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  1. Scientific Understanding and Felicitous Legitimate Falsehoods.Insa Lawler - forthcoming - Synthese:1-29.
    Science is replete with falsehoods that epistemically facilitate understanding by virtue of being the very falsehoods they are. In view of this puzzling fact, some have relaxed the truth requirement on understanding. I offer a factive view of understanding that fully accommodates the puzzling fact in four steps: (i) I argue that the question how these falsehoods are related to the phenomenon to be understood and the question how they figure into the content of understanding it are independent. (ii) I (...)
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  • To Envision a New Particle or Change an Existing Law? Hypothesis Formation and Anomaly Resolution for the Curious Case of the Β Decay Spectrum.Tjerk Gauderis - 2014 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 45:27-45.
    This paper addresses the question of how scientists determine which type of hypothesis is most suitable for tackling a particular problem by examining the historical case of the anomalous β spectrum in early nuclear physics, a puzzle that occasioned the most diverse hypotheses amongst physicists at the time. It is shown that such determinations are most often implicitly informed by scientists' individual perspectives on the structural relations between the various elements of the theory and the problem at hand. In addition (...)
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  • Approximations, Idealizations, and Models in Statistical Mechanics.Chuang Liu - 2001 - Erkenntnis 60 (2):235-263.
    In this paper, a criticism of the traditional theories of approximation and idealization is given as a summary of previous works. After identifying the real purpose and measure of idealization in the practice of science, it is argued that the best way to characterize idealization is not to formulate a logical model – something analogous to Hempel's D-N model for explanation – but to study its different guises in the praxis of science. A case study of it is then made (...)
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  • Scientific Representation.Mauricio Suárez - 2010 - Philosophy Compass 5 (1):91-101.
    Scientific representation is a currently booming topic, both in analytical philosophy and in history and philosophy of science. The analytical inquiry attempts to come to terms with the relation between theory and world; while historians and philosophers of science aim to develop an account of the practice of model building in the sciences. This article provides a review of recent work within both traditions, and ultimately argues for a practice-based account of the means employed by scientists to effectively achieve representation (...)
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  • How Do Models Give Us Knowledge? The Case of Carnot’s Ideal Heat Engine.Tarja Knuuttila & Mieke Boon - 2011 - European Journal for Philosophy of Science 1 (3):309-334.
    Our concern is in explaining how and why models give us useful knowledge. We argue that if we are to understand how models function in the actual scientific practice the representational approach to models proves either misleading or too minimal. We propose turning from the representational approach to the artefactual, which implies also a new unit of analysis: the activity of modelling. Modelling, we suggest, could be approached as a specific practice in which concrete artefacts, i.e., models, are constructed with (...)
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  • How Scientific Models Can Explain.Alisa Bokulich - 2011 - Synthese 180 (1):33 - 45.
    Scientific models invariably involve some degree of idealization, abstraction, or nationalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations, which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by applying it to the (...)
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  • When Scientific Models Represent.Daniela M. Bailer-Jones - 2003 - International Studies in the Philosophy of Science 17 (1):59 – 74.
    Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with data and (...)
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  • Making Models Count.Anna Alexandrova - 2008 - Philosophy of Science 75 (3):383-404.
    What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August 2008. †To contact (...)
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  • Forty Years of 'the Strategy': Levins on Model Building and Idealization. [REVIEW]Michael Weisberg - 2006 - Biology and Philosophy 21 (5):623-645.
    This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...)
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  • When Mechanistic Models Explain.Carl F. Craver - 2006 - Synthese 153 (3):355-376.
    Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...)
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  • Incredible Worlds, Credible Results.Jaakko Kuorikoski & Aki Lehtinen - 2009 - Erkenntnis 70 (1):119-131.
    Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability (...)
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  • Classification and Moral Evaluation of Uncertainties in Engineering Modeling.Colleen Murphy, Paolo Gardoni & Charles E. Harris - 2011 - Science and Engineering Ethics 17 (3):553-570.
    Engineers must deal with risks and uncertainties as a part of their professional work and, in particular, uncertainties are inherent to engineering models. Models play a central role in engineering. Models often represent an abstract and idealized version of the mathematical properties of a target. Using models, engineers can investigate and acquire understanding of how an object or phenomenon will perform under specified conditions. This paper defines the different stages of the modeling process in engineering, classifies the various sources of (...)
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  • Defending the Semantic View: What It Takes.Soazig Le Bihan - 2012 - European Journal for Philosophy of Science 2 (3):249-274.
    In this paper, a modest version of the Semantic View is motivated as both tenable and potentially fruitful for philosophy of science. An analysis is proposed in which the Semantic View is characterized by three main claims. For each of these claims, a distinction is made between stronger and more modest interpretations. It is argued that the criticisms recently leveled against the Semantic View hold only under the stronger interpretations of these claims. However, if one only commits to the modest (...)
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  • Interdisciplinary Modeling: A Case Study of Evolutionary Economics.Collin Rice & Joshua Smart - 2011 - Biology and Philosophy 26 (5):655-675.
    Biologists and economists use models to study complex systems. This similarity between these disciplines has led to an interesting development: the borrowing of various components of model-based theorizing between the two domains. A major recent example of this strategy is economists’ utilization of the resources of evolutionary biology in order to construct models of economic systems. This general strategy has come to be called evolutionary economics and has been a source of much debate among economists. Although philosophers have developed literatures (...)
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  • Model Organisms Are Not (Theoretical) Models.Arnon Levy & Adrian Currie - 2015 - British Journal for the Philosophy of Science 66 (2):327-348.
    Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. (...)
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  • Learning From Minimal Economic Models.Till Grüne-Yanoff - 2009 - Erkenntnis 70 (1):81-99.
    It is argued that one can learn from minimal economic models. Minimal models are models that are not similar to the real world, do not resemble some of its features, and do not adhere to accepted regularities. One learns from a model if constructing and analysing the model affects one’s confidence in hypotheses about the world. Economic models, I argue, are often assessed for their credibility. If a model is judged credible, it is considered to be a relevant possibility. Considering (...)
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  • La valeur de l'incertitude : l'évaluation de la précision des mesures physiques et les limites de la connaissance expérimentale.Fabien Grégis - 2016 - Dissertation, Université Sorbonne Paris Cité Université Paris.Diderot (Paris 7)
    Abstract : A measurement result is never absolutely accurate: it is affected by an unknown “measurement error” which characterizes the discrepancy between the obtained value and the “true value” of the quantity intended to be measured. As a consequence, to be acceptable a measurement result cannot take the form of a unique numerical value, but has to be accompanied by an indication of its “measurement uncertainty”, which enunciates a state of doubt. What, though, is the value of measurement uncertainty? What (...)
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  • How Models Are Used to Represent Reality.Ronald N. Giere - 2002 - Philosophy of Science 71 (5):742-752.
    Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, models, (...)
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  • The Philosophy of Simulation: Hot New Issues or Same Old Stew?Roman Frigg & Julian Reiss - 2009 - Synthese 169 (3):593-613.
    Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...)
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  • Representing in the Student Laboratory.Brandon Boesch - 2018 - Transversal: International Journal for the Historiography of Science 5:34-48.
    In this essay, I will expand the philosophical discussion about the representational practice in science to examine its role in science education through four case studies. The cases are of what I call ‘educational laboratory experiments’, performative models used representationally by students to come to a better understanding of theoretical knowledge of a scientific discipline. The studies help to demonstrate some idiosyncratic features of representational practices in science education, most importantly a lack of novelty and discovery built into the ELEs (...)
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  • Carnap's Forgotten Criterion of Empirical Significance.James Justus - 2014 - Mind 123 (490):415-436.
    The waning popularity of logical empiricism and the supposed discovery of insurmountable technical difficulties led most philosophers to abandon the project to formulate a formal criterion of empirical significance. Such a criterion would delineate claims that observation can confirm or disconfirm from those it cannot. Although early criteria were clearly inadequate, criticisms made of later, more sophisticated criteria were often indefensible or easily answered. Most importantly, Carnap’s last criterion was seriously misinterpreted and an amended version of it remains tenable.
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  • Idealization and the Aims of Economics: Three Cheers for Instrumentalism: Julian Reiss.Julian Reiss - 2012 - Economics and Philosophy 28 (3):363-383.
    This paper aims to provide characterizations of realism and instrumentalism that are philosophically interesting and applicable to economics; and to defend instrumentalism against realism as a methodological stance in economics. Starting point is the observation that ‘all models are false’, which, or so I argue, is difficult to square with the realist's aim of truth, even if the latter is understood as ‘partial’ or ‘approximate’. The three cheers in favour of instrumentalism are: Once we have usefulness, truth is redundant. There (...)
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  • Making Organisms Model Human Behavior: Situated Models in North-American Alcohol Research, Since 1950.Rachel A. Ankeny, Sabina Leonelli, Nicole C. Nelson & Edmund Ramsden - 2014 - Science in Context 27 (3):485-509.
    ArgumentWe examine the criteria used to validate the use of nonhuman organisms in North-American alcohol addiction research from the 1950s to the present day. We argue that this field, where the similarities between behaviors in humans and non-humans are particularly difficult to assess, has addressed questions of model validity by transforming the situatedness of non-human organisms into an experimental tool. We demonstrate that model validity does not hinge on the standardization of one type of organism in isolation, as often the (...)
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  • From the Lucasian Revolution to DSGE Models: An Account of Recent Developments in Macroeconomic Modelling.Francesco Sergi - 2017 - Erasmus Journal for Philosophy and Economics 10 (1):142-145.
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  • The Efficiency Question in Economics.Northcott Robert - 2018 - Philosophy of Science 85 (5):1140-1151.
    Much philosophical attention has been devoted to whether economic models explain, and more generally to how scientific models represent. Yet there is an issue more practically important to economics than either of these, which I label the efficiency question: regardless of how exactly models represent, or of whether their role is explanatory or something else, is current modeling practice an efficient way to achieve these goals – or should research efforts be redirected? In addition to showing how the efficiency question (...)
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  • Simulated Experiments: Methodology for a Virtual World.Winsberg Eric - 2003 - Philosophy of Science 70 (1):105-125.
    This paper examines the relationship between simulation and experiment. Many discussions of simulation, and indeed the term "numerical experiments," invoke a strong metaphor of experimentation. On the other hand, many simulations begin as attempts to apply scientific theories. This has lead many to characterize simulation as lying between theory and experiment. The aim of the paper is to try to reconcile these two points of viewto understand what methodological and epistemological features simulation has in common with experimentation, while at the (...)
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  • Experimental Modeling in Biology: In Vivo Representation and Stand-Ins As Modeling Strategies.Marcel Weber - 2014 - Philosophy of Science 81 (5):756-769.
    Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...)
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  • Modeling and Inferring in Science.Emiliano Ippoliti, Thomas Nickles & Fabio Sterpetti - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Springer. pp. 1-9.
    Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one is to (...)
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  • Modeling as a Case for the Empirical Philosophy of Science.Ekaterina Svetlova - 2015 - In Hanne Andersen, Nancy J. Nersessian & Susann Wagenknecht (eds.), Empirical Philosophy of Science. Springer Verlag. pp. 65-82.
    In recent years, the emergence of a new trend in contemporary philosophy has been observed in the increasing usage of empirical research methods to conduct philosophical inquiries. Although philosophers primarily use secondary data from other disciplines or apply quantitative methods (experiments, surveys, etc.), the rise of qualitative methods (e.g., in-depth interviews, participant observations and qualitative text analysis) can also be observed. In this paper, I focus on how qualitative research methods can be applied within philosophy of science, namely within the (...)
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  • Between Isolations and Constructions: Economic Models as Believable Worlds.Lukasz Hardt - 2016 - Poznan Studies in the Philosophy of the Sciences and the Humanities 106.
    As the title of this essay suggests, my concern is with the issue of what are economic models. However, the goal of the paper is not to offer an in-depth study on multiple approaches to modelling in economics, but rather to overcome the dichotomical divide between conceptualizing models as isolations and constructions. This is done by introducing the idea of economic models as believable worlds, precisely descriptions of mechanisms that refer to the essentials of the modelled targets. In doing so (...)
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  • Σύμβολου: An Attempt Toward the Early Origins: Part 2.Giuseppe Iurato - 2013 - Language and Psychoanalysis (ISSN 2049-324X) 2 (2):121-160.
    In continuation of what has been said in the first part of this two-part paper, herein we present further considerations on symbolism, reconsider some related psychodynamic case reports with some possible variants about their interpretations, and will apply what is said to some further speculations on mathematical symbolism and thought. In this second part, we continue with the numeration of the first part Σύμβολου, 1.
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  • Functional Analyses, Mechanistic Explanations, and Explanatory Tradeoffs.Sergio Daniel Barberis - 2013 - Journal of Cognitive Science 14:229-251.
    Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, we must take into account (...)
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  • Simplified Models: A Different Perspective on Models as Mediators.C. D. McCoy & Michela Massimi - 2018 - European Journal for Philosophy of Science 8 (1):99-123.
    We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...)
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  • Is Captain Kirk a Natural Blonde? Do X-Ray Crystallographers Dream of Electron Clouds? Comparing Model-Based Inferences in Science with Fiction.Ann-Sophie Barwich - 2018 - In Otávio Bueno, George Darby, Steven French & Dean Rickles (eds.), Thinking About Science, Reflecting on Art: Bringing Aesthetics and Philosophy of Science Together. London, UK:
    Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of (...)
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  • The Practical Value of Biological Information for Research.Beckett Sterner - 2014 - Philosophy of Science 81 (2):175-194,.
    Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent (...)
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  • The Scientific Image Twenty Years Later.Arthur Fine - 2001 - Philosophical Studies 106 (1-2):107 - 122.
    What we represent to ourselves behind the appear- ances exists only in our understanding . . . [having] only the value of memoria technica or formula whose form, because it is arbitrary and irrelevant, varies . . . with the standpoint of our culture.
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  • Building Simulations From the Ground Up: Modeling and Theory in Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2013 - Philosophy of Science 80 (4):533-556.
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  • Simulations, Models, and Theories: Complex Physical Systems and Their Representations.Eric Winsberg - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S442-.
    Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a "number crunching" technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories (and ascribes (...)
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  • Towards a General Model of Applying Science.Rens Bod - 2006 - International Studies in the Philosophy of Science 20 (1):5 – 25.
    How is scientific knowledge used, adapted, and extended in deriving phenomena and real-world systems? This paper aims at developing a general account of 'applying science' within the exemplar-based framework of Data-Oriented Processing (DOP), which is also known as Exemplar-Based Explanation (EBE). According to the exemplar-based paradigm, phenomena are explained not by deriving them all the way down from theoretical laws and boundary conditions but by modelling them on previously derived phenomena that function as exemplars. To accomplish this, DOP proposes to (...)
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  • On Representing the Relationship Between the Mathematical and the Empirical.Otávio Bueno, Steven French & James Ladyman - 2002 - Philosophy of Science 69 (3):497-518.
    We examine, from the partial structures perspective, two forms of applicability of mathematics: at the “bottom” level, the applicability of theoretical structures to the “appearances”, and at the “top” level, the applicability of mathematical to physical theories. We argue that, to accommodate these two forms of applicability, the partial structures approach needs to be extended to include a notion of “partial homomorphism”. As a case study, we present London's analysis of the superfluid behavior of liquid helium in terms of Bose‐Einstein (...)
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  • Mathematical Kinds, or Being Kind to Mathematics.David Neil Corfield - 2004 - Philosophica 74.
    In 1908, Henri Poincar? claimed that: ...the mathematical facts worthy of being studied are those which, by their analogy with other facts, are capable of leading us to the knowledge of a mathematical law, just as experimental facts lead us to the knowledge of a physical law. They are those which reveal to us unsuspected kinship between other facts, long known, but wrongly believed to be strangers to one another. Towards the end of the twentieth century, with many more mathematical (...)
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  • The Uses of Analogies in Seventeenth and Eighteenth Century Science.Yves Gingras & Alexandre Guay - 2011 - Perspectives on Science 19 (2):154-191.
    The object of this paper is to look at the extent and nature of the uses of analogy during the ªrst century following the so-called scientiªc revolution. Using the research tool provided by JSTOR we systematically analyze the uses of “analog” and its cognates (analogies, analogous, etc.) in the Philosophical Transactions of the Royal Society of London for the period 1665–1780. In addition to giving the possibility of evaluating quantitatively the proportion of papers explicitly using analogies, this approach makes it (...)
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  • Computer Simulations as Experiments.Sara Franceschelli - 2009 - Synthese 169 (3):557 - 574.
    Whereas computer simulations involve no direct physical interaction between the machine they are run on and the physical systems they are used to investigate, they are often used as experiments and yield data about these systems. It is commonly argued that they do so because they are implemented on physical machines. We claim that physicality is not necessary for their representational and predictive capacities and that the explanation of why computer simulations generate desired information about their target system is only (...)
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  • Towards a Unified Science of Cultural Evolution.Alex Mesoudi, Andrew Whiten & Kevin N. Laland - 2006 - Behavioral and Brain Sciences 29 (4):329-347.
    We suggest that human culture exhibits key Darwinian evolutionary properties, and argue that the structure of a science of cultural evolution should share fundamental features with the structure of the science of biological evolution. This latter claim is tested by outlining the methods and approaches employed by the principal subdisciplines of evolutionary biology and assessing whether there is an existing or potential corresponding approach to the study of cultural evolution. Existing approaches within anthropology and archaeology demonstrate a good match with (...)
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  • Professions as Science-Based Occupations.Thomas Brante - unknown
    How professions should be defined and separated from other occupations has constituted an enduring theoretical and empirical problem in studies of the professions. In this article, the definitions of the so-called list approaches, involving enumerations of social attributes, are scrutinized. Weak-nesses are highlighted and analysed. It is argued that an alternative approach to the issue of definition, commencing from the epistemic or cognitive dimensions of professions, may be more fruitful. One such possibility is presented by setting out from realist philosophy (...)
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  • Idealized, Inaccurate but Successful: A Pragmatic Approach to Evaluating Models in Theoretical Ecology. [REVIEW]Jay Odenbaugh - 2005 - Biology and Philosophy 20 (2-3):231-255.
    Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...)
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  • The Distribution of Representation.Lisa M. Osbeck & Nancy J. Nersessian - 2006 - Journal for the Theory of Social Behaviour 36 (2):141–160.
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  • Model, Theory, and Evidence in the Discovery of the DNA Structure.Samuel Schindler - 2008 - British Journal for the Philosophy of Science 59 (4):619-658.
    In this paper, I discuss the discovery of the DNA structure by Francis Crick and James Watson, which has provoked a large historical literature but has yet not found entry into philosophical debates. I want to redress this imbalance. In contrast to the available historical literature, a strong emphasis will be placed upon analysing the roles played by theory, model, and evidence and the relationship between them. In particular, I am going to discuss not only Crick and Watson's well-known model (...)
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  • Models of Success Versus the Success of Models: Reliability Without Truth.Eric Winsberg - 2006 - Synthese 152 (1):1-19.
    In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model comes not only (...)
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  • Experiments Versus Models: New Phenomena, Inference and Surprise.Mary S. Morgan - 2005 - Journal of Economic Methodology 12 (2):317-329.
    A comparison of models and experiments supports the argument that although both function as mediators and can be understood to work in an experimental mode, experiments offer greater epistemic power than models as a means to investigate the economic world. This outcome rests on the distinction that whereas experiments are versions of the real world captured within an artificial laboratory environment, models are artificial worlds built to represent the real world. This difference in ontology has epistemic consequences: experiments have greater (...)
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