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  1. Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
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  • Using Paleoclimate Analogues to Inform Climate Projections.Aja Watkins - 2024 - Perspectives on Science 32 (4):415-459.
    Philosophers of science have paid close attention to climate simulations as means of projecting the severity and effects of climate change, but have neglected the full diversity of methods in climate science. This paper shows the philosophical richness of another method in climate science: the practice of using paleoclimate analogues to inform our climate projections. First, I argue that the use of paleoclimate analogues can offer important insights to philosophers of the historical sciences. Rather than using the present as a (...)
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  • Simulated Data in Empirical Science.Aki Lehtinen & Jani Raerinne - forthcoming - Foundations of Science:1-22.
    This paper provides the first systematic epistemological account of simulated data in empirical science. We focus on the epistemic issues modelers face when they generate simulated data to solve problems with empirical datasets, research tools, or experiments. We argue that for simulated data to count as epistemically reliable, a simulation model does not have to mimic its target. Instead, some models take empirical data as a target, and simulated data may successfully mimic such a target even if the model does (...)
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  • Science, assertion, and the common ground.Corey Dethier - 2022 - Synthese 200 (1):1-19.
    I argue that the appropriateness of an assertion is sensitive to context—or, really, the “common ground”—in a way that hasn’t previously been emphasized by philosophers. This kind of context-sensitivity explains why some scientific conclusions seem to be appropriately asserted even though they are not known, believed, or justified on the available evidence. I then consider other recent attempts to account for this phenomenon and argue that if they are to be successful, they need to recognize the kind of context-sensitivity that (...)
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  • What is a Beautiful Experiment?Milena Ivanova - 2022 - Erkenntnis 88 (8):3419-3437.
    This article starts an engagement on the aesthetics of experiments and offers an account for analysing how aesthetics features in the design, evaluation and reception of experiments. I identify two dimensions of aesthetic evaluation of experiments: design and significance. When it comes to design, a number of qualities, such as simplicity, economy and aptness, are analysed and illustrated with the famous Meselson-Stahl experiment. Beautiful experiments are also regarded to make significant discoveries, but I argue against a narrow construal of experimental (...)
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  • Framing the Epistemic Schism of Statistical Mechanics.Javier Anta - 2021 - Proceedings of the X Conference of the Spanish Society of Logic, Methodology and Philosophy of Science.
    In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...)
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  • Data Journeys in the Sciences.Sabina Leonelli & Niccolò Tempini (eds.) - 2020 - Springer.
    This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in (...)
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  • Radiocarbon Dating in Archaeology: Triangulation and Traceability.Alison Wylie - 2020 - In Sabina Leonelli & Niccolò Tempini (eds.), Data Journeys in the Sciences. Springer. pp. 285-301.
    When radiocarbon dating techniques were applied to archaeological material in the 1950s they were hailed as a revolution. At last archaeologists could construct absolute chronologies anchored in temporal data backed by immutable laws of physics. This would make it possible to mobilize archaeological data across regions and time-periods on a global scale, rendering obsolete the local and relative chronologies on which archaeologists had long relied. As profound as the impact of 14C dating has been, it has had a long and (...)
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  • Computer Simulations as Scientific Instruments.Ramón Alvarado - 2022 - Foundations of Science 27 (3):1183-1205.
    Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.
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  • Models, Fictions and Artifacts.Tarja Knuuttila - 2021 - In Wenceslao J. Gonzalez (ed.), Language and Scientific Research. Springer Verlag. pp. 199-22.
    This paper discusses modeling from the artifactual perspective. The artifactual approach conceives models as erotetic devices. They are purpose-built systems of dependencies that are constrained in view of answering a pending scientific question, motivated by theoretical or empirical considerations. In treating models as artifacts, the artifactual approach is able to address the various languages of sciences that are overlooked by the traditional accounts that concentrate on the relationship of representation in an abstract and general manner. In contrast, the artifactual approach (...)
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  • Brain in the Shell. Assessing the Stakes and the Transformative Potential of the Human Brain Project.Philipp Haueis & Jan Slaby - 2015 - In Philipp Haueis & Jan Slaby (eds.), Neuroscience and Critique. London: pp. 117–140.
    The “Human Brain Project” (HBP) is a large-scale European neuroscience and information communication technology (ICT) project that has been a matter of heated controversy since its inception. With its aim to simulate the entire human brain with the help of supercomputing technologies, the HBP plans to fundamentally change neuroscientific research practice, medical diagnosis, and eventually the use of computers itself. Its controversial nature and its potential impacts render the HBP a subject of crucial importance for critical studies of science and (...)
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  • Scientific Coordination beyond the A Priori: A Three-dimensional Account of Constitutive Elements in Scientific Practice.Michele Luchetti - 2020 - Dissertation, Central European University
    In this dissertation, I present a novel account of the components that have a peculiar epistemic role in our scientific inquiries, since they contribute to establishing a form of coordination. The issue of coordination is a classic epistemic problem concerning how we justify our use of abstract conceptual tools to represent concrete phenomena. For instance, how could we get to represent universal gravitation as a mathematical formula or temperature by means of a numerical scale? This problem is particularly pressing when (...)
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  • Why computer simulations are not inferences, and in what sense they are experiments.Florian J. Boge - 2018 - European Journal for Philosophy of Science 9 (1):1-30.
    The question of where, between theory and experiment, computer simulations (CSs) locate on the methodological map is one of the central questions in the epistemology of simulation (cf. Saam Journal for General Philosophy of Science, 48, 293–309, 2017). The two extremes on the map have them either be a kind of experiment in their own right (e.g. Barberousse et al. Synthese, 169, 557–574, 2009; Morgan 2002, 2003, Journal of Economic Methodology, 12(2), 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison (...)
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  • How to infer explanations from computer simulations.Florian J. Boge - 2020 - Studies in History and Philosophy of Science Part A 82:25-33.
    Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue (...)
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  • How to Do Things with Theory: The Instrumental Role of Auxiliary Hypotheses in Testing.Corey Dethier - 2019 - Erkenntnis 86 (6):1453-1468.
    Pierre Duhem’s influential argument for holism relies on a view of the role that background theory plays in testing: according to this still common account of “auxiliary hypotheses,” elements of background theory serve as truth-apt premises in arguments for or against a hypothesis. I argue that this view is mistaken. Rather than serving as truth-apt premises in arguments, auxiliary hypotheses are employed as “epistemic tools”: instruments that perform specific tasks in connecting our theoretical questions with the world but that are (...)
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  • The epistemic superiority of experiment to simulation.Sherrilyn Roush - 2018 - Synthese 195 (11):4883-4906.
    This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...)
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  • Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
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  • From Models-as-Fictions to Models-as-Tools.Adrian Currie - 2017 - Ergo: An Open Access Journal of Philosophy 4.
    Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. (...)
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  • Hawking radiation and analogue experiments: A Bayesian analysis.Radin Dardashti, Stephan Hartmann, Karim P. Y. Thébault & Eric Winsberg - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 67:1-11.
    We present a Bayesian analysis of the epistemology of analogue experiments with particular reference to Hawking radiation. Provided such experiments can be externally validated via universality arguments, we prove that they are confirmatory in Bayesian terms. We then provide a formal model for the scaling behaviour of the confirmation measure for multiple distinct realisations of the analogue system and isolate a generic saturation feature. Finally, we demonstrate that different potential analogue realisations could provide different levels of confirmation. Our results thus (...)
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  • Robot life: simulation and participation in the study of evolution and social behavior.Christopher M. Kelty - 2018 - History and Philosophy of the Life Sciences 40 (1):16.
    This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton’s Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and (...)
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  • Varying the Explanatory Span: Scientific Explanation for Computer Simulations.Juan Manuel Durán - 2017 - International Studies in the Philosophy of Science 31 (1):27-45.
    This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model and the (...)
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  • Simulaciones computacionales: un análisis de dos concepciones antagónicas.Juan Manuel Duran - 2017 - Principia: An International Journal of Epistemology (April):125-140.
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  • Putting the Cart Before the Horse: Co-evolution of the Universe and Observers as an Explanatory Hypothesis.Milan M. Ćirković & Jelena Dimitrijević - 2018 - Foundations of Science 23 (3):427-442.
    The answer to the fine-tuning problem of the universe has been traditionally sought in terms of either design or multiverse. In philosophy circles, this is sometimes expanded by adding the option of explanatory nihilism—the claim that there is no explanation for statements of that high level of generality: fine-tunings are brute facts. In this paper, we consider the fourth option which, at least in principle, is available to us: co-evolution of the universe and observers. Although conceptual roots of this approach (...)
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  • “Agreement” in the IPCC Confidence measure.William Rehg & Kent Staley - 2017 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 57:126-134.
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  • Tools for Evaluating the Consequences of Prior Knowledge, but no Experiments. On the Role of Computer Simulations in Science.Eckhart Arnold - manuscript
    There is an ongoing debate on whether or to what degree computer simulations can be likened to experiments. Many philosophers are sceptical whether a strict separation between the two categories is possible and deny that the materiality of experiments makes a difference (Morrison 2009, Parker 2009, Winsberg 2010). Some also like to describe computer simulations as a “third way” between experimental and theoretical research (Rohrlich 1990, Axelrod 2003, Kueppers/Lenhard 2005). In this article I defend the view that computer simulations are (...)
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  • When can a Computer Simulation act as Substitute for an Experiment? A Case-Study from Chemisty.Johannes Kästner & Eckhart Arnold - manuscript
    In this paper we investigate with a case study from chemistry under what conditions a simulation can serve as a surrogate for an experiment. The case-study concerns a simulation of H2-formation in outer space. We find that in this case the simulation can act as a surrogate for an experiment, because there exists comprehensive theoretical background knowledge in form of quantum mechanics about the range of phenomena to which the investigated process belongs and because any particular modelling assumptions as can (...)
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  • Confirmation via Analogue Simulation: What Dumb Holes Could Tell Us about Gravity.Radin Dardashti, Karim P. Y. Thébault & Eric Winsberg - 2017 - British Journal for the Philosophy of Science 68 (1).
    In this article we argue for the existence of ‘analogue simulation’ as a novel form of scientific inference with the potential to be confirmatory. This notion is distinct from the modes of analogical reasoning detailed in the literature, and draws inspiration from fluid dynamical ‘dumb hole’ analogues to gravitational black holes. For that case, which is considered in detail, we defend the claim that the phenomena of gravitational Hawking radiation could be confirmed in the case that its counterpart is detected (...)
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  • Models and people: An alternative view of the emergent properties of computational models.Fabio Boschetti - 2016 - Complexity 21 (6):202-213.
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  • Global Climate Modeling as Applied Science.William M. Goodwin - 2015 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 46 (2):339-350.
    In this paper I argue that the appropriate analogy for “understanding what makes simulation results reliable” in Global Climate Modeling is not with scientific experimentation or measurement, but—at least in the case of the use of global climate models for policy development—with the applications of science in engineering design problems. The prospects for using this analogy to argue for the quantitative reliability of GCMs are assessed and compared with other potential strategies.
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  • Computer simulation and the features of novel empirical data.Greg Lusk - 2016 - Studies in History and Philosophy of Science Part A 56:145-152.
    In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining whether, and under (...)
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  • Models, measurement and computer simulation: the changing face of experimentation.Margaret Morrison - 2009 - Philosophical Studies 143 (1):33-57.
    The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections (...)
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  • Standing on the Shoulders of Giants—And Then Looking the Other Way? Epistemic Opacity, Immersion, and Modeling in Hydraulic Engineering.Matthijs Kouw - 2016 - Perspectives on Science 24 (2):206-227.
    Over the course of the twentieth century, hydraulic engineering has come to rely primarily on the use of computational models. Disco and van den Ende hint towards the reasons for widespread adoption of computational models by pointing out that such models fulfill a crucial role as management tools in Dutch water management, and meet a more general desire to quantify water-related phenomena. The successful application of computational models implies blackboxing : “[w]hen a machine runs efficiently … one need focus only (...)
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  • Computer simulations and experiments: in vivo–in vitro conditions in biochemistry.Pio Garcia - 2015 - Foundations of Chemistry 17 (1):49-65.
    Scientific practices have been changed by the increasing use of computer simulations. A central question for philosophers is how to characterize computer simulations. In this paper, we address this question by analyzing simulations in biochemistry. We propose that simulations have been used in biochemistry long before computers arrived. Simulation can be described as a surrogate relationship between models. Moreover, a simulative aspect is implicit in the classical dichotomy between in vivo–in vitro conditions. Based on a discussion about how to characterize (...)
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  • Brittleness and Bureaucracy: Software as a Material for Science.Matt Spencer - 2015 - Perspectives on Science 23 (4):466-484.
    . Through examining a case study of a major fluids modelling code, this paper charts two key properties of software as a material for building models. Scientific software development is characterized by piecemeal growth, and as a code expands, it begins to manifest frustrating properties that provide an important axis of motivation in the laboratory. The first such feature is a tendency towards brittleness. The second is an accumulation of supporting technologies that sometimes cause scientists to express a frustration with (...)
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  • Cognitive Science and Thought Experiments: A Refutation of Paul Thagard's Skepticism.Michael T. Stuart - 2014 - Perspectives on Science 22 (2):264-287.
    Paul Thagard has recently argued that thought experiments are dangerous and misleading when we try to use them as evidence for claims. This paper refutes his skepticism. Building on Thagard’s own work in cognitive science, I suggest that Thagard has much that is positive to say about how thought experiments work. My last section presents some new directions for research on the intersection between thought experiments and cognitive science.
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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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  • Classificatory Theory in Biology.Sabina Leonelli - 2013 - Biological Theory 7 (4):338-345.
    Scientific classification has long been recognized as involving a specific style of reasoning and doing research, and as occasionally affecting the development of scientific theories. However, the role played by classificatory activities in generating theories has not been closely investigated within the philosophy of science. I argue that classificatory systems can themselves become a form of theory, which I call classificatory theory, when they come to formalize and express the scientific significance of the elements being classified. This is particularly evident (...)
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  • Experimentele filosofie, kunstmatige intelligentie en cognitieve neurowetenschap.Pim Haselager - 2010 - Algemeen Nederlands Tijdschrift voor Wijsbegeerte 102 (1):49-58.
    English: In this paper I indicate why I consider 'experimental philosophy' to be good news, though not as good as it could be, and not as all that new. I'll argue that there is no need to restrict experimental philosophy to eliciting intuitions through questionnaires. I'll indicate that good examples of experimental philosophy already exist in Artificial Intelligence and Cognitive Neuroscience. Dutch: Hieronder wil ik proberen aan te geven waarom ik de experimentele filosofie weliswaar als goed nieuws beschouw, maar niet (...)
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  • Old and New Problems in Philosophy of Measurement.Eran Tal - 2013 - Philosophy Compass 8 (12):1159-1173.
    The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...)
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  • Computer Simulations in Science.Eric Winsberg - forthcoming - Stanford Encyclopedia of Philosophy.
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  • How can computer simulations produce new knowledge?Claus Beisbart - 2012 - European Journal for Philosophy of Science 2 (3):395-434.
    It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some (...)
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  • How simulations fail.Patrick Grim, Robert Rosenberger, Adam Rosenfeld, Brian Anderson & Robb E. Eason - 2011 - Synthese 190 (12):2367-2390.
    ‘The problem with simulations is that they are doomed to succeed.’ So runs a common criticism of simulations—that they can be used to ‘prove’ anything and are thus of little or no scientific value. While this particular objection represents a minority view, especially among those who work with simulations in a scientific context, it raises a difficult question: what standards should we use to differentiate a simulation that fails from one that succeeds? In this paper we build on a structural (...)
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  • Franklin, Holmes, and the epistemology of computer simulation.Wendy S. Parker - 2008 - International Studies in the Philosophy of Science 22 (2):165 – 183.
    Allan Franklin has identified a number of strategies that scientists use to build confidence in experimental results. This paper shows that Franklin's strategies have direct analogues in the context of computer simulation and then suggests that one of his strategies—the so-called 'Sherlock Holmes' strategy—deserves a privileged place within the epistemologies of experiment and simulation. In particular, it is argued that while the successful application of even several of Franklin's other strategies (or their analogues in simulation) may not be sufficient for (...)
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  • When is an Ensemble like a Sample?Corey Dethier - 2022 - Synthese 200 (52):1-22.
    Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriately termed “model-based,” and I examine the use of statistics in climate fingerprinting to show (...)
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  • Radical artifactualism.Guilherme Sanches de Oliveira - 2022 - European Journal for Philosophy of Science 12 (2):1-33.
    A powerful idea put forward in the recent philosophy of science literature is that scientific models are best understood as instruments, tools or, more generally, artifacts. This idea has thus far been developed in combination with the more traditional representational approach: accordingly, current artifactualist accounts treat models as representational tools. But artifactualism and representationalism are independent views, and adopting one does not require acceptance of the other. This paper argues that a leaner version of artifactualism, free of representationalist assumptions, is (...)
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  • Simulation and Calibration: Mitigating Uncertainty.Deborah Haar - 2021 - Philosophy of Science 88 (5):985-996.
    Calibrating a simulation is a crucial step for certain kinds of simulation modeling, and it results in a simulation that is epistemically different from its pre- or uncalibrated counterpart. This article discusses how simulation model builders mitigate uncertainty about model parameters that are necessary for modeling through calibration and argues that the simulation outcomes after calibration are physically meaningful and relevant. When evaluating the epistemic status of computer simulations, comparisons between computer simulations and traditional experiments need to consider this important (...)
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  • Capturing the representational and the experimental in the modelling of artificial societies.David Anzola - 2021 - European Journal for Philosophy of Science 11 (3):1-29.
    Even though the philosophy of simulation is intended as a comprehensive reflection about the practice of computer simulation in contemporary science, its output has been disproportionately shaped by research on equation-based simulation in the physical and climate sciences. Hence, the particularities of alternative practices of computer simulation in other scientific domains are not sufficiently accounted for in the current philosophy of simulation literature. This article centres on agent-based social simulation, a relatively established type of simulation in the social sciences, to (...)
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  • Method-Driven Experiments and the Search for Dark Matter.Siska De Baerdemaeker - 2021 - Philosophy of Science 88 (1):124-144.
    Since the discovery of dark matter in the 1980s, multiple experiments have been set up to detect dark matter particles through some other mode than gravity. Particle physicists provide detailed jus...
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  • Racial Attitudes, Accumulation Mechanisms, and Disparities.Ron Mallon - 2021 - Review of Philosophy and Psychology 12 (4):953-975.
    Some psychologists aim to secure a role for psychological explanations in understanding contemporary social disparities, a concern that plays out in debates over the relevance of the Implicit Association Test. Meta-analysts disagree about the predictive validity of the IAT and about the importance of implicit attitudes in explaining racial disparities. Here, I use the IAT to articulate and explore one route to establishing the relevance of psychological attitudes with small effects: an appeal to a process of “accumulation” that aggregates small (...)
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  • Epistemological Framework for Computer Simulations in Building Science Research: Insights from Theory and Practice.Amos Kalua & James Jones - 2020 - Philosophies 5 (4):30.
    Computer simulations are widely used within the area of building science research. Building science research deals with the physical phenomena that affect buildings, including heat and mass transfer, lighting and acoustic transmission. This wide usage of computer simulations, however, is characterized by a divergence in thought on the composition of an epistemological framework that may provide guidance for their deployment in research. This paper undertakes a fundamental review of the epistemology of computer simulations within the context of the philosophy of (...)
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