do they compete with one another for answering the same questions? Or do they complement each other, providing insights to different questions? What are the reasons for such diversity? Can this diversity be overcome by a broader unifying model of explanation or is it more profound and irreducible? Why? This volume aims at making sense of this diversity of types of explanations that are found in biology, of their relationship with one another. After all, explanation in biology may prove not only different from explanation in the physical sciences, but also much more diverse than originally anticipated. (shrink)

The ultimate source of explanation in biology is the principle of natural selection. Natural selection means differential reproduction of genes and gene combinations. It is a mechanistic process which accounts for the existence in living organisms of end-directed structures and processes. It is argued that teleological explanations in biology are not only acceptable but indeed indispensable. There are at least three categories of biological phenomena where teleological explanations are appropriate.

These essays are primarily concerned with the character of ethological research in the context of conflicts between animal and human interests. Specifically, to what extent is the projection into animals of human feelings a useful means to understand animal behavior? Annotation copyright Book News,.

We introduce the Relational Blockworld (RBW) as a paradigm for deflating the mysteries associated with quantum non-separability/non-locality and the measurement problem. We begin by describing how the relativity of simultaneity implies the blockworld, which has an explanatory potential subsuming both dynamical and relational explanations. It is then shown how the canonical commutation relations fundamental to non-relativistic quantum mechanics follow from the relativity of simultaneity. Therefore, quantum mechanics has at its disposal the full explanatory power of the blockworld. Quantum mechanics exploits (...) this expanded explanatory capability since event distributions among detectors per the density matrix follow from spacetime relations (symmetry group) alone. Thus, the event distributions of non-relativistic quantum mechanics follow from a blockworld wherein spacetime relations are fundamental. Per RBW "quantum mysteries" are deflated and the implications for consciousness and the perception of temporal flow and absolute becoming are explored. We conclude that given RBW, consciousness is no less fundamental than any "physical" feature of the world such as brain states. Further, active consciousness is needed to explain the illusion that it is a dynamical world and consciousness in its most fundamental state is relational and non-local. (shrink)

Science increasingly deals with human behavior: biology, neuroscience, genetics, psychology, evolutionary theory, and ethology all bring new insights into our actions and uncover new facts about our agency. However, what is the philosophical significance of their findings? The answer to this question varies according to one's background philosophical views. On the one hand, the dominant empiricist view contends that the sciences can in principle tell us everything there is to know about human agency. On the other hand, there are (...) other non-empiricist views - such as Kantian or Aristotelian perspectives - which hold that although science can contribute to our understanding of agency, agency itself cannot be reduced to mere scientific facts. This collection of original essays brings together a number of experts from different philosophical fields (history of philosophy, philosophy of action, ethics, and philosophy of science) to discuss how recent scientific developments about human behavior may be interpreted by, and may be relevant for, non-empiricist conceptions of agency. Contributors share the project of reconciling the scientific and the manifest images of the world in order to reach a stereoscopic vision of reality, with the conviction that philosophy is an attempt to establish coherence among our beliefs, while taking, at least prima facie, all the aspects of our experience at face value. (shrink)

Back cover: This book develops a philosophical account that reveals the major characteristics that make an explanation in the life sciences reductive and distinguish them from non-reductive explanations. Understanding what reductive explanations are enables one to assess the conditions under which reductive explanations are adequate and thus enhances debates about explanatory reductionism. The account of reductive explanation presented in this book has three major characteristics. First, it emerges from a critical reconstruction of the explanatory practice of the life (...) sciences itself. Second, the account is monistic since it specifies one set of criteria that apply to explanations in the life sciences in general. Finally, the account is ontic in that it traces the reductivity of an explanation back to certain relations that exist between objects in the world (such as part-whole relations and level relations), rather than to the logical relations between sentences. Beginning with a disclosure of the meta-philosophical assumptions that underlie the author’s analysis of reductive explanation, the book leads into the debate about reduction(ism) in the philosophy of biology and continues with a discussion on the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far. The author scrutinizes how the issue of reduction becomes entangled with explanation and analyzes two concepts, the concept of a biological part and the concept of a level of organization. The results of these five chapters constitute the ground on which the author bases her final chapter, developing her ontic account of reductive explanation. (shrink)

This article examines three candidate cases of non-causal explanation in computational neuroscience. I argue that there are instances of efficient coding explanation that are strongly analogous to examples of non-causal explanation in physics and biology, as presented by Batterman, Woodward, and Lange. By integrating Lange’s and Woodward’s accounts, I offer a new way to elucidate the distinction between causal and non-causal explanation, and to address concerns about the explanatory sufficiency of non-mechanistic models in neuroscience. I also (...) use this framework to shed light on the dispute over the interpretation of dynamical models of the brain. _1_ Introduction _1.1_ Efficient coding explanation in computational neuroscience _1.2_ Defining non-causal explanation _2_ Case I: Hybrid Computation _3_ Case II: The Gabor Model Revisited _4_ Case III: A Dynamical Model of Prefrontal Cortex _4.1_ A new explanation of context-dependent computation _4.2_ Causal or non-causal? _5_ Causal and Non-causal: Does the Difference Matter? (shrink)

The finding that women are attracted to men older than themselves whereas men are attracted to relatively younger women has been explained by social psychologists in terms of economic exchange rooted in traditional sex-role norms. An alternative evolutionary model suggests that males and females follow different reproductive strategies, and predicts a more complex relationship between gender and age preferences. In particular, males' preferences for relatively younger females should be minimal during early mating years, but should become more pronounced as the (...) male gets older. Young females are expected to prefer somewhat older males during their early years and to change less as they age. We briefly review relevant theory and present results of six studies testing this prediction. Study 1 finds support for this gender-differentiated prediction in age preferences expressed in personal advertisements. Study 2 supports the prediction with marriage statistics from two U.S. cities. Study 3 examines the cross-generational robustness of the phenomenon, and finds the same pattern in marriage statistics from 1923. Study 4 replicates Study 1 using matrimonial advertisements from two European countries, and from India. Study 5 finds a consistent pattern in marriages recorded from 1913 through 1939 on a small island in the Philippines. Study 6 reveals the same pattern in singles advertisements placed by financially successful American women and men. We consider the limitations of previous normative and evolutionary explanations of age preferences and discuss the advantages of expanding previous models to include the life history perspective. (shrink)

Does mathematics ever play an explanatory role in science? If so then this opens the way for scientific realists to argue for the existence of mathematical entities using inference to the best explanation. Elsewhere I have argued, using a case study involving the prime-numbered life cycles of periodical cicadas, that there are examples of indispensable mathematical explanations of purely physical phenomena. In this paper I respond to objections to this claim that have been made by various philosophers, and I (...) discuss potential future directions of research for each side in the debate over the existence of abstract mathematical objects. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of (...) complex explanations that appeal to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline (...) some promising answers that are being developed by a number of authors. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I (...) analyze a case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

It is a well-known fact that mathematics plays a crucial role in physics; in fact, it is virtually impossible to imagine contemporary physics without it. But it is questionable whether mathematical concepts could ever play such a role in psychology or philosophy. In this paper, we set out to examine a rather unobvious example of the application of topology, in the form of the theory of persons proposed by Kurt Lewin in his Principles of Topological Psychology. Our aim is to (...) show that this branch of mathematics can furnish a natural conceptual system for Gestalt psychology, in that it provides effective tools for describing global qualitative aspects of the latter’s object of investigation. We distinguish three possible ways in which mathematics can contribute to this: explanation, explication and metaphor. We hold that all three of these can be usefully characterized as throwing light on their subject matter, and argue that in each case this contrasts with the role of explanations in physics. Mathematics itself, we argue, provides something different from such explanations when applied in the field of psychology, and this is nevertheless still cognitively fruitful. (shrink)

Mathematicians distinguish between proofs that explain their results and those that merely prove. This paper explores the nature of explanatory proofs, their role in mathematical practice, and some of the reasons why philosophers should care about them. Among the questions addressed are the following: what kinds of proofs are generally explanatory (or not)? What makes a proof explanatory? Do all mathematical explanations involve proof in an essential way? Are there really such things as explanatory proofs, and if so, how do (...) they relate to the sorts of explanation encountered in philosophy of science and metaphysics? (shrink)

In this paper we argue that structural explanations are an effective way of explaining well known relativistic phenomena like length contraction and time dilation, and then try to understand how this can be possible by looking at the literature on scientific models. In particular, we ask whether and how a model like that provided by Minkowski spacetime can be said to represent the physical world, in such a way that it can successfully explain physical phenomena structurally. We conclude by claiming (...) that a partial isomorphic approach to scientific representation can supply an answer only if supplemented by a robust injection of pragmatic factors. (shrink)

Philosophers of psychology debate, among other things, which psychological models, if any, are (or provide) mechanistic explanations. This should seem a little strange given that there is rough consensus on the following two claims: 1) a mechanism is an organized collection of entities and activities that produces, underlies, or maintains a phenomenon, and 2) a mechanistic explanation describes, represents, or provides information about the mechanism producing, underlying, or maintaining the phenomenon to be explained (i.e. the explanandum phenomenon) (Bechtel and (...) Abrahamsen 2005; Craver 2007). If there is a rough consensus on what mechanisms are and that mechanistic explanations describe, represent, or provide information about them, then how is there no consensus on which psychological models are (or provide) mechanistic explanations? Surely the psychological models that are mechanistic explanations are the models that describe, represent, or provide information about mechanisms. That is true, of course; the trouble arises when determining what exactly that involves. Philosophical disagreement over which psychological models are mechanistic explanations is often disagreement about what it means to describe, represent, or provide information about a mechanism, among other things (Hochstein 2016; Levy 2013). In addition, one's position in this debate depends on a host of other seemingly arcane metaphysical issues, such as the nature of mechanisms, computational and functional properties (Piccinini 2016), and realization (Piccinini and Maley 2014), as well as the relation between models, methodologies, and explanations (Craver 2014; Levy 2013; Zednik 2015). Although I inevitably advocate a position, my primary aim in this chapter is to spell out all these relationships and canvas the positions that have been taken (or could be taken) with respect to mechanistic explanation in psychology, using dynamical systems models and cognitive models (or functional analyses) as examples. (shrink)

This article focuses on a case that expert practitioners count as an explanation: a mathematical account of Plateau’s laws for soap films. I argue that this example falls into a class of explanations that I call abstract explanations.explanations involve an appeal to a more abstract entity than the state of affairs being explained. I show that the abstract entity need not be causally relevant to the explanandum for its features to be explanatorily relevant. However, it remains unclear how to (...) unify abstract and causal explanations as instances of a single sort of thing. I conclude by examining the implications of the claim that explanations require objective dependence relations. If this claim is accepted, then there are several kinds of objective dependence relations. 1 Introduction2 A Case3 Abstract and Causal Explanations4 Recent Work on Mathematical Explanation5 Explanation and Dependence6 Conclusion. (shrink)

In this paper I apply the mechanistic account of explanation to engineering science. I discuss two ways in which this extension offers further development of the mechanistic view. First, functional individuation of mechanisms in engineering science proceeds by means of two distinct sub types of role function, behavior function and effect function, rather than role function simpliciter. Second, it offers refined assessment of the explanatory power of mechanistic explanations. It is argued that in the context of malfunction explanations of (...) technical systems, two key desiderata for mechanistic explanations, ‘completeness and specificity’ and ‘abstraction’, pull in opposite directions. I elaborate a novel explanatory desideratum to accommodate this explanatory context, dubbed ‘local specificity and global abstraction’, and further argue that it also holds for mechanistic explanations of malfunctions in the biological domain. The overall result is empirically-informed understanding of mechanistic explanation in engineering science, thus contributing to the ongoing project of understanding mechanistic explanation in novel or relatively unexplored domains. I illustrate these claims in terms of reverse engineering and malfunction explanations in engineering science. (shrink)

In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this (...) kind of explanation as a goal of dynamical cognitive science. I conclude by briefly outlining two consequences. First, dynamical cognitive science’s explanatory style may strengthen its links to the so-called “situated” approach to cognition, but, secondly, it may also undermine the widespread intuition that dynamics is related to emergentism in the philosophy of mind. (shrink)

Analysis of online mathematics forums can help reveal how explanation is used by mathematicians; we contend that this use of explanation may help to provide an informal conceptualization of simplicity. We extracted six conjectures from recent philosophical work on the occurrence and characteristics of explanation in mathematics. We then tested these conjectures against a corpus derived from online mathematical discussions. To this end, we employed two techniques, one based on indicator terms, the other on a random sample (...) of comments lacking such indicators. Our findings suggest that explanation is widespread in mathematical practice and that it occurs not only in proofs but also in other mathematical contexts. Our work also provides further evidence for the utility of empirical methods in addressing philosophical problems. (shrink)

This chapter discusses Thomas Hobbes's statements about the structure of philosophy and suggests that a focus on these reflections has led some scholars to understand Hobbes as an armchair speculative philosopher, both in his own natural‐philosophy endeavors and his well‐known criticisms of Robert Boyle and other experimental philosophers. Beyond Hobbes's statements about natural philosophy, it argues that a more complete understanding of his natural philosophy must also consider his practice of explaining in natural philosophy and optics. Hobbes divides all human (...) knowledge into two parts: scientia, and cognition. These two parts provide different levels of certainty to knowers. The chapter shows that explanations in optics and natural philosophy are ideally a mixture of appeals to everyday sense experience and Hobbes's own a priori geometry by providing two case studies: a case study from Hobbes's optics in De homine II and a case study of Hobbes's explanation of sense in De corpora XXV. (shrink)

It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques (...) of systems biologists as part of a broader practice of constructing and evaluating mechanism schemas. This argument is elaborated by considering the case of bacterial chemotactic networks, where some research has been interpreted as explaining phenomena by means of abstract design principles. (shrink)