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  1. Four Pillars of Statisticalism.Denis M. Walsh, André Ariew & Mohan Matthen - 2017 - Philosophy, Theory, and Practice in Biology 9 (1):1-18.
    Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...)
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  • Descriptions and models: Some responses to Abrams.Denis M. Walsh - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (3):302-308.
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  • Fitness: static or dynamic?Peter Takacs & Pierrick Bourrat - 2021 - European Journal for Philosophy of Science 11 (4):1-20.
    The most consistent definition of fitness makes it a static property of organisms. However, this is not how fitness is used in many evolutionary models. In those models, fitness is permitted to vary with an organism’s circumstances. According to this second conception, fitness is dynamic. There is consequently tension between these two conceptions of fitness. One recently proposed solution suggests resorting to conditional properties. We argue, however, that this solution is unsatisfactory. Using a very simple model, we show that it (...)
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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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  • 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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  • Inscrutability and the Opacity of Natural Selection and Random Genetic Drift: Distinguishing the Epistemic and Metaphysical Aspects.Philippe Huneman - 2015 - Erkenntnis 80 (S3):491-518.
    ‘Statisticalists’ argue that the individual interactions of organisms taken together constitute natural selection. On this view, natural selection is an aggregated effect of interactions rather than some added cause acting on populations. The statisticalists’ view entails that natural selection and drift are indistinguishable aggregated effects of interactions, so that it becomes impossible to make a difference between them. The present paper attempts to make sense of the difference between selection and drift, given the main insights of statisticalism; basically, it will (...)
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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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