One of the central aims of science is explanation: scientists seek to uncover why things happen the way they do. This chapter addresses what kinds of explanations are formulated in biology, how explanatory aims influence other features of the field of biology, and the implications of all of this for biology education. Philosophical treatments of scientific explanation have been both complicated and enriched by attention to explanatory strategies in biology. Most basically, whereas traditional philosophy (...) of science based explanation on derivation from scientific laws, there are many biological explanations in which laws play little or no role. Instead, the field of biology is a natural place to turn for support for the idea that causal information is explanatory. Biology has also been used to motivate mechanistic accounts of explanation, as well as criticisms of that approach. Ultimately, the most pressing issue about explanation in biology may be how to account for the wide range of explanatory styles encountered in the field. This issue is crucial, for the aims of biological explanation influence a variety of other features of the field of biology. Explanatory aims account for the continued neglect of some central causal factors, a neglect that would otherwise be mysterious. This is linked to the persistent use of models like evolutionary game theory and population genetic models, models that are simplified to the point of unreality. These explanatory aims also offer a way to interpret many biologists’ total commitment to one or another methodological approach, and the intense disagreements that result. In my view, such debates are better understood as arising not from different theoretical commitments, but commitments to different explanatory projects. Biology education would thus be enriched by attending to approaches to biological explanation, as well as the unexpected ways that these explanatory aims influence other features of biology. I suggest five lessons for teaching about explanation in biology that follow from the considerations of this chapter. (shrink)

The new mechanists and the autonomy approach both aim to account for how biological phenomena are explained. One identifies appeals to how components of a mechanism are organized so that their activities produce a phenomenon. The other directs attention towards the whole organism and focuses on how it achieves self-maintenance. This paper discusses challenges each confronts and how each could benefit from collaboration with the other: the new mechanistic framework can gain by taking into account what happens outside individual mechanisms, (...) while the autonomy approach can ground itself in biological research into how the actual components constituting an autonomous system interact and contribute in different ways to realize and maintain the system. To press the case that these two traditions should be constructively integrated we describe how three recent developments in the autonomy tradition together provide a bridge between the two traditions: (1) a framework of work and constraints, (2) a conception of function grounded in the organization of an autonomous system, and (3) a focus on control. (shrink)

Inequalities of social goods between gender, racial, or other groups call out for explanation. Such inequalities might be explained by socialization and discrimination. But historically some have attributed these inequalities to biological differences between social groups. Such explanations are highly controversial: on the one hand, they have a very troubling racist and sexist history, but on the other hand, they are empirical claims, and so it seems inappropriate to rule them out a priori. I propose that the appropriate epistemic (...) attitude toward biological explanations of social inequalities is a general but defeasible skepticism. I then turn to the appropriate moral attitude, arguing that when such explanations are inadequately supported, they are offensive. (shrink)

The aim of this paper is to show that critics of biological explanations of human nature may be granting too much to those who propose such explanations when they argue that the truth of genetic determinism implies an end to critical evaluation and reform of our social institutions. This is the case because when we argue that biological determinism exempts us from social critique we are erroneously presupposing that our social values, practices, and institutions have nothing to do with what (...) makes biological explanations troublesome. My argument is that what constitutes a problem for those who are concerned with social justice is not the fact that particular behaviours may be genetically determined, but the fact that our value system and social institutions create the conditions that make such behaviours problematic. Thus, I will argue that even if genetic determinism were correct, the requirement of assessing and transforming our social practices and institutions would be far from superfluous. Biology is rarely destiny for human beings and the institutions they create. (shrink)

That biology provides explanations is not open to doubt. But how it does so must be a vexed question for those who deny that biology embodies laws or other generalizations with the sort of explanatory force that the philosophy of science recognizes. The most common response to this problem has involved redefining law so that those grammatically general statements which biologists invoke in explanations can be counted as laws. But this terminological innovation cannot identify the source of (...) class='Hi'>biology's explanatory power. I argue that because biological science is historical, the problem of biological explanation can be assimilated to the parallel problem in the philosophy of history, and that the problem was solved by Carl Hempel. All we need to do is recognize that the only laws that biology—in all its compartments from the molecular onward—has or needs are the laws of natural selection. (shrink)

Causal explanations of behavior must distinguish two kinds of cause. There are triggering causes, the events or conditions that come before the effect and are followed regularly by the effect, and structuring causes, events that cause a triggering cause to produce its effect. Moving the mouse is the triggering cause of cursor movement; hardware and programming conditions are the structuring causes of cursor movement. I use this distinction to show how representational facts can be structuring causes of behavior even though (...) biological events trigger the behavior. (shrink)

The aim of this paper is to show that critics of biological explanations of human nature may be granting too much to those who propose such explanations when they argue that the truth of genetic determinism implies an end to critical evaluation and reform of our social institutions. This is the case because when we argue that biological determinism exempts us from social critique we are erroneously presupposing that our social values, practices, and institutions have nothing to do with what (...) makes biological explanations troublesome. My argument is that what constitutes a problem for those who are concerned with social justice is not the fact that particular behaviours may be genetically determined, but the fact that our value system and social institutions create the conditions that make such behaviours problematic. Thus, I will argue that even if genetic determinism were correct, the requirement of assessing and transforming our social practices and institutions would be far from superfluous. Biology is rarely destiny for human beings and the institutions they create. (shrink)

This is an extended review of John Dupré's _Processes of Life_, a collection of essays. It clarifies Dupré's concepts of reductionism and anti-reductionism, and critically examines his associated discussions of downward causation, and both the context sensitivity and multiple realization of categories. It reviews his naturalistic monism, and critically distinguishes between his realism about categories and constructivism about classification. Challenges to his process ontology are presented, as are arguments for his pluralism about scientific categories. None of his main conclusions are (...) rejected; rather it is main arguments for them that are the focus. (shrink)

This article argues that the basic account of mechanism and mechanistic explanation, involving sequential execution of qualitatively characterized operations, is itself insufficient to explain biological phenomena such as the capacity of living organisms to maintain themselves as systems distinct from their environment. This capacity depends on cyclic organization, including positive and negative feedback loops, which can generate complex dynamics. Understanding cyclically organized mechanisms with complex dynamics requires coordinating research directed at decomposing mechanisms into parts and operations with research using (...) computational models to recompose mechanisms and determine their dynamic behavior. This coordinated endeavor yields dynamic mechanistic explanations. (shrink)

Philosophers intent upon characterizing the difference between physics and biology often seize upon the purported fact that physical explanations conform more closely to the covering law model than biological explanations. Central to this purported difference is the role of laws of nature in the explanations of these two sciences. However, I argue that, although certain important differences between physics and biology can be highlighted by differences between physical and biological explanations, these differences are not differences in the degree (...) to which those explanations conform to the covering law model, which fits biology about as well as it does physics. (shrink)

Machines and Biology have been, since antiquity, closely related. From the zoological figures present in astronomical simulacra, through renaissance mechanical imitations of animals, through Decartes' wind pipe nerves, to present day discussions on the computer and the brain, runs a continuous thread. In fact, the very name of mechanism for an attitude of inquiry throughout the history of Biology reveals this at a philosophical level. More often than not, mechanism is mentioned in opposition to vitalism, as an assertion (...) of the validity of the objectivity principle in biology: there are no purposes in animal nature; its apparent purposefulness is similar to the purposefulness of machines. Yet, the fact that one picks machines as a set of objects comparable to living systems, deserves a closer look. What in machines makes it possible to establish such a connection? (shrink)

Turing patterns are a class of minimal mathematical models that have been used to discover and conceptualize certain abstract features of early biological development. This paper examines a range of these minimal models in order to articulate and elaborate a philosophical analysis of their epistemic uses. It is argued that minimal mathematical models aid in structuring the epistemic practices of biology by providing precise descriptions of the quantitative relations between various features of the complex systems, generating novel predictions that (...) can be compared with experimental data, promoting theory exploration, and acting as constitutive parts of empirically adequate explanations of naturally occurring phenomena, such as biological pattern formation. Focusing on the roles that minimal model explanations play in science motivates the adoption of a broader diachronic view of scientific explanation. (shrink)

Walter M. Miller, Jr.’s 1959 novel A Canticle for Leibowitz is on one level a theological reflection on the human propensity to sin. Not coincidentally, the story is located in an Albertinian abbey in the former American southwest six hundred years after a nuclear holocaust, recounting three separate historical periods over the following twelve hundred years: a dark age, a scientific renaissance, and finally a time of technological achievement where a second nuclear holocaust is imminent. Miller asks the question of (...) whether humans as a species cannot avoid committing acts of sin that cumulatively and continually lead to acts of societal and technological self-destruction; his response oscillates between a fatalistic pessimism (the final extinction of the human species) and a vague optimism (the “new creature,” the mutant Rachel, or perhaps a last group of humans leaving the Earth as the curtain falls). It is my thesis in this article that theological questions about sin (as explored by Augustine and later scholars) can be fruitfully approached by analogous genetic processes; more precisely by reference to the rising science of Epigenetics, which explores how genes can express themselves differently without mutating in response to life stressors. In light of the idea of a genetic and epigenetic expression of moral rules of existence, Augustine’s thesis of original sin as something that is inherited makes new sense. In this light, it may also be possible to approach the question that the Canticle proposes: are we destined to self-destruction, or is there a way out of this destructive cycle? (shrink)

Kant's Critique of Teleological Judgment is read as a reflection on philosophical methodological problems that arose through the constitution of an independent science of life - biology. This work presents an example of the interconnections between philosophy and the history of science.

This chapter contains sections titled: Introduction Systems Biology Function: A Minimalist Conception Kant and As‐If Purpose Cybernetics and Bernard Machines A Guarded Optimism Postscript: Counterpoint References.

In the paper, starting from a slightly modified version of van Fraassen's pragmatic approach to explanation, I will propose a pragmatical meta-model for the different biological explanatory models. That is, I will offer a pragmatic point of view to rule different explanatory models in function of the biological context from which the given biologist explains.

In discussion of mechanisms, philosophers often debate about whether quantitative descriptions of generalizations or qualitative descriptions of operations are explanatorily fundamental. I argue that these debates have erred by conflating the explanatory roles of generalizations and patterns. Patterns are types of variations within or between quantities in a mechanism over time or across conditions. While these patterns must often be represented in addition to descriptions of operations in order to explain a phenomenon, they are not equivalent to generalizations because their (...) explanatory role does not depend on any specific facts about their scope or domain of invariance. (shrink)

Lea & Webley (L&W) provide two alternative biological accounts of human monetary motivations, the Tool Theory and the Drug Theory. They argue that both are required for an adequate explanation. I explore the applicability of these models to philosophical discussions of how we might justify such motivations. I argue their approach is not entirely satisfactory for normative questions, since it precludes the possibility of rational non-instrumental attitudes towards money. (Published Online April 5 2006).

In this essay I will consider some epistemological issues raised by the following two questions:(l) Does molecular biology provide the best explanations of biological phenomena?(2) What are the best ways (i.e., fruitful strategies) to cast molecular explanations of molecular phenomena?I will argue that notwithstanding the manifest scientific successes of the molecular revolution, the assessment of the philosophical debate between reductionists and antireductionists requires an examination of the ways in which the second question is currently being answered by molecular biologists.

This chapter contains sections titled: Introduction: No Need for Special Biological Laws? The Reductionist Principle Strong Emergence Complex Relations in Biology A Misinformed Slogan and Its Contributions Genes Causation Systems Biology Metaphysical Coda Postscript: Counterpoint Acknowledgments Notes References.

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)

Molecular biologists and biochemists often use diagrams to present hypotheses. Analysis of diagrams shows that their content can be expressed with linguistic representations. Why do biologists use visual representations instead? One reason is simple comprehensibility: some diagrams present information which is readily understood from the diagram format, but which would not be comprehensible if the same information was expressed linguistically. But often diagrams are used even when concise, comprehensible linguistic alternatives are available. I explain this phenomenon by showing why diagrammatic (...) representation is especially well suited for a particular kind of explanation common in molecular biology and biochemistry: namely, functional analysis, in which a capacity of the system is explained in terms of capacities of its component parts. (shrink)

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to (...) such explanations. I discuss how mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena, where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations. I offer general conclusions for philosophical accounts of explanation. (shrink)

In medicine, racial differences are frequently presented as part of the best explanation of differences in the risk of diseases. The problem of using racial classification in biomedical research has become important because of its ethical consequences in society. However, the biological relevance of the concept of race cannot be established by any ethical argument and the epistemological role of racial categorisation requires clarification. In this paper, different issues related to the concept of race are considered. This paper analyses (...) the semantic problem concerning the definition of race, considers the ontological problem of race, drawing attention to the biological evidence for genetic differences among human groups, and presents a promising epistemological approach to the problem of race. The purpose of the paper is to examine whether, or when, racial categories belong in biological explanations. It shows that the concept of race cannot be justified in biology because it does not lead to successful predictions, and that genetic discontinuities are sufficient to explain differences in diseases but not needed in the explanation. The biomedical field should search for genetic patterns related to diseases, and should not assume racial discontinuities among human groups and use racial clusters as proxies for undetected genetic patterns. (shrink)

I show how archaeologists have two problems. The construction of scenarios accounting for the raw data of Archaeology, the material remains of the past, and the explanation of pre-history. Within Archaeology, there has been an ongoing debate about how to constrain speculation within both of these archaeological projects, and archaeologists have consistently looked to biological mechanisms for constraints. I demonstrate the problems of using biology, either as an analogy for cultural processes or through direct application of biological principles (...) to material remains. This is done through setting out the requirements of a Darwinian Archaeology, and then measuring various approaches against these requirements. This approach leads to the conclusion that archaeologist's explanations of the past must include within their formulations an account of human cognitive capacities within their explanatory framework. The limits of our understanding of the human past will be the limits of our understanding of Homo sapiens. (shrink)

Pure mathematics can play an indispensable role explaining empirical phenomena if recent accounts of insect evolution are correct. In particular, the prime life cycles of cicadas and the geometric structure of honeycombs are taken to undergird an inference to the best explanation about mathematical entities. Neither example supports this inference or the mathematical realism it is intended to establish. Both incorrectly assume that facts about mathematical optimality drove selection for the respective traits and explain why they exist. We show (...) how this problem can be avoided, identify limitations of explanatory indispensability arguments, and attempt to clarify the nature of mathematical explanation. (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.

Persons have a curious dual nature. On the one hand, they are subjects, whose actions must be explained in terms of beliefs, desires, plans, and goals. At the same time, however, they also are physical objects, whose actions must be explicable in terms of physical laws. So far no satisfying account of this duality has been offered. Both Cartesian dualism and the modern materialist alternatives (reductionist and antireductionist) have failed to capture the full range of our experience of persons. I (...) argue that an exciting new approach to this difficulty can be found by considering developments in clinical psychology. The clinical debate between those endorsing biological models of mental illness and those endorsing psychodynamic models mirrors broader debates in the philosophy of mind. The possible resolution of this debate through the development of integrated psychobiological models suggests a promising way to reconcile the dual nature of persons in a far more appealing way than any yet proposed. (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)

David Marr's theory of vision has been a rich source of inspiration, fascination and confusion. I will suggest that some of this confusion can be traced to discrepancies between the way Marr developed his theory in practice and the way he suggested such a theory ought to be developed in his explicit metatheoretical remarks. I will address claims that Marr's theory may be seen as an optimizing theory, along with the attendant suggestion that optimizing assumptions may be inappropriate for cognitive (...) mechanisms just as anti-adaptationists have argued they are inappropriate for other physiological mechanisms. I will discuss the nature of optimizing assumptions and theories. Considering various difficulties in identifying and assessing optimizing assumptions, I will suggest that Marr's theory is not purely an optimizing theory and that reaction to Marr on this issue prompts interesting considerations for the development of inter-disciplinary constraints in the cognitive and brain sciences. (shrink)

Biology and history are often viewed as closely related disciplines, with biology informed by history, especially in its task of charting our evolutionary past. Maximizing the opportunities for cross-fertilization in these two fields requires an accurate reckoning of their commonalities and differences-precisely what this volume sets out to achieve. Specially commissioned essays by a team of recognized international researchers cover the full panoply of topics in these fields and include notable contributions on the correlativity of evolutionary and historical (...) explanations, applying to history the latest causal-mechanical approach in the philosophy of biology, and the question of generalized laws that might pertain across the two subjects. The collection opens with a vital interrogation of general issues on explanation that apart from potentially fruitful areas of interaction (could the etiology of the causal-mechanical perspective in biology account for the historical trajectory of the Roman Empire?) this volume also seeks to chart relative certainties distinguishing explanations in biology and history. It also assesses techniques such as the use of probabilities in biological reconstruction, deployed to overcome the inevitable gaps in physical evidence on early evolution. Methodologies such as causal graphs and semantic explanation receive in-depth analysis. Contributions from a host of prominent and widely read philosophers ensure that this new volume has the stature of a major addition to the literature. (shrink)

Given the rise of genetic etiological beliefs regarding psychiatric disorders, a growing body of research has focused on trying to elucidate the effects that such explanatory frameworks might be having on how mental disorders are perceived by patients, clinicians, and the general public. Genetic and other biomedical explanations of mental disorders have long been seen as a potential tool in the efforts to destigmatize mental disorders, given the harshness of the widespread negative attitudes about them and the important negative clinical (...) and social impacts of this stigma. The conventional wisdom has appeared to be that because the effects of genes are seen as falling outside individual control, conceiving of mental disorders as caused by genes casts patients as blameless, thereby reducing stigmatization. Indeed, the results of experimental and correlational research have now robustly linked genetic and other biomedical explanations for mental disorders with reductions in the extent to which people are blamed for their psychiatric symptoms. However, research examining the impact of genetic and other biomedical explanations of mental disorders has also suggested that they can have significant downsides. The most consistently observed negative effect of these kinds of explanations is that they can apparently lead to the assumption that mental disorders are unlikely to improve or abate. Genetic and other biomedical explanations of mental disorders can also increase people’s confidence in the effectiveness of biomedical treatments (such as pharmacotherapy) but decrease their confidence in the effectiveness of “nonbiomedical” treatments (such as psychotherapy). (shrink)

This paper argues that besides mechanistic explanations, there is a kind of explanation that relies upon “topological” properties of systems in order to derive the explanandum as a consequence, and which does not consider mechanisms or causal processes. I first investigate topological explanations in the case of ecological research on the stability of ecosystems. Then I contrast them with mechanistic explanations, thereby distinguishing the kind of realization they involve from the realization relations entailed by mechanistic explanations, and explain how (...) both kinds of explanations may be articulated in practice. The second section, expanding on the case of ecological stability, considers the phenomenon of robustness at all levels of the biological hierarchy in order to show that topological explanations are indeed pervasive there. Reasons are suggested for this, in which “neutral network” explanations are singled out as a form of topological explanation that spans across many levels. Finally, I appeal to the distinction of explanatory regimes to cast light on a controversy in philosophy of biology, the issue of contingence in evolution, which is shown to essentially involve issues about realization. (shrink)

This paper gives an account of evolutionary explanations in biology. Briefly, the explanations I am primarily concerned with are explanations of adaptations. These explanations are contrasted with other nonteleological evolutionary explanations. The distinction is made by distinguishing the different kinds of questions these different explanations serve to answer. The sense in which explanations of adaptations are teleological is spelled out.

One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely shared philosophical views about scientific explanation. But this discussion also reflects what I think is important for philosophers and biologists alike to appreciate about successful scientific explanations, so some points will be controversial, at least among philosophers. I make three main (...) points: (1) causal relationships and broad patterns have often been granted importance to scientific explanations, and they are in fact both important; (2) some explanations in biology cite the components of or processes in systems that account for the systems’ features, whereas other explanations feature large-scale or structural causes that influence a system; and (3) there can be multiple different explanations of a given biological phenomenon, explanations that respond to different research aims and can thus be compatible with one another even when they may seem to disagree. (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)