Studia Metodologiczne, 2019, nr 39


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    Foreword: Culture(s) of Modelling in Science(s)
    (Wydawnictwo Naukowe UAM, 2019) Boruszewski, Jarosław; Nowak-Posadzy, Krzysztof
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    Models and their Foundational Framework
    (2019) Thalheim, Bernhard
    The term model is mainly used in two meanings which are considered to be different: a model of a problem domain as a conceptualisation; a model of a set of formulas as an interpretation in which every formula within this set is true. A general theory of models has not yet been developed. H. Stachowiak proposes a phenomenal approach and ‘defines’ models by their properties of mapping, truncation and pragmatics. Meanwhile, a notion of the model has been developed. At the same time, it seems that there are rather different understandings of model in sciences and especially Mathematical Logics. Sciences treat models as reflections of origins. Mathematical logics considers models as an instantiation in which a set of statements is valid. So, mathematical model theory is often considered to be a completely different approach to modelling. We realise however that mathematical model theory is only a specific kind of modelling. We show that the treatment of models in logics and in sciences can be embedded into a more general framework. So, the theory of models is based on a separation of concern or orientation.
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    Cultures of Modelling: Rudolf Peierls on ‘Model-Making in Physics’
    (Wydawnictwo Naukowe UAM, 2019) Gelfert, Axel
    The philosophical debate about scientific models has, over the past thirty years or so, reached a high degree of sophistication. Yet, in spite of efforts to seek common ground with scientific practice, there remains the suspicion that philosophical accounts are sometimes too ‘free-floating’, in that they do not adequately reflect scientists’ views (and actual uses) of models. The present paper deals with one such scientific perspective, due to physicist Sir Rudolf Peierls (1907-1995). Writing thoroughly from the perspective of a theoretician with a deep appreciation for experimental physics, Peierls, in a series of papers, developed a taxonomy of scientific models, which – in spite of some inevitable arbitrariness – exhibits surprising points of convergence with contemporary philosophical accounts of how scientific models function. The present paper situates Peierls’s approach within the philosophical and scientific developments of his time, engages (in an immersive way) with his proposed taxonomy, and argues that Peierls’s views – and others like them – warrant the recent philosophical shift from a focus on model-based representation to non-representational (e.g., exploratory) uses and functions of models.
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    Modeling in Biology: looking backward and looking forward
    (Wydawnictwo Naukowe UAM, 2019) Orzack, Steven Hecht; McLoone, Brian
    Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and evolutionary biology believe that the use of many different experimental and mathematical models is necessary in order to do this. Many practitioners of both approaches misunderstand best practices of modeling, especially those related to model testing. We stress the need for biologists to better engage with best practices and for philosophers of biology providing normative guidance for biologists to better engage with current developments in biology. This is especially important as biology transitions from a “data-poor” to a “data-rich” discipline. If 21st century biology is going to capitalize on the unprecedented availability of ecological, evolutionary, and molecular data, of computational resources, and of mathematical and statistical tools, biologists will need a better understanding of what modeling is and can be.
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    The Curious Case of Formal Theory in Political Science: How Did It Emerge as a Discipline, Why Its Existence Is a Sign of a Failure, and Why the Science of Politics Is Not Possible Without It?
    (Wydawnictwo Naukowe UAM, 2019) Swistak, Piotr
    American political science has evolved a subfield which is commonly referred to as formal theory. Political scientists identify themselves as specializing in formal theory, departments advertise faculty positions in formal theory and put together formal theory subfields that offer undergraduate and graduate curricula. The roots of the field can be traced to Thomas Hobbes. Hobbes’ message, however, seems to have been utterly ignored by the social science. William Riker’s second launch of “Hobbesian advice”, in 1950’s and 60’s, proved more successful and put the field of formal theory on the map of political science. Yet, the very existence of the formal theory field can be seen as the failure of both Hobbes and Riker. There seems to be a continuing need for teaching social scientists why they should construct a proper science and how they should do it. This paper is an attempt to meet this need. I believe that the future science of politics will have to follow in the footsteps of Hobbes and Riker. And so will other social sciences. My point in the paper is not new; the way I make it, is.