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  1. Entangled Life: Organism and Environment in the Biological and Social Sciences.Gillian Barker, Eric Desjardins & Trevor Pearce (eds.) - 2014 - Dordrecht: Springer.
    Despite the burgeoning interest in new and more complex accounts of the organism-environment dyad by biologists and philosophers, little attention has been paid in the resulting discussions to the history of these ideas and to their deployment in disciplines outside biology—especially in the social sciences. Even in biology and philosophy, there is a lack of detailed conceptual models of the organism-environment relationship. This volume is designed to fill these lacunae by providing the first multidisciplinary discussion of the topic of organism-environment (...)
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  • Environment as Abstraction.Denis Walsh - 2021 - Biological Theory 17 (1):68-79.
    The concept of the environment appears to be indispensably involved in adaptive explanation. Quite what its role is, however, is a matter of some dispute. The environment is customarily viewed as the dual of the organism; a wholly external, discrete, autonomous cause of evolution. On this view, the external environment is the principal cause of the adaptedness of form, and the determinant of what it is to be an adaptation. I argue that this conception of the environment neither adequately explains (...)
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  • Using causal models to integrate proximate and ultimate causation.Jun Otsuka - 2015 - Biology and Philosophy 30 (1):19-37.
    Ernst Mayr’s classical work on the nature of causation in biology has had a huge influence on biologists as well as philosophers. Although his distinction between proximate and ultimate causation recently came under criticism from those who emphasize the role of development in evolutionary processes, the formal relationship between these two notions remains elusive. Using causal graph theory, this paper offers a unified framework to systematically translate a given “proximate” causal structure into an “ultimate” evolutionary response, and illustrates evolutionary implications (...)
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  • Causal Foundations of Evolutionary Genetics.Jun Otsuka - 2014 - British Journal for the Philosophy of Science (1):axu039.
    The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...)
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  • Causal Foundations of Evolutionary Genetics.Jun Otsuka - 2016 - British Journal for the Philosophy of Science 67 (1):247-269.
    The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...)
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  • A critical review of the statisticalist debate.Jun Otsuka - 2016 - Biology and Philosophy 31 (4):459-482.
    Over the past decade philosophers of biology have discussed whether evolutionary theory is a causal theory or a phenomenological study of evolution based solely on the statistical features of a population. This article reviews this controversy from three aspects, respectively concerning the assumptions, applications, and explanations of evolutionary theory, with a view to arriving at a definite conclusion in each contention. In so doing I also argue that an implicit methodological assumption shared by both sides of the debate, namely the (...)
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  • How the Concept of Population Resolves Concepts of Environment.Roberta L. Millstein - 2014 - Philosophy of Science 81 (5):741-755.
    Elsewhere, I defend the “causal interactionist population concept” (CIPC). Here I further defend the CIPC by showing how it clarifies another concept that biologists grapple with, namely, environment. Should we understand selection as ranging only over homogeneous environments or, alternatively, as ranging over any habitat area we choose to study? I argue instead that the boundaries of the population dictate the range of the environment, whether homogeneous or heterogeneous, over which selection operates. Thus, understanding the concept of population helps us (...)
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  • Model change and reliability in scientific inference.Erich Kummerfeld & David Danks - 2014 - Synthese 191 (12):2673-2693.
    One persistent challenge in scientific practice is that the structure of the world can be unstable: changes in the broader context can alter which model of a phenomenon is preferred, all without any overt signal. Scientific discovery becomes much harder when we have a moving target, and the resulting incorrect understandings of relationships in the world can have significant real-world and practical consequences. In this paper, we argue that it is common (in certain sciences) to have changes of context that (...)
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  • Explanatory goals and explanatory means in multilevel selection theory.Ciprian Jeler - 2020 - History and Philosophy of the Life Sciences 42 (3):1-24.
    It has become customary in multilevel selection theory to use the same terms to denote both two explanatory goals and two explanatory means. This paper spells out some of the benefits that derive from avoiding this terminological conflation. I argue that keeping explanatory means and goals well apart allows us to see that, contrary to a popular recent idea, Price’s equation and contextual analysis—the statistical methods most extensively used for measuring the effects of certain evolutionary factors on the change in (...)
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  • A Note Against the Use of “Belonging To” Properties in Multilevel Selection Theory.Ciprian Jeler - 2020 - Acta Biotheoretica 69 (3):377-390.
    In this short paper, I argue against what I call the “belonging to” interpretation of group selection in scenarios in which a group’s fitness is defined as the per capita reproductive output of the individuals of the group. According to this interpretation, group selection acts on “belonging to” properties of individuals, i.e. on relational or contextual properties that all the individuals of a group share simply by belonging to that group; thus, if differences in the individuals’ “belonging to” properties cause (...)
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  • The Compatibility of Differential Equations and Causal Models Reconsidered.Wes Anderson - 2020 - Erkenntnis 85 (2):317-332.
    Weber argues that causal modelers face a dilemma when they attempt to model systems in which the underlying mechanism operates according to some set of differential equations. The first horn is that causal models of these systems leave out certain causal effects. The second horn is that causal models of these systems leave out time-dependent derivatives, and doing so distorts reality. Either way causal models of these systems leave something important out. I argue that Weber’s reasons for thinking causal modeling (...)
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  • Some Adaptations Were Not Positive Causal Factors for Reproductive Success.Wes Anderson - 2017 - Philosophy of Science 84 (1):1-13.
    Sober develops an account of adaptations on which they must have been positive causal factors for reproductive success. Glymour defends an account of a proper subset of adaptations—adaptations to particular environmental conditions—on which traits must interact in a special way with adapting conditions to cause reproductive success. These theories render conflicting judgments about which traits count as adaptations in some interesting cases. In this article I explore one such case and argue that we ought to replace the notion of adaptation (...)
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  • Causally Modeling Adaptation to the Environment.Wes Anderson - 2019 - Acta Biotheoretica 67 (3):201-224.
    Brandon claims that to explain adaptation one must specify fitnesses in each selective environment and specify the distribution of individuals across selective environments. Glymour claims, using an example of the adaptive evolution of costly plasticity in a symmetric environment, that there are some predictive or explanatory tasks for which Brandon’s claim is limited. In this paper, I provide necessary conditions for carrying out Brandon’s task, produce a new version of the argument for his claim, and show that Glymour’s reasons for (...)
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  • Probability and Manipulation: Evolution and Simulation in Applied Population Genetics.Marshall Abrams - 2015 - Erkenntnis 80 (S3):519-549.
    I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...)
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