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  1. When philosophy (of science) meets formal methods: a citation analysis of early approaches between research fields.Guido Bonino, Paolo Maffezioli, Eugenio Petrovich & Paolo Tripodi - 2022 - Synthese 200 (2).
    The article investigates what happens when philosophy meets and begins to establish connections with two formal research methods such as game theory and network science. We use citation analysis to identify, among the articles published in Synthese and Philosophy of Science between 1985 and 2021, those that cite the specialistic literature in game theory and network science. Then, we investigate the structure of the two corpora thus identified by bibliographic coupling and divide them into clusters of related papers by automatic (...)
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  • Organization needs organization: Understanding integrated control in living organisms.Leonardo Bich & William Bechtel - 2022 - Studies in History and Philosophy of Science Part A 93:96-106.
    Organization figures centrally in the understanding of biological systems advanced by both new mechanists and proponents of the autonomy framework. The new mechanists focus on how components of mechanisms are organized to produce a phenomenon and emphasize productive continuity between these components. The autonomy framework focuses on how the components of a biological system are organized in such a way that they contribute to the maintenance of the organisms that produce them. In this paper we analyze and compare these two (...)
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  • Decoupling Topological Explanations from Mechanisms.Daniel Kostic & Kareem Khalifa - 2023 - Philosophy of Science 90 (2):245 - 268.
    We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...)
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  • Biosemiotics and Applied Evolutionary Epistemology: A Comparison.Nathalie Gontier & M. Facoetti - 2021 - In Nathalie Gontier & M. Facoetti (eds.), In: Pagni E., Theisen Simanke R. (eds) Biosemiotics and Evolution. Interdisciplinary Evolution Research, vol 6. Springer, Cham. Cham: pp. 175-199.
    Both biosemiotics and evolutionary epistemology are concerned with how knowledge evolves. (Applied) Evolutionary Epistemology thereby focuses on identifying the units, levels, and mechanisms or processes that underlie the evolutionary development of knowing and knowledge, while biosemiotics places emphasis on the study of how signs underlie the development of meaning. We compare the two schools of thought and analyze how in delineating their research program, biosemiotics runs into several problems that are overcome by evolutionary epistemologists. For one, by emphasizing signs, biosemiotics (...)
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  • Mathematical Explanations in Evolutionary Biology or Naturalism? A Challenge for the Statisticalist.Fabio Sterpetti - 2021 - Foundations of Science 27 (3):1073-1105.
    This article presents a challenge that those philosophers who deny the causal interpretation of explanations provided by population genetics might have to address. Indeed, some philosophers, known as statisticalists, claim that the concept of natural selection is statistical in character and cannot be construed in causal terms. On the contrary, other philosophers, known as causalists, argue against the statistical view and support the causal interpretation of natural selection. The problem I am concerned with here arises for the statisticalists because the (...)
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  • Descriptive understanding and prediction in COVID-19 modelling.Johannes Findl & Javier Suárez - 2021 - History and Philosophy of the Life Sciences 43 (4):1-31.
    COVID-19 has substantially affected our lives during 2020. Since its beginning, several epidemiological models have been developed to investigate the specific dynamics of the disease. Early COVID-19 epidemiological models were purely statistical, based on a curve-fitting approach, and did not include causal knowledge about the disease. Yet, these models had predictive capacity; thus they were used to ground important political decisions, in virtue of the understanding of the dynamics of the pandemic that they offered. This raises a philosophical question about (...)
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  • Applying mechanical philosophy to web science: The case of social machines.Paul R. Smart, Kieron O’Hara & Wendy Hall - 2021 - European Journal for Philosophy of Science 11 (3):1-29.
    Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines, there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of (...)
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  • Unifying statistically autonomous and mathematical explanations.Travis L. Holmes - 2021 - Biology and Philosophy 36 (3):1-22.
    A subarea of the debate over the nature of evolutionary theory addresses what the nature of the explanations yielded by evolutionary theory are. The statisticalist line is that the general principles of evolutionary theory are not only amenable to a mathematical interpretation but that they need not invoke causes to furnish explanations. Causalists object that construction of these general principles involves crucial causal assumptions. A recent view claims that some biological explanations are statistically autonomous explanations (SAEs) whereby phenomena are accounted (...)
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  • Naturalización de la Metafísica Modal.Carlos Romero - 2021 - Dissertation, National Autonomous University of Mexico
    ⦿ In my dissertation I introduce, motivate and take the first steps in the implementation of, the project of naturalising modal metaphysics: the transformation of the field into a chapter of the philosophy of science rather than speculative, autonomous metaphysics. -/- ⦿ In the introduction, I explain the concept of naturalisation that I apply throughout the dissertation, which I argue to be an improvement on Ladyman and Ross' proposal for naturalised metaphysics. I also object to Williamson's proposal that modal metaphysics (...)
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  • How is cancer complex?Anya Plutynski - 2021 - European Journal for Philosophy of Science 11 (2):1-30.
    Cancer is typically spoken of as a “complex” disease. But, in what sense are cancers “complex”? Is there one sense, or several? What implications does this complexity have – both for how we study, and how we intervene upon cancers? The aim of this paper is first, to clarify the variety of senses in which cancer is spoken of as "complex" in the scientific literature, and second, to discover what explanatory and predictive roles such features play.
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  • The selectionist rationale for evolutionary progress.Hugh Desmond - 2021 - Biology and Philosophy 36 (3):1-26.
    The dominant view today on evolutionary progress is that it has been thoroughly debunked. Even value-neutral progress concepts are seen to lack important theoretical underpinnings: natural selection provides no rationale for progress, and natural selection need not even be invoked to explain large-scale evolutionary trends. In this paper I challenge this view by analysing how natural selection acts in heterogeneous environments. This not only undermines key debunking arguments, but also provides a selectionist rationale for a pattern of “evolutionary unfolding”, where (...)
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  • The Narrow Ontic Counterfactual Account of Distinctively Mathematical Explanation.Mark Povich - 2021 - British Journal for the Philosophy of Science 72 (2):511-543.
    An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s (forthcoming) deductive-mathematical account, because it is modelled on the deductive-nomological account, is unlikely to satisfy these desiderata. I provide a counterfactual account of DME, the Narrow (...)
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  • Distinctively mathematical explanation and the problem of directionality: A quasi-erotetic solution.Travis L. Holmes - 2021 - Studies in History and Philosophy of Science Part A 87 (C):13-21.
    The increasing preponderance of opinion that some natural phenomena can be explained mathematically has inspired a search for a viable account of distinctively mathematical explanation. Among the desiderata for an adequate account is that it should solve the problem of directionality and the reversals of distinctively mathematical explanations should not count as members among the explanatory fold but any solution must also avoid the exclusion of genuine explanations. In what follows, I introduce and defend what I refer to as a (...)
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  • The Ontology of Organismic Agency: A Kantian Approach.Hugh Desmond & Philippe Huneman - 2020 - In Andrea Altobrando & Pierfrancesco Biasetti (eds.), Natural Born Monads: On the Metaphysics of Organisms and Human Individuals. De Gruyter. pp. 33-64.
    Biologists explain organisms’ behavior not only as having been programmed by genes and shaped by natural selection, but also as the result of an organism’s agency: the capacity to react to environmental changes in goal-driven ways. The use of such ‘agential explanations’ reopens old questions about how justified it is to ascribe agency to entities like bacteria or plants that obviously lack rationality and even a nervous system. Is organismic agency genuinely ‘real’ or is it just a useful fiction? In (...)
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  • Philosophy of Cell Biology.William Bechtel & Andrew Bollhagen - 2019 - Stanford Encyclopedia of Philosophy.
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  • Prediction and Topological Models in Neuroscience.Bryce Gessell, Matthew Stanley, Benjamin Geib & Felipe De Brigard - 2020 - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...)
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  • How to Reconcile a Unified Account of Explanation with Explanatory Diversity.Collin Rice & Yasha Rohwer - 2020 - Foundations of Science 26 (4):1025-1047.
    The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that (...)
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  • General Theory of Topological Explanations and Explanatory Asymmetry.Daniel Kostic - 2020 - Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1796):1-8.
    In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; (...)
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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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  • Explaining the behaviour of random ecological networks: the stability of the microbiome as a case of integrative pluralism.Roger Deulofeu, Javier Suárez & Alberto Pérez-Cervera - 2019 - Synthese 198 (3):2003-2025.
    Explaining the behaviour of ecosystems is one of the key challenges for the biological sciences. Since 2000, new-mechanicism has been the main model to account for the nature of scientific explanation in biology. The universality of the new-mechanist view in biology has been however put into question due to the existence of explanations that account for some biological phenomena in terms of their mathematical properties (mathematical explanations). Supporters of mathematical explanation have argued that the explanation of the behaviour of ecosystems (...)
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  • Shades of Grey: Granularity, Pragmatics, and Non-Causal Explanation.Hugh Desmond - 2019 - Perspectives on Science 27 (1):68-87.
    Implicit contextual factors mean that the boundary between causal and noncausal explanation is not as neat as one might hope: as the phenomenon to be explained is given descriptions with varying degrees of granularity, the nature of the favored explanation alternates between causal and non-causal. While it is not surprising that different descriptions of the same phenomenon should favor different explanations, it is puzzling why re-describing the phenomenon should make any difference for the causal nature of the favored explanation. I (...)
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  • Multilevel Ensemble Explanations: A Case from Theoretical Biology.Luca Rivelli - 2019 - Perspectives on Science 27 (1):88-116.
    In this paper I will reconstruct and analyze a famous argument by Stuart Kauffman about complex systems and evolution, in order to highlight the use in theoretical biology of a kind of non-mechanistic and non-causal explanation which I propose to call, following Kauffman, ensemble explanation. The aim is to contribute to the ongoing philosophical debate about non-causal explanations in the special sciences, kinds of explanation apparently extraneous to the received causal-mechanistic view. Ensemble explanations resemble quite closely the explanations of the (...)
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  • Two challenges for a boolean approach to constitutive inference.Jens Harbecke - 2018 - European Journal for Philosophy of Science 9 (1):17.
    This paper discusses two challenges for a Boolean method for establishing constitutive regularity statements which, according to the regularity theory of mechanistic constitution, form the core of any mechanistic explanation in neuroscience. After presenting the regularity definition for the constitution relation and a methodology for constitutive inference, the paper discusses the problem of full variation of tested mechanistic factors and the problem of informational redundancy. A solution is offered for each problem. The first requires some adjustments to the original theory (...)
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  • Mathematical Explanations and the Piecemeal Approach to Thinking About Explanation.Gabriel Târziu - 2018 - Logique Et Analyse 61 (244):457-487.
    A new trend in the philosophical literature on scientific explanation is that of starting from a case that has been somehow identified as an explanation and then proceed to bringing to light its characteristic features and to constructing an account for the type of explanation it exemplifies. A type of this approach to thinking about explanation – the piecemeal approach, as I will call it – is used, among others, by Lange (2013) and Pincock (2015) in the context of their (...)
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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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  • Minimal structure explanations, scientific understanding and explanatory depth.Daniel Kostić - 2018 - Perspectives on Science (1):48-67.
    In this paper, I outline a heuristic for thinking about the relation between explanation and understanding that can be used to capture various levels of “intimacy”, between them. I argue that the level of complexity in the structure of explanation is inversely proportional to the level of intimacy between explanation and understanding, i.e. the more complexity the less intimacy. I further argue that the level of complexity in the structure of explanation also affects the explanatory depth in a similar way (...)
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  • Inference, Explanation, and Asymmetry.Kareem Khalifa, Jared Millson & Mark Risjord - 2018 - Synthese (Suppl 4):929-953.
    Explanation is asymmetric: if A explains B, then B does not explain A. Tradition- ally, the asymmetry of explanation was thought to favor causal accounts of explanation over their rivals, such as those that take explanations to be inferences. In this paper, we develop a new inferential approach to explanation that outperforms causal approaches in accounting for the asymmetry of explanation.
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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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  • Structural Powers and the Homeodynamic Unity of Organisms.Christopher J. Austin & Anna Marmodoro - 2017 - In William M. R. Simpson, Robert Charles Koons & Nicholas Teh (eds.), Neo-Aristotelian Perspectives on Contemporary Science. New York: Routledge. pp. 169-184.
    Although they are continually compositionally reconstituted and reconfigured, organisms nonetheless persist as ontologically unified beings over time – but in virtue of what? A common answer is: in virtue of their continued possession of the capacity for morphological invariance which persists through, and in spite of, their mereological alteration. While we acknowledge that organisms‟ capacity for the “stability of form” – homeostasis - is an important aspect of their diachronic unity, we argue that this capacity is derived from, and grounded (...)
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  • Why one model is never enough: a defense of explanatory holism.Hochstein Eric - 2017 - Biology and Philosophy 32 (6):1105-1125.
    Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...)
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  • The directionality of distinctively mathematical explanations.Carl F. Craver & Mark Povich - 2017 - Studies in History and Philosophy of Science Part A 63:31-38.
    In “What Makes a Scientific Explanation Distinctively Mathematical?” (2013b), Lange uses several compelling examples to argue that certain explanations for natural phenomena appeal primarily to mathematical, rather than natural, facts. In such explanations, the core explanatory facts are modally stronger than facts about causation, regularity, and other natural relations. We show that Lange's account of distinctively mathematical explanation is flawed in that it fails to account for the implicit directionality in each of his examples. This inadequacy is remediable in each (...)
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  • (1 other version)Systems Biology and Mechanistic Explanation.Ingo Brigandt, Sara Green & Maureen A. O'Malley - 2017 - In Stuart Glennan & Phyllis McKay Illari (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. Routledge. pp. 362-374.
    We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction (...)
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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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  • Selection in a Complex World: Deriving Causality from Stable Equilibrium.Hugh Desmond - 2018 - Erkenntnis 83 (2):265-286.
    It is an ongoing controversy whether natural selection is a cause of population change, or a mere statistical description of how individual births and deaths accumulate. In this paper I restate the problem in terms of the reference class problem, and propose how the structure of stable equilibrium can provide a solution in continuity with biological practice. Insofar natural selection can be understood as a tendency towards equilibrium, key statisticalist criticisms are avoided. Further, in a modification of the Newtonian-force analogy, (...)
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  • Minimal Models and the Generalized Ontic Conception of Scientific Explanation.Mark Povich - 2018 - British Journal for the Philosophy of Science 69 (1):117-137.
    Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) they propose (...)
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  • Outlines of a theory of structural explanations.Philippe Huneman - 2018 - Philosophical Studies 175 (3):665-702.
    This paper argues that in some explanations mathematics are playing an explanatory rather than a representational role, and that this feature unifies many types of non-causal or non-mechanistic explanations that some philosophers of science have been recently exploring under various names. After showing how mathematics can play either a representational or an explanatory role by considering two alternative explanations of a same biological pattern—“Bergmann’s rule”—I offer an example of an explanation where the bulk of the explanatory job is done by (...)
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  • II—James Woodward: Mechanistic Explanation: Its Scope and Limits.James Woodward - 2013 - Aristotelian Society Supplementary Volume 87 (1):39-65.
    This paper explores the question of whether all or most explanations in biology are, or ideally should be, ‘mechanistic’. I begin by providing an account of mechanistic explanation, making use of the interventionist ideas about causation I have developed elsewhere. This account emphasizes the way in which mechanistic explanations, at least in the biological sciences, integrate difference‐making and spatio‐temporal information, and exhibit what I call fine‐tunedness of organization. I also emphasize the role played by modularity conditions in mechanistic explanation. I (...)
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  • L'explication en biologie.Marie I. Kaiser - 2014 - In Eric Bapteste, Thierry Hoquet, Anouk Barberousse, Francesca Merlin, Frédéric Bouchard & Vincent Devictor (eds.), Précis de Philosophie de la biologie [Handbook Philosophy of Biology]. Vuibert Press. pp. 143-155.
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  • Network analyses in systems biology: new strategies for dealing with biological complexity.Sara Green, Maria Şerban, Raphael Scholl, Nicholaos Jones, Ingo Brigandt & William Bechtel - 2018 - Synthese 195 (4):1751-1777.
    The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from (...)
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  • Evo-devo: a science of dispositions.Christopher J. Austin - 2017 - European Journal for Philosophy of Science 7 (2):373-389.
    Evolutionary developmental biology represents a paradigm shift in the understanding of the ontogenesis and evolutionary progression of the denizens of the natural world. Given the empirical successes of the evo-devo framework, and its now widespread acceptance, a timely and important task for the philosophy of biology is to critically discern the ontological commitments of that framework and assess whether and to what extent our current metaphysical models are able to accommodate them. In this paper, I argue that one particular model (...)
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  • Explanation beyond causation? New directions in the philosophy of scientific explanation.Alexander Reutlinger - 2017 - Philosophy Compass 12 (2):e12395.
    In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of science. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism, and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations.
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  • (1 other version)Does the counterfactual theory of explanation apply to non-causal explanations in metaphysics?Alexander Reutlinger - 2017 - European Journal for Philosophy of Science 7 (2):239-256.
    In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I support (...)
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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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  • (1 other version)Does the Counterfactual Theory of Explanation Apply to Non-Causal Explanations in Metaphysics?Alexander Reutlinger - 2016 - European Journal for Philosophy of Science:1-18.
    In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation (CTE) captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I (...)
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  • Revisiting generality in the life sciences: Systems biology and the quest for general principles.Sara Green - unknown
    Due to the variation, contingency and complexity of living systems, biology is often taken to be a science without fundamental theories, laws or general principles. I revisit this question in light of the quest for design principles in systems biology and show that different views can be reconciled if we distinguish between different types of generality. The philosophical literature has primarily focused on generality of specific models or explanations, or on the heuristic role of abstraction. This paper takes a different (...)
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  • Is There A Monist Theory of Causal and Non-Causal Explanations? The Counterfactual Theory of Scientific Explanation.Alexander Reutlinger - 2016 - Philosophy of Science 83 (5):733-745.
    The goal of this paper is to develop a counterfactual theory of explanation. The CTE provides a monist framework for causal and non-causal explanations, according to which both causal and non-causal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler’s explanation and renormalization group explanations of universality.
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  • Diversifying the picture of explanations in biological sciences: ways of combining topology with mechanisms.Philippe Huneman - 2018 - Synthese 195 (1):115-146.
    Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological explanations (...)
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  • An Ontic Account of Explanatory Reduction in Biology.Marie I. Kaiser - 2012 - Köln: Kölner Hochschulschriften.
    Convincing disputes about explanatory reductionism in the philosophy of biology require a clear and precise understanding of what a reductive explanation in biology is. The central aim of this book is to provide such an account by revealing the features that determine the reductive character of a biological explanation. Chapters I-IV provide the ground, on which I can then, in Chapter V, develop my own account of explanatory reduction in biology: Chapter I reveals the meta-philosophical assumptions that underlie my analysis (...)
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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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  • Interdisciplinarity in Philosophy of Science.Marie I. Kaiser, Maria Kronfeldner & Robert Meunier - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):59-70.
    This paper examines various ways in which philosophy of science can be interdisciplinary. It aims to provide a map of relations between philosophy and sciences, some of which are interdisciplinary. Such a map should also inform discussions concerning the question “How much philosophy is there in the philosophy of science?” In Sect. 1, we distinguish between synoptic and collaborative interdisciplinarity. With respect to the latter, we furthermore distinguish between two kinds of reflective forms of collaborative interdisciplinarity. We also briefly explicate (...)
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