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  1. Turing Patterns and Biological Explanation.Maria Serban - 2017 - Disputatio 9 (47):529-552.
    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 (...)
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  • Medizin als Wissenschaft - eine wissenschaftstheoretische Analyse.Holger Lyre - 2018 - In Daniela Ringkamp & Héctor Wittwer (eds.), Was ist Medizin? Der Begriff der Medizin und seine ethischen Implikationen. Alber.
    Gegenstand dieses Beitrags ist eine Auseinandersetzung mit der Wissenschaftlichkeit der Medizin. Den Leitfaden der Analyse bildet dabei ein jüngerer Ansatz in der analytischen Wissenschaftstheorie, wonach Systematizität als zentrales Kriterium von Wissenschaft anzusehen ist (Hoyningen-Huene 2013). Ich werde im Detail zeigen, dass die Medizin dieses mehrdimensionale Kriterium insgesamt erfüllt, dass aus der Wissenschaftlichkeit der Medizin aber gleichwohl normative Konsequenzen folgen, die beispielsweise zur Abgrenzung von der Homöopathie und einer kritischen Bewertung des biopsychosozialen Modells führen. Zudem resultieren der Anwendungscharakter der Medizin und (...)
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  • (1 other version)On the Incompatibility of Dynamical Biological Mechanisms and Causal Graphs.Marcel Weber - 2016 - Philosophy of Science 83 (5):959-971.
    I examine to what extent accounts of mechanisms based on formal interventionist theories of causality can adequately represent biological mechanisms with complex dynamics. Using a differential equation model for a circadian clock mechanism as an example, I first show that there exists an iterative solution that can be interpreted as a structural causal model. Thus, in principle, it is possible to integrate causal difference-making information with dynamical information. However, the differential equation model itself lacks the right modularity properties for a (...)
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  • A Biologically Informed Hylomorphism.Christopher J. Austin - 2017 - In William M. R. Simpson, Robert Charles Koons & Nicholas Teh (eds.), Neo-Aristotelian Perspectives on Contemporary Science. New York: Routledge. pp. 185-210.
    Although contemporary metaphysics has recently undergone a neo-Aristotelian revival wherein dispositions, or capacities are now commonplace in empirically grounded ontologies, being routinely utilised in theories of causality and modality, a central Aristotelian concept has yet to be given serious attention – the doctrine of hylomorphism. The reason for this is clear: while the Aristotelian ontological distinction between actuality and potentiality has proven to be a fruitful conceptual framework with which to model the operation of the natural world, the distinction between (...)
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  • Typology and Natural Kinds in Evo-Devo.Ingo Brigandt - 2021 - In Nuño De La Rosa Laura & Müller Gerd (eds.), Evolutionary Developmental Biology: A Reference Guide. Springer. pp. 483-493.
    The traditional practice of establishing morphological types and investigating morphological organization has found new support from evolutionary developmental biology (evo-devo), especially with respect to the notion of body plans. Despite recurring claims that typology is at odds with evolutionary thinking, evo-devo offers mechanistic explanations of the evolutionary origin, transformation, and evolvability of morphological organization. In parallel, philosophers have developed non-essentialist conceptions of natural kinds that permit kinds to exhibit variation and undergo change. This not only facilitates a construal of species (...)
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  • Recent Work in The Philosophy of Biology.Christopher J. Austin - 2017 - Analysis 77 (2):412-432.
    The biological sciences have always proven a fertile ground for philosophical analysis, one from which has grown a rich tradition stemming from Aristotle and flowering with Darwin. And although contemporary philosophy is increasingly becoming conceptually entwined with the study of the empirical sciences with the data of the latter now being regularly utilised in the establishment and defence of the frameworks of the former, a practice especially prominent in the philosophy of physics, the development of that tradition hasn’t received the (...)
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  • The Ontic Account of Scientific Explanation.Carl F. Craver - 2014 - In Marie I. Kaiser, Oliver R. Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special science: The case of biology and history. Dordrecht: Springer. pp. 27-52.
    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 (...)
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  • Network representation and complex systems.Charles Rathkopf - 2018 - Synthese (1).
    In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining the properties (...)
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  • Functional kinds: a skeptical look.Cameron Buckner - 2015 - Synthese 192 (12):3915-3942.
    The functionalist approach to kinds has suffered recently due to its association with law-based approaches to induction and explanation. Philosophers of science increasingly view nomological approaches as inappropriate for the special sciences like psychology and biology, which has led to a surge of interest in approaches to natural kinds that are more obviously compatible with mechanistic and model-based methods, especially homeostatic property cluster theory. But can the functionalist approach to kinds be weaned off its dependency on laws? Dan Weiskopf has (...)
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  • (1 other version)Diagrams as Tools for Scientific Reasoning.Adele Abrahamsen & William Bechtel - 2015 - Review of Philosophy and Psychology 6 (1):117-131.
    We contend that diagrams are tools not only for communication but also for supporting the reasoning of biologists. In the mechanistic research that is characteristic of biology, diagrams delineate the phenomenon to be explained, display explanatory relations, and show the organized parts and operations of the mechanism proposed as responsible for the phenomenon. Both phenomenon diagrams and explanatory relations diagrams, employing graphs or other formats, facilitate applying visual processing to the detection of relevant patterns. Mechanism diagrams guide reasoning about how (...)
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  • Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In Pierre-Alain Braillard & Christophe Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    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 (...)
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  • Simulation and Understanding in the Study of Weather and Climate.Wendy S. Parker - 2014 - Perspectives on Science 22 (3):336-356.
    In 1904, Norwegian physicist Vilhelm Bjerknes published what would become a landmark paper in the history of meteorology. In that paper, he proposed that daily weather forecasts could be made by calculating later states of the atmosphere from an earlier state using the laws of hydrodynamics and thermodynamics (Bjerknes 1904). He outlined a set of differential equations to be solved and advocated the development of graphical and numerical solution methods, since analytic solution was out of the question. Using these theory-based (...)
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  • A Field Guide to Mechanisms: Part I.Holly Andersen - 2014 - Philosophy Compass 9 (4):274-283.
    In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning distinct senses. The ‘new mechanisms’ (...)
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  • Sculpting the space of actions. Explaining human action by integrating intentions and mechanisms.Machiel Keestra - 2014 - Dissertation, University of Amsterdam
    How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...)
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  • Synthetic Modeling and Mechanistic Account: Material Recombination and Beyond.Tarja Knuuttila & Andrea Loettgers - 2013 - Philosophy of Science 80 (5):874-885.
    Recently, Bechtel and Abrahamsen have argued that mathematical models study the dynamics of mechanisms by recomposing the components and their operations into an appropriately organized system. We will study this claim through the practice of combinational modeling in circadian clock research. In combinational modeling, experiments on model organisms and mathematical/computational models are combined with a new type of model—a synthetic model. We argue that the strategy of recomposition is more complicated than what Bechtel and Abrahamsen indicate. Moreover, synthetic modeling as (...)
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  • Information Channels and Biomarkers of Disease.Phyllis Illari & Federica Russo - 2016 - Topoi 35 (1):175-190.
    Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...)
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  • (1 other version)A property cluster theory of cognition.Cameron Buckner - 2013 - Philosophical Psychology (3):1-30.
    Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that comparative (...)
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  • Causal graphs and biological mechanisms.Alexander Gebharter & Marie I. Kaiser - 2014 - In Marie I. Kaiser, Oliver R. Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special science: The case of biology and history. Dordrecht: Springer. pp. 55-86.
    Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...)
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  • Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation.Ingo Brigandt - 2015 - In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer. pp. 135-173.
    Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...)
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  • Understanding endogenously active mechanisms: A scientific and philosophical challenge. [REVIEW]William Bechtel - 2012 - European Journal for Philosophy of Science 2 (2):233-248.
    Abstract Although noting the importance of organization in mechanisms, the new mechanistic philosophers of science have followed most biologists in focusing primarily on only the simplest mode of organization in which operations are envisaged as occurring sequentially. Increasingly, though, biologists are recognizing that the mechanisms they confront are non-sequential and the operations nonlinear. To understand how such mechanisms function through time, they are turning to computational models and tools of dynamical systems theory. Recent research on circadian rhythms addressing both intracellular (...)
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  • Mechanism and Biological Explanation.William Bechtel - 2011 - Philosophy of Science 78 (4):533-557.
    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 (...)
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  • What is a mechanism? Thinking about mechanisms across the sciences.Phyllis McKay Illari & Jon Williamson - 2012 - European Journal for Philosophy of Science 2 (1):119-135.
    After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.
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  • The Nature of Dynamical Explanation.Carlos Zednik - 2011 - Philosophy of Science 78 (2):238-263.
    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 (...)
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  • The cell: locus or object of inquiry?William Bechtel - 2010 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (3):172-182.
    Research in many fields of biology has been extremely successful in decomposing biological mechanisms to discover their parts and operations. It often remains a significant challenge for scientists to recompose these mechanisms to understand how they function as wholes and interact with the environments around them. This is true of the eukaryotic cell. Although initially identified in nineteenth-century cell theory as the fundamental unit of organisms, researchers soon learned how to decompose it into its organelles and chemical constituents and have (...)
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  • The Explanatory Role of Machine Learning in Molecular Biology.Fridolin Gross - forthcoming - Erkenntnis:1-21.
    The philosophical debate around the impact of machine learning in science is often framed in terms of a choice between AI and classical methods as mutually exclusive alternatives involving difficult epistemological trade-offs. A common worry regarding machine learning methods specifically is that they lead to opaque models that make predictions but do not lead to explanation or understanding. Focusing on the field of molecular biology, I argue that in practice machine learning is often used with explanatory aims. More specifically, I (...)
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  • The pragmatic use of metaphor in empirical psychology.Rami Gabriel - 2022 - History of the Human Sciences 35 (3-4):291-316.
    Metaphors of mind and their elaboration into models serve a crucial explanatory role in psychology. In this article, an attempt is made to describe how biology and engineering provide the predominant metaphors for contemporary psychology. A contrast between the discursive and descriptive functions of metaphor use in theory construction serves as a platform for deliberation upon the pragmatic consequences of models derived therefrom. The conclusion contains reflections upon the possibility of an integrative interdisciplinary psychology.
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  • Control Mechanisms: Explaining the Integration and Versatility of Biological Organisms.Leonardo Bich & William Bechtel - 2022 - Adaptive Behavior.
    Living organisms act as integrated wholes to maintain themselves. Individual actions can each be explained by characterizing the mechanisms that perform the activity. But these alone do not explain how various activities are coordinated and performed versatilely. We argue that this depends on a specific type of mechanism, a control mechanism. We develop an account of control by examining several extensively studied control mechanisms operative in the bacterium E. coli. On our analysis, what distinguishes a control mechanism from other mechanisms (...)
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  • Mechanism, autonomy and biological explanation.Leonardo Bich & William Bechtel - 2021 - Biology and Philosophy 36 (6):1-27.
    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, (...)
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  • In search of an ontology for 4E theories: from new mechanism to causal powers realism.Charles Lassiter & Joseph Vukov - 2021 - Synthese 199 (3-4):9785-9808.
    Embodied, embedded, enactive, and extended theorists do not typically focus on the ontological frameworks in which they develop their theories. One exception is 4E theories that embrace New Mechanism. In this paper, we endorse the New Mechanist’s general turn to ontology, but argue that their ontology is not the best on the market for 4E theories. Instead, we advocate for a different ontology: causal powers realism. Causal powers realism posits that psychological manifestations are the product of mental powers, and that (...)
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  • Etiological Explanations: Illness Causation Theory.Olaf Dammann - 2020 - Boca Raton, FL, USA: CRC Press.
    Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...)
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  • Two kinds of explanatory integration in cognitive science.Samuel D. Taylor - 2019 - Synthese 198 (5):4573-4601.
    Some philosophers argue that we should eschew cross-explanatory integrations of mechanistic, dynamicist, and psychological explanations in cognitive science, because, unlike integrations of mechanistic explanations, they do not deliver genuine, cognitive scientific explanations. Here I challenge this claim by comparing the theoretical virtues of both kinds of explanatory integrations. I first identify two theoretical virtues of integrations of mechanistic explanations—unification and greater qualitative parsimony—and argue that no cross-explanatory integration could have such virtues. However, I go on to argue that this is (...)
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  • Phenomenology and functional analysis. A functionalist reading of Husserlian phenomenology.Marek Pokropski - 2020 - Phenomenology and the Cognitive Sciences 19 (5):869-889.
    In the article I discuss functionalist interpretations of Husserlian phenomenology. The first one was coined in the discussion between Hubert Dreyfus and Ronald McIntyre. They argue that Husserl’s phenomenology shares similarities with computational functionalism, and the key similarity is between the concept of noema and the concept of mental representation. I show the weaknesses of that reading and argue that there is another available functionalist reading of Husserlian phenomenology. I propose to shift perspective and approach the relation between phenomenology and (...)
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  • Toward Mechanism 2.1: A Dynamic Causal Approach.Wei Fang - 2021 - Philosophy of Science 88 (5):796-809.
    I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...)
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  • Dynamical causes.Russell Meyer - 2020 - Biology and Philosophy 35 (5):1-21.
    Mechanistic explanations are often said to explain because they reveal the causal structure of the world. Conversely, dynamical models supposedly lack explanatory power because they do not describe causal structure. The only way for dynamical models to produce causal explanations is via the 3M criterion: the model must be mapped onto a mechanism. This framing of the situation has become the received view around the viability of dynamical explanation. In this paper, I argue against this position and show that dynamical (...)
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  • Mental kinematics: dynamics and mechanics of neurocognitive systems.David L. Barack - 2020 - Synthese 199 (1-2):1091-1123.
    Dynamical systems play a central role in explanations in cognitive neuroscience. The grounds for these explanations are hotly debated and generally fall under two approaches: non-mechanistic and mechanistic. In this paper, I first outline a neurodynamical explanatory schema that highlights the role of dynamical systems in cognitive phenomena. I next explore the mechanistic status of such neurodynamical explanations. I argue that these explanations satisfy only some of the constraints on mechanistic explanation and should be considered pseudomechanistic explanations. I defend this (...)
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  • Philosophy of Cell Biology.William Bechtel & Andrew Bollhagen - 2019 - Stanford Encyclopedia of Philosophy.
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  • Getting over Atomism: Functional Decomposition in Complex Neural Systems.Daniel C. Burnston - 2021 - British Journal for the Philosophy of Science 72 (3):743-772.
    Functional decomposition is an important goal in the life sciences, and is central to mechanistic explanation and explanatory reduction. A growing literature in philosophy of science, however, has challenged decomposition-based notions of explanation. ‘Holists’ posit that complex systems exhibit context-sensitivity, dynamic interaction, and network dependence, and that these properties undermine decomposition. They then infer from the failure of decomposition to the failure of mechanistic explanation and reduction. I argue that complexity, so construed, is only incompatible with one notion of decomposition, (...)
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  • The Emotional Mind: the affective roots of culture and cognition.Stephen Asma & Rami Gabriel - 2019 - Harvard University Press.
    Tracing the leading role of emotions in the evolution of the mind, a philosopher and a psychologist pair up to reveal how thought and culture owe less to our faculty for reason than to our capacity to feel. Many accounts of the human mind concentrate on the brain’s computational power. Yet, in evolutionary terms, rational cognition emerged only the day before yesterday. For nearly 200 million years before humans developed a capacity to reason, the emotional centers of the brain were (...)
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  • Mechanisms, Models and Laws in Understanding Supernovae.Phyllis Illari - 2019 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 50 (1):63-84.
    There has been a burst of work in the last couple of decades on mechanistic explanation, as an alternative to the traditional covering-law model of scientific explanation. That work makes some interesting claims about mechanistic explanations rendering phenomena ‘intelligible’, but does not develop this idea in great depth. There has also been a growth of interest in giving an account of scientific understanding, as a complement to an account of explanation, specifically addressing a three-place relationship between explanation, world, and the (...)
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  • Strategies of Explanatory Abstraction in Molecular Systems Biology.Nicholaos Jones - 2018 - Philosophy of Science 85 (5):955-968.
    I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation of chemotaxis (...)
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  • Structures, dynamics and mechanisms in neuroscience: an integrative account.Holger Lyre - 2018 - Synthese 195 (12):5141-5158.
    Proponents of mechanistic explanations have recently proclaimed that all explanations in the neurosciences appeal to mechanisms. The purpose of the paper is to critically assess this statement and to develop an integrative account that connects a large range of both mechanistic and dynamical explanations. I develop and defend four theses about the relationship between dynamical and mechanistic explanations: that dynamical explanations are structurally grounded, that they are multiply realizable, possess realizing mechanisms and provide a powerful top-down heuristic. Four examples shall (...)
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  • The Sum of the Parts: Large-Scale Modeling in Systems Biology.Fridolin Gross & Sara Green - 2017 - Philosophy, Theory, and Practice in Biology 9 (10).
    Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems “as a whole.” Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call “modular reductionism” and “bottom-up reductionism.” Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies (...)
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  • The ontology of organisms: Mechanistic modules or patterned processes?Christopher J. Austin - 2016 - Biology and Philosophy 31 (5):639-662.
    Though the realm of biology has long been under the philosophical rule of the mechanistic magisterium, recent years have seen a surprisingly steady rise in the usurping prowess of process ontology. According to its proponents, theoretical advances in the contemporary science of evo-devo have afforded that ontology a particularly powerful claim to the throne: in that increasingly empirically confirmed discipline, emergently autonomous, higher-order entities are the reigning explanantia. If we are to accept the election of evo-devo as our best conceptualisation (...)
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  • Data graphs and mechanistic explanation.Daniel C. Burnston - 2016 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 57 (C):1-12.
    It is a widespread assumption in philosophy of science that data is what is explained by theory—that data itself is not explanatory. I draw on instances of representational and explanatory practice from mammalian chronobiology to suggest that this assumption is unsustainable. In many instances, biologists employ representations of data in explanatory ways that are not reducible to constraints on or evidence for representations of mechanisms. Data graphs are used to exemplify relationships between quantities in the mechanism, and often these representations (...)
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  • Basic science through engineering? Synthetic modeling and the idea of biology-inspired engineering.Tarja Knuuttila & Andrea Loettgers - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):158-169.
    Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is (...)
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  • Environmental Ethics.Roberta L. Millstein - 2013 - In Kostas Kampourakis (ed.), The Philosophy of Biology: a Companion for Educators. Dordrecht: Springer.
    A number of areas of biology raise questions about what is of value in the natural environment and how we ought to behave towards it: conservation biology, environmental science, and ecology, to name a few. Based on my experience teaching students from these and similar majors, I argue that the field of environmental ethics has much to teach these students. They come to me with pent-up questions and a feeling that more is needed to fully engage in their subjects, and (...)
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  • Pain is Mechanism.Simon van Rysewyk - 2013 - Dissertation, University of Tasmania
    What is the relationship between pain and the body? I claim that pain is best explained as a type of personal experience and the bodily response during pain is best explained in terms of a type of mechanical neurophysiologic operation. I apply the radical philosophy of identity theory from philosophy of mind to the relationship between the personal experience of pain and specific neurophysiologic mechanism and argue that the relationship between them is best explained as one of type identity. Specifically, (...)
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  • Systems biology and the integration of mechanistic explanation and mathematical explanation.Ingo Brigandt - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    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 (...)
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  • Abstraction and the Organization of Mechanisms.Arnon Levy & William Bechtel - 2013 - Philosophy of Science 80 (2):241-261.
    Proponents of mechanistic explanation all acknowledge the importance of organization. But they have also tended to emphasize specificity with respect to parts and operations in mechanisms. We argue that in understanding one important mode of organization—patterns of causal connectivity—a successful explanatory strategy abstracts from the specifics of the mechanism and invokes tools such as those of graph theory to explain how mechanisms with a particular mode of connectivity will behave. We discuss the connection between organization, abstraction, and mechanistic explanation and (...)
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  • Thinking Dynamically About Biological Mechanisms: Networks of Coupled Oscillators. [REVIEW]William Bechtel & Adele A. Abrahamsen - 2013 - Foundations of Science 18 (4):707-723.
    Explaining the complex dynamics exhibited in many biological mechanisms requires extending the recent philosophical treatment of mechanisms that emphasizes sequences of operations. To understand how nonsequentially organized mechanisms will behave, scientists often advance what we call dynamic mechanistic explanations. These begin with a decomposition of the mechanism into component parts and operations, using a variety of laboratory-based strategies. Crucially, the mechanism is then recomposed by means of computational models in which variables or terms in differential equations correspond to properties of (...)
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