Studia Metodologiczne, 2019, nr 39
Permanent URI for this collection
Browse
Recent Submissions
Item Foreword: Culture(s) of Modelling in Science(s)(Wydawnictwo Naukowe UAM, 2019) Boruszewski, Jarosław; Nowak-Posadzy, KrzysztofItem Models and their Foundational Framework(2019) Thalheim, BernhardThe 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.Item Cultures of Modelling: Rudolf Peierls on ‘Model-Making in Physics’(Wydawnictwo Naukowe UAM, 2019) Gelfert, AxelThe 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.Item Modeling in Biology: looking backward and looking forward(Wydawnictwo Naukowe UAM, 2019) Orzack, Steven Hecht; McLoone, BrianUnderstanding 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.Item 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, PiotrAmerican 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.Item Modelling communities and populations: An introduction to computational social science(Wydawnictwo Naukowe UAM, 2019) Jarynowski, Andrzej; Paradowski, Michał B.; Buda, AndrzejIn sociology, interest in modelling has not yet become widespread. However, the methodology has been gaining increased attention in parallel with its growing popularity in economics and other social sciences, notably psychology and political science, and the growing volume of social data being measured and collected. In this paper, we present representative computational methodologies from both data-driven (such as “black box”) and rule-based (such as “per analogy”) approaches. We show how to build simple models, and discuss both the greatest successes and the major limitations of modelling societies. We claim that the end goal of computational tools in sociology is providing meaningful analyses and calculations in order to allow making causal statements in sociological explanation and support decisions of great importance for society.Item Models and Beliefs they Produce(Wydawnictwo Naukowe UAM, 2019) Hardt, ŁukaszThis paper does not focus neither on models nor on modelling procedures but rather on the nature of knowledge about the world models give us. It puts forward the thesis that models are producers of beliefs about their targets. These beliefs may differ both in degree and scope. They are offered by various kinds of models, including models understood in terms of isolations as well as minimal models. This paper puts emphasis on what kind of entities beliefs produced by economic models are.Item Erosion of belief in “social rationality”: How game theory and social choice theory changed the understanding and modeling of social rationality(Wydawnictwo Naukowe UAM, 2019) Kaminski, Marek M.This article discusses how the developments in game theory and social choice theory profoundly transformed our understanding and modeling of social rationality in the social sciences due to the erosion of the concept of social optimum. I discuss the Prisoner’s Dilemma and relevant examples of social situations, analyze the difficulties that arise when games are repeated, and finally, check how the main results of social choice theory influenced our understanding of the “best” social outcome.Item The Exploratory Role of Idealizations and Limiting Cases in Models(Wydawnictwo Naukowe UAM, 2019) Shech, Elay; Gelfert, AxelIn this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transition. We end by reflecting on how our case studies and claims compare to accounts of idealization in the philosophy of science literature such as Michael Weisberg’s three-fold taxonomy.Item Value judgements and economic models – a Weberian perspective(Wydawnictwo Naukowe UAM, 2019) Mróz, RobertThe paper argues for the need to introduce analysis of value judgements into literature on economic modelling, which does not currently deal with this topic. It starts with a prescription formulated by Max Weber, that because social science is so permeated with value judgements (such as acceptance of certain ethical values and policy ends, or some methodological convictions), social scientists should openly state values and policy ends they accept while doing research. From this, a meta-theoretical prescription is formulated: whenever analysing a piece of research as its user or methodologist, value judgements expressed or assumed by the author need to be taken into account. If this is so, then a meta-theory of how to identify these components will be useful. As economics is a model-based science, it is desirable that this meta-theory be about models, or be part of a broader theory of models or modelling. Uskali Mäki’s “model of a model” is an example of such theory of models that is easy to amend and refocus to account for this requirement.Item From integration to modelling. On a neglected function of the methodology of humanities(Wydawnictwo Naukowe UAM, 2019) Boruszewski, Jarosław; Nowak-Posadzy, KrzysztofThe aim of this paper is two-fold: to engage the contemporary discussion about the nature of relations between different scientific disciplines, as well as to disentangle the concept of integration of sciences from superstructures of rival proposals. The authors start with a critical analysis of the Polish contribution to the discussion about the nature of integration of sciences from the second half of the XXth century. Such a step is followed by elaborating a refined account of integration and by disentangling the concept of integration from superstructures of rival proposals – unification and interdisciplinarity. On the grounds of such a refined account the authors deliver a reconstruction of a successful scientific integration. In doing this they introduce the idea of connective knowledge as generated by the methodology of humanities. After reconstructing the successful integration trial, in the concluding remarks their account of integration is specified and summarized.