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Nancy J. Nersessian [59]Nancy Nersessian [16]Nancy Joan Nersessian [1]NancyJ Nersessian [1]
  1.  34
    Creating Scientific Concepts.Nancy Nersessian - unknown
    How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural (...)
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  2.  92
    Peeking Inside the Black Box: A New Kind of Scientific Visualization.Michael T. Stuart & Nancy J. Nersessian - 2018 - Minds and Machines 29 (1):87-107.
    Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...)
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  3.  36
    Faraday to Einstein: Constructing Meaning in Scientific Theories.Nancy J. Nersessian - 1984 - Kluwer Academic Publishers.
    PARTI The Philosophical Situation: A Critical Appraisal We must begin with the mistake and find out the truth in it. That is, we must uncover the source of ...
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  4.  43
    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.
  5.  34
    Coupling Simulation and Experiment: The Bimodal Strategy in Integrative Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2013 - Studies in History and Philosophy of Science Part C 44 (4a):572-584.
    The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...)
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  6.  12
    Interdisciplinary Problem- Solving: Emerging Modes in Integrative Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2016 - European Journal for Philosophy of Science 6 (3):401-418.
    Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific practices address the (...)
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  7.  70
    How Do Scientists Think? Capturing the Dynamics of Conceptual Change in Science.Nancy Nersessian - 1992 - In R. Giere & H. Feigl (eds.), Cognitive Models of Science. University of Minnesota Press. pp. 3--45.
  8.  26
    Model-Based Reasoning in Conceptual Change.Nancy J. Nersessian - 1999 - In L. Magnani, N. J. Nersessian & P. Thagard (eds.), Model-Based Reasoning in Scientific Discovery. Kluwer/Plenum. pp. 5--22.
  9. Faraday to Einstein: Constructing Meaning in Scientific Theories.Nancy J. Nersessian - 1987 - British Journal for the Philosophy of Science 38 (4):575-577.
     
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  10.  49
    The Cognitive Basis of Model-Based Reasoning in Science.Nancy J. Nersessian - 2002 - In Peter Carruthers, Stephen Stich & Michael Siegal (eds.), The Cognitive Basis of Science. Cambridge University Press. pp. 133--153.
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  11.  21
    Building Cognition: The Construction of Computational Representations for Scientific Discovery.Sanjay Chandrasekharan & Nancy J. Nersessian - 2015 - Cognitive Science 39 (8):1727-1763.
    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery, are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that (...)
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  12. Kuhn, Conceptual Change, and Cognitive Science.Nancy Nersessian - 2003 - In Tom Nickles (ed.), Thomas Kuhn. Cambridge University Press. pp. 179-211.
  13.  12
    Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2018 - History and Philosophy of the Life Sciences 40 (1):17.
    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...)
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  14.  15
    Should Physicists Preach What They Practice?Nancy J. Nersessian - 1995 - Science & Education 4 (3):203-226.
  15.  28
    Modeling Systems-Level Dynamics: Understanding Without Mechanistic Explanation in Integrative Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 49:1-11.
  16.  62
    How Do Engineering Scientists Think? Model‐Based Simulation in Biomedical Engineering Research Laboratories.Nancy J. Nersessian - 2009 - Topics in Cognitive Science 1 (4):730-757.
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  17.  11
    Epistemic Identities in Interdisciplinary Science.Lisa M. Osbeck & Nancy J. Nersessian - 2017 - Perspectives on Science 25 (2):226-260.
    Confronting any science studies or learning sciences researcher in the 21st century is the reality of interdisciplinary science. New hybrid fields1 collaboratively build new concepts, combine models from two or more disciplines and forge inter-reliant relationships among specialists with different skill sets to solve new problems. This paper emerges from our recognition that inescapable psychological factors, including identity dynamics, must be described and analyzed in order to better understand the social and cognitive practices specific to interdisciplinary science. In analysis of (...)
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  18.  15
    Empirical Philosophy of Science: Introducing Qualitative Methods Into Philosophy of Science.Hanne Andersen, Nancy Nersessian & Susann Wagenknecht - unknown
    The book examines the emerging approach of using qualitative methods, such as interviews and field observations, in the philosophy of science. Qualitative methods are gaining popularity among philosophers of science as more and more scholars are resorting to empirical work in their study of scientific practices. At the same time, the results produced through empirical work are quite different from those gained through the kind of introspective conceptual analysis more typical of philosophy. This volume explores the benefits and challenges of (...)
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  19.  41
    In the Theoretician's Laboratory: Thought Experimenting as Mental Modeling.Nancy J. Nersessian - 1992 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1992:291 - 301.
    Thought experiments have played a prominent role in numerous cases of conceptual change in science. I propose that research in cognitive psychology into the role of mental modeling in narrative comprehension can illuminate how and why thought experiments work. In thought experimenting a scientist constructs and manipulates a mental simulation of the experimental situation. During this process, she makes use of inferencing mechanisms, existing representations, and general world knowledge to make realistic transformations from one possible physical state to the next. (...)
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  20.  44
    Diversity as Asset.Andrea Bender, Sieghard Beller & Nancy J. Nersessian - 2015 - Topics in Cognitive Science 7 (4):677-688.
    We begin our commentary by summarizing the commonalities and differences in cognitive phenomena across cultures, as found by the seven papers of this topic. We then assess the commonalities and differences in how our various authors have approached the study of cognitive diversity, and speculate on the need for, and potential of, cross-disciplinary collaboration.
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  21.  77
    Thought Experimenting as Mental Modeling.Nancy J. Nersessian - 2007 - Croatian Journal of Philosophy 7 (2):125-161.
    The paper argues that the practice of thought experintenting enables scientists to follow through the implications of a way of representing nature by simulating an exemplary or representative situation that is feasible within that representation. What distinguishes thought experimenting from logical argument and other forms of propositional reasoning is that reasoning by means of a thought experiment involves constructing and simulating a mental model of a representative situation. Although thought experimenting is a creative part of scientific practice, it is a (...)
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  22.  34
    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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  23. Conceptual Change in Science and in Science Education.Nancy J. Nersessian - 1989 - Synthese 80 (1):163 - 183.
    There is substantial evidence that traditional instructional methods have not been successful in helping students to restructure their commonsense conceptions and learn the conceptual structures of scientific theories. This paper argues that the nature of the changes and the kinds of reasoning required in a major conceptual restructuring of a representation of a domain are fundamentally the same in the discovery and in the learning processes. Understanding conceptual change as it occurs in science and in learning science will require the (...)
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  24.  13
    The Creative Industry of Integrative Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2013 - Mind and Society 12 (1):35-48.
    Integrative systems biology is among the most innovative fields of contemporary science, bringing together scientists from a range of diverse backgrounds and disciplines to tackle biological complexity through computational and mathematical modeling. The result is a plethora of problem-solving techniques, theoretical perspectives, lab-structures and organizations, and identity labels that have made it difficult for commentators to pin down precisely what systems biology is, philosophically or sociologically. In this paper, through the ethnographic investigation of two ISB laboratories, we explore the particular (...)
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  25.  11
    Situating Distributed Cognition.Lisa M. Osbeck & Nancy J. Nersessian - 2014 - Philosophical Psychology 27 (1):1-16.
    We historically and conceptually situate distributed cognition by drawing attention to important similarities in assumptions and methods with those of American ?functional psychology? as it emerged in contrast and complement to controlled laboratory study of the structural components and primitive ?elements? of consciousness. Functional psychology foregrounded the adaptive features of cognitive processes in environments, and adopted as a unit of analysis the overall situation of organism and environment. A methodological implication of this emphasis was, to the extent possible, the study (...)
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  26.  6
    Faraday to Einstein: Constructing Meaning in Scientific Theories.Nancy J. Nersessian - 1985 - Philosophy of Science 52 (4):641-642.
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  27.  41
    Philosophy of and as Interdisciplinarity.Michael Hg Hoffmann, Jan C. Schmidt & Nancy J. Nersessian - 2013 - Synthese 190 (11):1857-1864.
  28.  55
    Model‐Based Reasoning in Distributed Cognitive Systems.Nancy J. Nersessian - 2006 - Philosophy of Science 73 (5):699-709.
    This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive science that construes (...)
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  29. James Robert Brown: Thought Experiments and Platonism. Part Two.Nancy J. Nersessian, Dunja Jutronic, Ksenija Puskaric, Nenad Miscevic, Andreas K. A. Georgiou & James Robert Brown - 2007 - Croatian Journal of Philosophy 7 (20):125-268.
     
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  30.  28
    The Process of Science: Contemporary Philosophical Approaches to Understanding Scientific Practice.Nancy J. Nersessian (ed.) - 1987 - Kluwer Academic Publishers.
    ' this volume will make a significant contribution to a more adequate understanding of the 'nature of scientific knowledge and inquiry' ' ISIS Vol.79,No.1,1988.
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  31. Nomic Concepts, Frames, and Conceptual Change.Hanne Andersen & Nancy J. Nersessian - 2000 - Philosophy of Science 67 (3):241.
  32.  41
    Abstraction Via Generic Modeling in Concept Formation in Science.Nancy J. Nersessian - 2005 - Poznan Studies in the Philosophy of the Sciences and the Humanities 86 (1):117-144.
    Cases where analogy has played a significant role in the formation of a new scientific concept are well-documented. Yet, how is it that genuinely new representations can be constructed from existing representations? It is argued that the process of ‘generic modeling’ enables abstraction of features common to both the domain of the source of the analogy and of the target phenomena. The analysis focuses on James Clerk Maxwell's construction of the electromagnetic field concept. The mathematical representation Maxwell constructed turned out (...)
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  33.  21
    Affective Problem Solving: Emotion in Research Practice.Lisa M. Osbeck & Nancy J. Nersessian - 2011 - Mind and Society 10 (1):57-78.
    This paper presents an analysis of emotional and affectively toned discourse in biomedical engineering researchers’ accounts of their problem solving practices. Drawing from our interviews with scientists in two laboratories, we examine three classes of expression: explicit, figurative and metaphorical, and attributions of emotion to objects and artifacts important to laboratory practice. We consider the overall function of expressions in the particular problem solving contexts described. We argue that affective processes are engaged in problem solving, not as simply tacked onto (...)
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  34.  35
    Aether/Or: The Creation of Scientific Concepts.Nancy J. Nersessian - 1984 - Studies in History and Philosophy of Science Part A 15 (3):175.
  35.  45
    Reasoning From Imagery and Analogy in Scientific Concept Formation.Nancy J. Nersessian - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:41 - 47.
    Concept formation in science is a reasoned process, commensurate with ordinary problem-solving processes. An account of how analogical reasoning and reasoning from imagistic representations generate new scientific concepts is presented. The account derives from case studies of concept formation in science and from computational theories of analogical problem solving in cognitive science. Concept formation by analogy is seen to be a process of increasing abstraction from existing conceptual structures.
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  36.  37
    From Maxwell to Microphysics: Aspects of Electromagnetic Theory in the Last Quarter of the Nineteenth Century. Jed Z. Buchwald.Nancy J. Nersessian - 1987 - Philosophy of Science 54 (3):489-490.
  37.  6
    "Why Wasn't Lorentz Einstein?" An Examination of the Scientific Method of H. A. Lorentz.Nancy J. Nersessian - 1986 - Centaurus 29 (3):205-242.
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  38.  1
    What Has History to Do with Cognition? Interactive Methods for Studying Research Laboratories.Elke Kurz-Milcke, Nancy Nersessian & Wendy Newstetter - 2004 - Journal of Cognition and Culture 4 (3-4):663-700.
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  39. Mental Modeling in Conceptual Change.Nancy J. Nersessian - 2010 - International Journal on Humanistic Ideology 3 (1):11-48.
  40.  9
    Child's Play.Nancy J. Nersessian - 1996 - Philosophy of Science 63 (4):542-546.
  41.  41
    Why is 'Incommensurability' a Problem?Nancy J. Nersessian - 1982 - Acta Biotheoretica 31 (4):205-218.
    The origins of the ‘ incommensurability problem’ and its central aspect, the ‘ meaning variance thesis’ are traced to the successive collapse of several distinctions maintained by the standard empiricist account of meaning in scientific theories. The crucial distinction is that between a conceptual structure and a theory. The ‘thesis’ and the ‘problem’ follow from critiques of this distinction by Duhem, Quine and Feyerabend. It is maintained that, rather than revealing the ‘problem’, the arguments leading to it simply show the (...)
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  42.  33
    Concept Formation and Commensurability.Nancy J. Nersessian - 2001 - In Paul Hoyningen-Huene & Howard Sankey (eds.), Incommensurability and Related Matters. Kluwer Academic Publishers. pp. 275--301.
  43. Preface.Lorenzo Magnani & Nancy J. Nersessian - 2001 - Mind and Society 2 (2):29-32.
  44. Constructive Modeling in Creating Scientific Understanding.Nancy J. Nersessian - 1995 - Science & Education 4:203-226.
  45.  7
    Abstraction Via Generic Modeling in Concept Formation in Science.Nancy J. Nersessian - 2002 - Mind and Society 3 (1):129-154.
    Cases where analogy has played a significant role in the formation of a new scientific concept are well-documented. Yet, how is it that genuinely new representations can be constructed from existing representations? It is argued that the process of ‘generic modeling’ enables abstraction of features common to both the domain of the source of the analogy and of the target phenomena. The analysis focuses on James Clerk Maxwell's construction of the electromagnetic field concept. The mathematical representation Maxwell constructed turned out (...)
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  46.  17
    Preface.Lorenzo Magnani, Nancy Nersessian & Paul Thagard - 1998 - Philosophica 62.
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  47.  69
    Visual Models in Analogical Problem Solving.Jim Davies, Nancy J. Nersessian & Ashok K. Goel - 2005 - Foundations of Science 10 (1):133-152.
    Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about electromagnetism.
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  48.  15
    Forms of Positioning in Interdisciplinary Science Practice and Their Epistemic Effects.Lisa M. Osbeck & Nancy J. Nersessian - 2010 - Journal for the Theory of Social Behaviour 40 (2):136-161.
  49. A Cognitive-Historical Approach to Meaning in Scientific Theories.Nancy J. Nersessian - 1987 - In The Process of Science: Contemporary Philosophical Approaches to Understanding Scientific Practice. Kluwer Academic Publishers.
  50.  19
    Counterfactuals in Science and Engineering.Sanjay Chandrasekharan & Nancy J. Nersessian - 2007 - Behavioral and Brain Sciences 30 (5-6):454-455.
    The notion of mutation is applicable to the generation of novel designs and solutions in engineering and science. This suggests that engineers and scientists have to work against the biases identified in counterfactual thinking. Therefore, imagination appears a lot less rational than claimed in the target article.
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