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  1. An Agent-Based Conception of Models and Scientific Representation.Ronald N. Giere - 2010 - Synthese 172 (2):269–281.
    I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of models. (...)
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  • Explication as a Method of Conceptual Re-Engineering.Georg Brun - 2016 - Erkenntnis 81 (6):1211-1241.
    Taking Carnap’s classic exposition as a starting point, this paper develops a pragmatic account of the method of explication, defends it against a range of challenges and proposes a detailed recipe for the practice of explicating. It is then argued that confusions are involved in characterizing explications as definitions, and in advocating precising definitions as an alternative to explications. Explication is better characterized as conceptual re-engineering for theoretical purposes, in contrast to conceptual re-engineering for other purposes and improving exactness for (...)
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  • What is Understanding? An Overview of Recent Debates in Epistemology and Philosophy of Science.Christoph Baumberger, Claus Beisbart & Georg Brun - 2017 - In Stephen Grimm Christoph Baumberger & Sabine Ammon (eds.), Explaining Understanding: New Perspectives from Epistemolgy and Philosophy of Science. Routledge. pp. 1-34.
    The paper provides a systematic overview of recent debates in epistemology and philosophy of science on the nature of understanding. We explain why philosophers have turned their attention to understanding and discuss conditions for “explanatory” understanding of why something is the case and for “objectual” understanding of a whole subject matter. The most debated conditions for these types of understanding roughly resemble the three traditional conditions for knowledge: truth, justification and belief. We discuss prominent views about how to construe these (...)
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  • Dimensions of Objectual Understanding.Christoph Baumberger & Georg Brun - 2017 - In Stephen Grimm Christoph Baumberger & Sabine Ammon (eds.), Explaining Understanding: New Perspectives from Epistemology and Philosophy of Science. Routledge. pp. 165-189.
    In science and philosophy, a relatively demanding notion of understanding is of central interest: an epistemic subject understands a subject matter by means of a theory. This notion can be explicated in a way which resembles JTB analyses of knowledge. The explication requires that the theory answers to the facts, that the subject grasps the theory, that she is committed to the theory and that the theory is justified for her. In this paper, we focus on the justification condition and (...)
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  • Towards a Knowledge-Based Account of Understanding.Christoph9 Kelp - 2016 - In S. Grimm, C. Baumberger & S. Ammon (eds.), Explaining Understanding. Routledge.
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  • True Enough.Catherine Z. Elgin - 2004 - Philosophical Issues 14 (1):113–131.
    Truth is standardly considered a requirement on epistemic acceptability. But science and philosophy deploy models, idealizations and thought experiments that prescind from truth to achieve other cognitive ends. I argue that such felicitous falsehoods function as cognitively useful fictions. They are cognitively useful because they exemplify and afford epistemic access to features they share with the relevant facts. They are falsehoods in that they diverge from the facts. Nonetheless, they are true enough to serve their epistemic purposes. Theories that contain (...)
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  • Understanding and the Facts.Catherine Z. Elgin - 2007 - Philosophical Studies 132 (1):33 - 42.
    If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a sufficient but not slavish sensitivity (...)
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  • Understanding, Grasping and Luck.Kareem Khalifa - 2013 - Episteme 10 (1):1-17.
    Recently, it has been debated as to whether understanding is a species of explanatory knowledge. Those who deny this claim frequently argue that understanding, unlike knowledge, can be lucky. In this paper I argue that current arguments do not support this alleged compatibility between understanding and epistemic luck. First, I argue that understanding requires reliable explanatory evaluation, yet the putative examples of lucky understanding underspecify the extent to which subjects possess this ability. In the course of defending this claim, I (...)
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  • Understanding Without Justification or Belief.Finnur Dellsén - 2017 - Ratio 30 (3):239-254.
    In recent years there has been a resurgence of interest among epistemologists in the nature of understanding, with some authors arguing that understanding should replace knowledge as the primary focus of epistemology. But what is understanding? According to what is often called the standard view, understanding is a species of knowledge. Although this view has recently been challenged in various ways, even the critics of the standard view have assumed that understanding requires justification and belief. I argue that it requires (...)
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  • Scientific Representation: Against Similarity and Isomorphism.Mauricio Suárez - 2003 - International Studies in the Philosophy of Science 17 (3):225-244.
    I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific representation. I (...)
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  • Understanding Why.Alison Hills - 2015 - Noûs 49 (2):661-688.
    I argue that understanding why p involves a kind of intellectual know how and differsfrom both knowledge that p and knowledge why p (as they are standardly understood).I argue that understanding, in this sense, is valuable.
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  • Logical Foundations of Probability.Arthur W. Burks - 1951 - Journal of Philosophy 48 (17):524-535.
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  • Explanation and Scientific Understanding.Michael Friedman - 1974 - Journal of Philosophy 71 (1):5-19.
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  • The Scientific Image.Michael Friedman - 1982 - Journal of Philosophy 79 (5):274-283.
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  • Logical Foundations of Probability.Rudolf Carnap - 1950 - Chicago, IL, USA: Chicago University of Chicago Press.
    APA PsycNET abstract: This is the first volume of a two-volume work on Probability and Induction. Because the writer holds that probability logic is identical with inductive logic, this work is devoted to philosophical problems concerning the nature of probability and inductive reasoning. The author rejects a statistical frequency basis for probability in favor of a logical relation between two statements or propositions. Probability "is the degree of confirmation of a hypothesis (or conclusion) on the basis of some given evidence (...)
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  • The Scientific Image.William Demopoulos & Bas C. van Fraassen - 1982 - Philosophical Review 91 (4):603.
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  • An Essay on Belief and Acceptance. [REVIEW]Joseph Moore - 1994 - Philosophical Review 103 (4):705.
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  • Logical Foundations of Probability, 2nd Edition.R. Carnap - 1962 - Chicago Univeresity Press.
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  • True Enough.Catherine Z. Elgin - 2017 - Cambridge: MIT Press.
    Science relies on models and idealizations that are known not to be true. Even so, science is epistemically reputable. To accommodate science, epistemology should focus on understanding rather than knowledge and should recognize that the understanding of a topic need not be factive. This requires reconfiguring the norms of epistemic acceptability. If epistemology has the resources to accommodate science, it will also have the resources to show that art too advances understanding.
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  • An Essay on Belief and Acceptance.Louis P. Pojman - 1995 - Philosophy and Phenomenological Research 55 (2):496-498.
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  • Science and Partial Truth: A Unitary Approach to Models and Scientific Reasoning.Newton C. A. Da Costa & Steven French - 2003 - Oxford University Press USA.
    In the past thirty years, two fundamental issues have emerged in the philosophy of science. One concerns the appropriate attitude we should take towards scientific theories--whether we should regard them as true or merely empirically adequate, for example. The other concerns the nature of scientific theories and models and how these might best be represented. In this ambitious book, da Costa and French bring these two issues together by arguing that theories and models should be regarded as partially rather than (...)
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  • Achieving Knowledge: A Virtue-Theoretic Account of Epistemic Normativity.John Greco - 2010 - Cambridge University Press.
    When we affirm that someone knows something, we are making a value judgment of sorts - we are claiming that there is something superior about that person's opinion, or their evidence, or perhaps about them. A central task of the theory of knowledge is to investigate the sort of evaluation at issue. This is the first book to make 'epistemic normativity,' or the normative dimension of knowledge and knowledge ascriptions, its central focus. John Greco argues that knowledge is a kind (...)
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  • No Understanding Without Explanation.Michael Strevens - 2013 - Studies in History and Philosophy of Science Part A 44 (3):510-515.
    Scientific understanding, this paper argues, can be analyzed entirely in terms of a mental act of “grasping” and a notion of explanation. To understand why a phenomenon occurs is to grasp a correct explanation of the phenomenon. To understand a scientific theory is to be able to construct, or at least to grasp, a range of potential explanations in which that theory accounts for other phenomena. There is no route to scientific understanding, then, that does not go by way of (...)
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  • Objectivity, Value Judgment, and Theory Choice.Thomas S. Kuhn - 1977 - In The Essential Tension: Selected Studies in Scientific Tradition and Change. University of Chicago Press. pp. 320--39.
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  • Science and Partial Truth: A Unitary Approach to Models and Scientific Reasoning.Newton C. A. da Costa & Steven French - 2003 - Oup Usa.
    Da Costa and French explore the consequences of adopting a 'pragmatic' notion of truth in the philosophy of science. Their framework sheds new light on issues to do with belief, theory acceptance, and the realism-antirealism debate, as well as the nature of scientific models and their heuristic development.
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  • Scientific Understanding: Truth or Dare?Henk W. de Regt - 2015 - Synthese 192 (12):3781-3797.
    It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...)
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  • Functional Explaining: A New Approach to the Philosophy of Explanation.Daniel A. Wilkenfeld - 2014 - Synthese 191 (14):3367-3391.
    In this paper, I argue that explanations just ARE those sorts of things that, under the right circumstances and in the right sort of way, bring about understanding. This raises the question of why such a seemingly simple account of explanation, if correct, would not have been identified and agreed upon decades ago. The answer is that only recently has it been made possible to analyze explanation in terms of understanding without the risk of collapsing both to merely phenomenological states. (...)
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  • A Priori Knowledge and the Scope of Philosophy.George Bealer - 1996 - Philosophical Studies 81 (2-3):121-142.
    This paper provides a defense of two traditional theses: the Autonomy of Philosophy and the Authority of Philosophy. The first step is a defense of the evidential status of intuitions (intellectual seemings). Rival views (such as radical empiricism), which reject the evidential status of intuitions, are shown to be epistemically self-defeating. It is then argued that the only way to explain the evidential status of intuitions is to invoke modal reliabilism. This theory requires that intuitions have a certain qualified modal (...)
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  • Simulation and Similarity: Using Models to Understand the World.Michael Weisberg - 2013 - Oxford University Press.
    one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...
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  • The Value of Knowledge and the Pursuit of Understanding.Jonathan L. Kvanvig - 2003 - Cambridge University Press.
    Epistemology has for a long time focused on the concept of knowledge and tried to answer questions such as whether knowledge is possible and how much of it there is. Often missing from this inquiry, however, is a discussion on the value of knowledge. In The Value of Knowledge and the Pursuit of Understanding Jonathan Kvanvig argues that epistemology properly conceived cannot ignore the question of the value of knowledge. He also questions one of the most fundamental assumptions in epistemology, (...)
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  • An Essay on Belief and Acceptance.L. Jonathan Cohen - 1992 - New York: Clarendon Press.
    In this incisive new book one of Britain's most eminent philosophers explores the often overlooked tension between voluntariness and involuntariness in human cognition. He seeks to counter the widespread tendency for analytic epistemology to be dominated by the concept of belief. Is scientific knowledge properly conceived as being embodied, at its best, in a passive feeling of belief or in an active policy of acceptance? Should a jury's verdict declare what its members involuntarily believe or what they voluntarily accept? And (...)
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  • Must Understanding Be Coherent?Kareem Khalifa - 2016 - In Stephen Grimm, Christoph Baumberger & Sabine Ammon (eds.), Explaining understanding: new perspectives from epistemology and philosophy of science. London, UK: Routledge. pp. 139-164.
    Several authors suggest that understanding and epistemic coherence are tightly connected. Using an account of understanding that makes no appeal to coherence, I explain away the intuitions that motivate this position. I then show that the leading coherentist epistemologies only place plausible constraints on understanding insofar as they replicate my own account’s requirements. I conclude that understanding is only superficially coherent.
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  • Taming Theory with Thought Experiments: Understanding and Scientific Progress.Michael T. Stuart - 2016 - Studies in History and Philosophy of Science Part A 58:24-33.
    I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, (...)
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  • Agent-Based Simulation and Sociological Understanding.Petri Ylikoski - 2014 - Perspectives on Science 22 (3):318-335.
    This article discusses agent-based simulation (ABS) as a tool of sociological understanding. I argue that agent-based simulations can play an important role in the expansion of explanatory understanding in the social sciences. The argument is based on an inferential account of understanding (Ylikoski 2009, Ylikoski & Kuorikoski 2010), according to which computer simulations increase our explanatory understanding by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. The inferential account also suggests a (...)
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  • A Contextual Approach to Scientific Understanding.Henk W. de Regt & Dennis Dieks - 2005 - Synthese 144 (1):137-170.
    Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...)
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  • The Role of Explanation in Understanding.Kareem Khalifa - 2013 - British Journal for the Philosophy of Science 64 (1):161-187.
    Peter Lipton has argued that understanding can exist in the absence of explanation. We argue that this does not denigrate explanation's importance to understanding. Specifically, we show that all of Lipton's examples are consistent with the idea that explanation is the ideal of understanding, i.e. other modes of understanding ought to be assessed by how well they replicate the understanding provided by a good and correct explanation. We defend this idea by showing that for all of Lipton's examples of non-explanatory (...)
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  • Theoretical Understanding in Science.Mark P. Newman - 2017 - British Journal for the Philosophy of Science 68 (2).
    In this article I develop a model of theoretical understanding in science. This is a philosophical theory that specifies the conditions that are both necessary and sufficient for a scientist to satisfy the construction ‘S understands theory T ’. I first consider how this construction is preferable to others, then build a model of the requisite conditions on the basis of examples from elementary physics. I then show how this model of theoretical understanding can be made philosophically robust and provide (...)
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  • The Value of Understanding.Jonathan Kvanvig - 2009 - In Pritchard, Haddock & MIllar (eds.), Epistemic Value. Oxford: Oxford University Press. pp. 95--112.
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  • The Epistemic, the Cognitive, and the Social.Larry Laudan - 2004 - In Peter Machamer & Gereon Wolters (eds.), Science, values, and objectivity. Pittsburgh, PA: University of Pittsburgh Press. pp. 14-23.
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  • The Value of Cognitive Values.Heather Douglas - 2013 - Philosophy of Science 80 (5):796-806.
    Traditionally, cognitive values have been thought of as a collective pool of considerations in science that frequently trade against each other. I argue here that a finer-grained account of the value of cognitive values can help reduce such tensions. I separate the values into groups, minimal epistemic criteria, pragmatic considerations, and genuine epistemic assurance, based in part on the distinction between values that describe theories per se and values that describe theory-evidence relationships. This allows us to clarify why these values (...)
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  • What Types of Values Enter Simulation Validation and What Are Their Roles?Gertrude Hirsch Hadorn & Christoph Baumberger - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation: Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Cham, Switzerland: pp. 961-979.
    Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic values, such as empirical accuracy and coherence with background knowledge, have the role to assess the credibility of simulation results, whereas, second, cognitive values, such as comprehensiveness of a conceptual model or easy handling of a numerical model, have the role to assess the usefulness of a model for (...)
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  • An Inferential Model of Scientific Understanding.Mark Newman - 2012 - International Studies in the Philosophy of Science 26 (1):1 - 26.
    In this article I argue that two current accounts of scientific understanding are incorrect and I propose an alternative theory. My new account draws on recent research in cognitive psychology which reveals the importance of making causal and logical inferences on the basis of incoming information. To understand a phenomenon we need to make particular kinds of inferences concerning the explanations we are given. Specifically, we come to understand a phenomenon scientifically by developing mental models that incorporate the correct causal (...)
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  • The Epistemic Value of Understanding.Henk W. de Regt - 2009 - Philosophy of Science 76 (5):585-597.
    This article analyzes the epistemic value of understanding and offers an account of the role of understanding in science. First, I discuss the objectivist view of the relation between explanation and understanding, defended by Carl Hempel and J. D. Trout. I challenge this view by arguing that pragmatic aspects of explanation are crucial for achieving the epistemic aims of science. Subsequently, I present an analysis of these pragmatic aspects in terms of ‘intelligibility’ and a contextual account of scientific understanding based (...)
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  • The Goal of Explanation.Stephen R. Grimm - 2010 - Studies in History and Philosophy of Science Part A 41 (4):337-344.
    I defend the claim that understanding is the goal of explanation against various persistent criticisms, especially the criticism that understanding is not truth-connected in the appropriate way, and hence is a merely psychological state. Part of the reason why understanding has been dismissed as the goal of explanation, I suggest, is because the psychological dimension of the goal of explanation has itself been almost entirely neglected. In turn, the psychological dimension of understanding—the Aha! experience, the sense that a certain explanation (...)
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  • What Types of Values Enter Simulation Validation and What Are Their Roles?Gertrude Hirsch Hadorn & Christoph Baumberger - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation - Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Springer. pp. 961-979.
    Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic valuesEpistemic values, such as empirical accuracyAccuracy and coherence with background knowledgeBackground knowledge, have the role to assess the credibilityCredibility of simulation results, whereas, second, cognitive valuesCognitive values, such as comprehensiveness of a conceptual modelConceptual model or easy handling of a numerical model, have the role to assess the usefulness (...)
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  • Cognitive Attitudes and Values in Science.Kevin Elliott & David Willmes - unknown
    We argue that the analysis of cognitive attitudes should play a central role in developing more sophisticated accounts of the proper roles for values in science. First, we show that the major recent efforts to delineate appropriate roles for values in science would be strengthened by making clearer distinctions among cognitive attitudes. Next, we turn to a specific example and argue that a more careful account of the distinction between the attitudes of belief and acceptance can contribute to a better (...)
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  • "Understanding and Transparency".Stephen R. Grimm - 2016 - In Explaining Understanding: New Perspectives From Epistemology and Philosophy of Science. Routledge.
    I explore the extent to which the epistemic state of understanding is transparent to the one who understands. Against several contemporary epistemologists, I argue that it is not transparent in the way that many have claimed, drawing on results from developmental psychology, animal cognition, and other fields.
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  • The Diverse Aims of Science.Angela Potochnik - 2015 - Studies in History and Philosophy of Science Part A 53:71-80.
    There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...)
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  • Scientific Progress: Knowledge Versus Understanding.Finnur Dellsén - 2016 - Studies in History and Philosophy of Science Part A 56:72-83.
    What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the (...)
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  • MUDdy Understanding.Daniel Wilkenfeld - 2017 - Synthese 194 (4).
    This paper focuses on two questions: Is understanding intimately bound up with accurately representing the world? Is understanding intimately bound up with downstream abilities? We will argue that the answer to both these questions is “yes”, and for the same reason-both accuracy and ability are important elements of orthogonal evaluative criteria along which understanding can be assessed. More precisely, we will argue that representational-accuracy and intelligibility are good-making features of a state of understanding. Interestingly, both evaluative claims have been defended (...)
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