Search results for 'Models in measurement' (try it on Scholar)

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  1. Alessandro Giordani & Luca Mari (2012). Measurement, Models, and Uncertainty. IEEE Transactions on Instrumentation and Measurement 61 (8):2144 - 2152.score: 129.0
    Against the tradition, which has considered measurement able to produce pure data on physical systems, the unavoidable role played by the modeling activity in measurement is increasingly acknowledged, particularly with respect to the evaluation of measurement uncertainty. This paper characterizes measurement as a knowledge-based process and proposes a framework to understand the function of models in measurement and to systematically analyze their influence in the production of measurement results and their interpretation. To this (...)
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  2. John K. Dagsvik & Stine Røine Hoff (2011). Justification of Functional Form Assumptions in Structural Models: Applications and Testing of Qualitative Measurement Axioms. [REVIEW] Theory and Decision 70 (2):215-254.score: 117.0
    In both theoretical and applied modeling in behavioral sciences, it is common to choose a mathematical specification of functional form and distribution of unobservables on grounds of analytic convenience without support from explicit theoretical postulates. This article discusses the issue of deriving particular qualitative hypotheses about functional form restrictions in structural models from intuitive theoretical axioms. In particular, we focus on a family of postulates known as dimensional invariance. Subsequently, we discuss how specific qualitative postulates can be reformulated so (...)
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  3. Luca Mari, Valentina Lazzarotti & Raffaella Manzini (2009). Measurement in Soft Systems: Epistemological Framework and a Case Study. Measurement 42 (2):241-253.score: 111.0
    Measurement in soft systems generally cannot exploit physical sensors as data acquisition devices. The emphasis in this case is instead on how to choose the appropriate indicators and to combine their values so to obtain an overall result, interpreted as the value of a property, i.e., the measurand, for the system under analysis. This paper aims at discussing the epistemological conditions of the claim that such a process is a measurement, and performance evaluation is the case introduced to (...)
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  4. Alessandro Giordani & Luca Mari (2014). Modeling Measurement: Error and Uncertainty. In Marcel Boumans, Giora Hon & Arthur Petersen (eds.), Error and Uncertainty in Scientific Practice. Pickering & Chatto. 79-96.score: 99.0
    In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and (...)
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  5. Eran Tal (forthcoming). Making Time: A Study in the Epistemology of Measurement. British Journal for the Philosophy of Science.score: 87.0
    This article develops a model-based account of the standardization of physical measurement, taking the contemporary standardization of time as its central case-study. To standardize the measurement of a quantity, I argue, is to legislate the mode of application of a quantity-concept to a collection of exemplary artefacts. Legislation involves an iterative exchange between top-down adjustments to theoretical and statistical models regulating the application of a concept, and bottom-up adjustments to material artefacts in light of remaining gaps. The (...)
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  6. John Bickle (2008). Anna Alexandrova is an Assistant Professor in Philosophy at the University of Missouri St. Louis. Her Research Focuses on the Use of Formal Models for Explanation and Policy Making in Economics and Also on the Measurement of Happiness and Well-Being. Her Recent Papers Are Appearing in Philosophy of Science, Philosophical Psychology, and the Journal. [REVIEW] Economics and Philosophy 24:545-547.score: 81.0
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  7. Paola Cantù (2010). The Role of Epistemological Models in Veronese's and Bettazzi's Theory of Magnitudes. In M. D'Agostino, G. Giorello, F. Laudisa, T. Pievani & C. Sinigaglia (eds.), New Essays in Logic and Philosophy of Science. College Publications.score: 80.0
    The philosophy of mathematics has been accused of paying insufficient attention to mathematical practice: one way to cope with the problem, the one we will follow in this paper on extensive magnitudes, is to combine the `history of ideas' and the `philosophy of models' in a logical and epistemological perspective. The history of ideas allows the reconstruction of the theory of extensive magnitudes as a theory of ordered algebraic structures; the philosophy of models allows an investigation into the (...)
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  8. Eran Tal (2013). Old and New Problems in Philosophy of Measurement. Philosophy Compass 8 (12):1159-1173.score: 77.0
    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 (...)
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  9. Yuh-Jia Chen & Thomas Li-Ping Tang (2006). Attitude Toward and Propensity to Engage in Unethical Behavior: Measurement Invariance Across Major Among University Students. [REVIEW] Journal of Business Ethics 69 (1):77 - 93.score: 72.0
    This research examines business and psychology students’ attitude toward unethical behavior (measured at Time 1) and their propensity to engage in unethical behavior (measured at Time 1 and at Time 2, 4 weeks later) using a 15-item Unethical Behavior measure with five Factors: Abuse Resources, Not Whistle Blowing, Theft, Corruption, and Deception. Results suggested that male students had stronger unethical attitudes and had higher propensity to engage in unethical behavior than female students. Attitude at Time 1 predicted Propensity at Time (...)
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  10. Michael Heidelberger, Models in Fluid Dynamics.score: 71.0
    In this paper, I would like to show that considering technological models as they arise in engineering disciplines can greatly enrich the philosophical perspective on models. In fluid mechanics, (at least) three types of models are distinguished: mathematical, computer and physical models. Very often, the choice of a particular mathematical, computer or physical model highly affects the type of solutions and the computational time needed for it. Technological models not only aim at a correct description (...)
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  11. Roger A. Hegstrom & Fernando Sols (1995). A Model of Quantum Measurement in Josephson Junctions. Foundations of Physics 25 (5):681-700.score: 68.0
    A model for the quantum measurement of the electronic current in a Josephson junction is presented and analyzed. The model is similar to a Stern-Gerlach apparatus, relying on the deflection of a spin-polarized particle beam by the magnetic field created by the Josephson current. The aim is (1) to explore, with the help of a simple model, some general ideas about the nature of the information which can be obtained by measurements upon a quantum system and (2) to find (...)
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  12. Iordanis Kavathatzopoulos & Georgios Rigas (2006). A Measurement Model for Ethical Competence in Business. Journal of Business Ethics Education 3:55-74.score: 68.0
    Ethical Competence Questionnaire-Working Life and Business (ECQ-WLB) is an effort to build an instrument that measures ethical competence in business as a psychological problem-solving and decision-making skill. The questionnaire is constructed in a way that aims to avoid connection to any particular moral philosophical theory. Its theoretical base is the autonomy hypothesis of Piaget. Autonomous reasoning as measured by the questionnaire correlated positively to the level of organizational hierarchy. ECQ-WLB demonstrated satisfying psychometricproperties and reasonable reliability properties. A confirmatory factor analysis (...)
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  13. Ron A. Shapira (1999). Fuzzy Measurement in the Mishnah and the Talmud. Artificial Intelligence and Law 7 (2-3):273-288.score: 67.0
    I discuss the attitude of Jewish law sources from the 2nd–:5th centuries to the imprecision of measurement. I review a problem that the Talmud refers to, somewhat obscurely, as impossible reduction. This problem arises when a legal rule specifies an object by referring to a maximized (or minimized) measurement function, e.g., when a rule applies to the largest part of a divided whole, or to the first incidence that occurs, etc. A problem that is often mentioned is whether (...)
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  14. Margaret Morrison (2009). Models, Measurement and Computer Simulation: The Changing Face of Experimentation. Philosophical Studies 143 (1):33 - 57.score: 65.0
    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 (...)
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  15. Jonathan Baron (2012). The Point of Normative Models in Judgment and Decision Making. Frontiers in Psychology 3.score: 65.0
    The point of normative models in judgment and decision making.
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  16. Peter Rodenburg (2005). Models as Measuring Instruments: Measurement of Duration Dependence of Unemployment. Journal of Economic Methodology 12 (3):407-431.score: 65.0
    Nancy Cartwright views models as blueprints for nomological machines ? machines that, if properly shielded, generate law?like behaviour or regularities. Marcel Boumans has argued that we can look for devices inside models, which enable us to measure aspects of these regularities. Therefore, if models do produce regular behaviour (Cartwright), they might perhaps generate numbers about phenomena in the world, provided we can locate a good measuring device in the model (Boumans). How do they do this? (...)
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  17. Michael B. Mensky (1997). Decoherence in Continuous Measurements: From Models to Phenomenology. [REVIEW] Foundations of Physics 27 (12):1637-1654.score: 63.0
    Decoherence is the name for the complex of phenomena leading to appearance of classical features of quantum systems. In the present paper decoherence in continuous measurements is analyzed with the help of restricted path integrals (RPI) and (equivalently in simple cases) complex Hamiltonians. A continuous measurement results in a readout giving information in the classical form on the evolution of the measured quantum system. The quantum features of the system reveal themselves in the variation of possible measurement readouts. (...)
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  18. Hubert M. Blalock (1986). Multiple Causation, Indirect Measurement and Generalizability in the Social Sciences. Synthese 68 (1):13-36.score: 63.0
    The fact that causal laws in the social sciences are most realistically expressed as both multivariate and stochastic has a number of very important implications for indirect measurement and generalizability. It becomes difficult to link theoretical definitions of general constructs in a one-to-one relationship to research operations, with the result that there is conceptual slippage in both experimental and nonexperimental research. It is argued that problems of this nature can be approached by developing specific multivariate causal models that (...)
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  19. Hubert M. Blalock Jr (1986). Multiple Causation, Indirect Measurement and Generalizability in the Social Sciences. Synthese 68 (1):13 - 36.score: 63.0
    The fact that causal laws in the social sciences are most realistically expressed as both multivariate and stochastic has a number of very important implications for indirect measurement and generalizability. It becomes difficult to link theoretical definitions of general constructs in a one-to-one relationship to research operations, with the result that there is conceptual slippage in both experimental and nonexperimental research. It is argued that problems of this nature can be approached by developing specific multivariate causal models that (...)
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  20. Fred C. Boogerd, Frank J. Bruggeman & Robert C. Richardson (2013). Mechanistic Explanations and Models in Molecular Systems Biology. Foundations of Science 18 (4):725-744.score: 62.0
    Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation (...)
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  21. James R. Griesemer (1990). Modeling in the Museum: On the Role of Remnant Models in the Work of Joseph Grinnell. [REVIEW] Biology and Philosophy 5 (1):3-36.score: 62.0
    Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate (...)
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  22. Lara Huber & Lara Kutschenko (2009). Medicine in a Neurocentric World: About the Explanatory Power of Neuroscientific Models in Medical Research and Practice. [REVIEW] Medicine Studies 1 (4):307-313.score: 62.0
    Medicine in a Neurocentric World: About the Explanatory Power of Neuroscientific Models in Medical Research and Practice Content Type Journal Article Category Editorial Notes Pages 307-313 DOI 10.1007/s12376-009-0036-2 Authors Lara Huber, University Medical Center of the Johannes Gutenberg University Mainz Institute for History, Philosophy and Ethics of Medicine Am Pulverturm 13 55131 Mainz Germany Lara K. Kutschenko, University Medical Center of the Johannes Gutenberg University Mainz Institute for History, Philosophy and Ethics of Medicine Am Pulverturm 13 55131 (...)
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  23. Marcel J. Boumans, Calibration of Models in Experiments.score: 61.0
    The assessment of models in an experiment depends on their material nature and their function in the experiment. Models that are used to make the phenomenon under investigation visible - sensors - are assessed by calibration. However, calibration strategies assume material intervention. The experiment discssed in this paper is an experiment in economics to measure the influence of technology shocks on business cycles. It uses immaterial, mathematical instruments. It appears that calibration did not work for these kinds of (...)
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  24. Axel Gelfert (2009). Rigorous Results, Cross-Model Justification, and the Transfer of Empirical Warrant: The Case of Many-Body Models in Physics. Synthese 169 (3):497 - 519.score: 60.0
    This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map (...)
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  25. Chuang Liu, Fictional Models in Science.score: 60.0
    In this paper, I begin with a discussion of Giere’s recent work arguing against taking models as works of fiction. I then move on to explore a spectrum of scientific models that goes from the obviously fictional to the not so obviously fictional. And then I discuss the modeling of the unobservable and make a case for the idea that despite difficulties of defining them, unobservable systems are modeled in a fundamentally different way than the observable systems. While (...)
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  26. Björn Kralemann & Claas Lattmann (2013). Models as Icons: Modeling Models in the Semiotic Framework of Peirce's Theory of Signs. Synthese 190 (16):3397-3420.score: 60.0
    In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) by (...)
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  27. John J. Furedy & Karl Schiffman (1973). Concurrent Measurement of Autonomic and Cognitive Processes in a Test of the Traditional Discriminative Control Procedure for Pavlovian Electrodermal Conditioning. Journal of Experimental Psychology 100 (1):210.score: 60.0
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  28. Răzvan Diaconescu & Marius Petria (2010). Saturated Models in Institutions. Archive for Mathematical Logic 49 (6):693-723.score: 60.0
    Saturated models constitute one of the powerful methods of conventional model theory, with many applications. Here we develop a categorical abstract model theoretic approach to saturated models within the theory of institutions. The most important consequence is that the method of saturated models becomes thus available to a multitude of logical systems from logic or from computing science. In this paper we define the concept of saturated model at an abstract institution-independent level and develop the fundamental existence (...)
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  29. Ronald H. Nowaczyk, John J. Shaughnessy & Joel Zimmerman (1974). Proactive Interference in Short-Term Retention and the Measurement of Degree of Learning: A New Technique. Journal of Experimental Psychology 103 (1):45.score: 60.0
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  30. Tarja Knuuttila (2011). Scientific Models in Philosophy of Science. International Studies in the Philosophy of Science 24 (4):437-440.score: 59.0
    Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. (...)
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  31. Eran Tal (2012). The Epistemology of Measurement: A Model-Based Account. Dissertation, University of Torontoscore: 59.0
    This work develops an epistemology of measurement, that is, an account of the conditions under which measurement and standardization methods produce knowledge as well as the nature, scope, and limits of this knowledge. I focus on three questions: (i) how is it possible to tell whether an instrument measures the quantity it is intended to? (ii) what do claims to measurement accuracy amount to, and how might such claims be justified? (iii) when is disagreement among instruments a (...)
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  32. Chuang Liu (2004). Approximations, Idealizations, and Models in Statistical Mechanics. Erkenntnis 60 (2):235-263.score: 59.0
    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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  33. Steffen Ducheyne (2005). Mathematical Models in Newton's Principia: A New View of the 'Newtonian Style'. International Studies in the Philosophy of Science 19 (1):1 – 19.score: 59.0
    In this essay I argue against I. Bernard Cohen's influential account of Newton's methodology in the Principia: the 'Newtonian Style'. The crux of Cohen's account is the successive adaptation of 'mental constructs' through comparisons with nature. In Cohen's view there is a direct dynamic between the mental constructs and physical systems. I argue that his account is essentially hypothetical-deductive, which is at odds with Newton's rejection of the hypothetical-deductive method. An adequate account of Newton's methodology needs to show how Newton's (...)
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  34. R. M. Nugayev (1987). The Genesis and Structure of Models in the Modern Theory of Gravity. International Studies in the Philosophy of Science 2 (1):84 – 104.score: 59.0
    INTERNATIONAL STUDIES IN THE PHILOSOPHY OF SCIENCE Vol. 2, number 1, Autumn 1987, pp. 84-104. R.M. Nugayev. The genesis and structure of models in the modern theory of gravity. Abstract. The analysis of theory-choice problem in modern theory of gravity necessitates consideration of the genesis and the structure of the systems of gravitational abstract objects. My approach to physical theory structure uses and develops the ideas of V.S.Stepin. The basic equations of general relativity - Einstein’s equations – are shown (...)
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  35. Diderik Batens (2000). Minimally Abnormal Models in Some Adaptive Logics. Synthese 125 (1-2):5-18.score: 59.0
    In an adaptive logic APL, based on a (monotonic) non-standardlogic PL the consequences of can be defined in terms ofa selection of the PL-models of . An important property ofthe adaptive logics ACLuN1, ACLuN2, ACLuNs1, andACLuNs2 logics is proved: whenever a model is not selected, this isjustified in terms of a selected model (Strong Reassurance). Theproperty fails for Priest's LP m because its way of measuring thedegree of abnormality of a model is incoherent – correcting thisdelivers the property.
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  36. Hidde de Jong, Nicolaas Mars & Paul van der Vet (1999). Computer-Supported Resolution of Measurement Conflicts: A Case-Study in Materials Science. [REVIEW] Foundations of Science 4 (4):427-461.score: 59.0
    Resolving conflicts between different measurements ofa property of a physical system may be a key step in a discoveryprocess. With the emergence of large-scale databases and knowledgebases with property measurements, computer support for the task ofconflict resolution has become highly desirable. We will describe amethod for model-based conflict resolution and the accompanyingcomputer tool KIMA, which have been applied in a case-study inmaterials science. In order to be a useful aid to scientists, the toolneeds to be integrated with other tools in (...)
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  37. L. Wolpert (2009). Review of "Animal Models in the Light of Evolution" by Niall Shanks, Ph.D., and C. Ray Greek, M.D. [REVIEW] Philosophy, Ethics, and Humanities in Medicine 5 (1):12-12.score: 59.0
    Animal Models in the Light of Evolution provides persuasive evidence that animal models should be used with great caution when applying the results to human diseases. Mice and other model animals are both similar and different, in their biology, to humans.
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  38. Darrell P. Rowbottom (2009). Models in Biology and Physics: What's the Difference? Foundations of Science 14 (4):281-294.score: 58.0
    In Making Sense of Life , Keller emphasizes several differences between biology and physics. Her analysis focuses on significant ways in which modelling practices in some areas of biology, especially developmental biology, differ from those of the physical sciences. She suggests that natural models and modelling by homology play a central role in the former but not the latter. In this paper, I focus instead on those practices that are importantly similar, from the point of view of epistemology and (...)
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  39. Jay Odenbaugh (2005). Idealized, Inaccurate but Successful: A Pragmatic Approach to Evaluating Models in Theoretical Ecology. [REVIEW] Biology and Philosophy 20 (2-3):231-255.score: 58.0
    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, (...)
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  40. Roberta Sebastiani, Francesca Montagnini & Daniele Dalli (2013). Ethical Consumption and New Business Models in the Food Industry. Evidence From the Eataly Case. Journal of Business Ethics 114 (3):473-488.score: 58.0
    Individual and collective ethical stances regarding ethical consumption and related outcomes are usually seen as both a form of concern about extant market offerings and as opportunities to develop new offerings. In this sense, demand and supply are traditionally portrayed as interacting dialectically on the basis of extant business models. In general, this perspective implicitly assumes the juxtaposition of demand side ethical stances and supply side corporate initiatives. The Eataly story describes, however, a different approach to market transformation; in (...)
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  41. Brian Riordan & Michael N. Jones (2011). Redundancy in Perceptual and Linguistic Experience: Comparing Feature-Based and Distributional Models of Semantic Representation. Topics in Cognitive Science 3 (2):303-345.score: 57.0
    Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We (...)
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  42. J. Kleijnen (2011). Ethical Issues in Engineering Models: An Operations Researcher's Reflections. Science and Engineering Ethics 17 (3):539-552.score: 57.0
    This article starts with an overview of the author’s personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; e.g., case-studies on nuclear waste, water management, sustainable ecology, military tactics, and animal welfare. All these case studies employ computer simulation models. In general, models are meant to solve practical problems, which may have ethical implications for the various stakeholders; namely, the modelers, the clients, and the public at large. The article further presents an overview (...)
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  43. Juan Botella, Huiling Huang & Manuel Suero (2013). Multinomial Tree Models for Assessing the Status of the Reference in Studies of the Accuracy of Tools for Binary Classification. Frontiers in Psychology 4.score: 57.0
    Studies that evaluate the accuracy of binary classification tools are needed. Such studies provide 2x2 cross-classifications of test outcomes and the categories according to an unquestionable reference (or gold standard). However, sometimes a suboptimal reliability reference is employed. Several methods have been proposed to deal with studies where the observations are cross-classified with an imperfect reference. These methods require that the status of the reference, as a gold standard or as an imperfect reference, is known. In this paper a procedure (...)
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  44. Sibylle C. Herholz Emily B. J. Coffey (2013). Task Decomposition: A Framework for Comparing Diverse Training Models in Human Brain Plasticity Studies. Frontiers in Human Neuroscience 7.score: 57.0
    Training studies, in which the structural or functional neurophysiology is compared before and after expertise is acquired, are increasingly being used as models for understanding the human brain’s potential for reorganization. It is proving difficult to use these results to answer basic and important questions like how task training leads to both specific and general changes in behaviour and how these changes correspond with modifications in the brain. The main culprit is the diversity of paradigms used as complex task (...)
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  45. Andrew Sutton (2006). Measures and Models in Developmental Psychology∗. Educational Studies 6 (2):111-126.score: 57.0
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  46. Daniel A. Weiskopf (2011). Models and Mechanisms in Psychological Explanation. Synthese 183 (3):313-338.score: 56.0
    Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of (...)
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  47. Sylvia Wenmackers & Danny E. P. Vanpoucke (2012). Models and Simulations in Material Science: Two Cases Without Error Bars. Statistica Neerlandica 66 (3):339–355.score: 56.0
    We discuss two research projects in material science in which the results cannot be stated with an estimation of the error: a spectroscopic ellipsometry study aimed at determining the orientation of DNA molecules on diamond and a scanning tunneling microscopy study of platinum-induced nanowires on germanium. To investigate the reliability of the results, we apply ideas from the philosophy of models in science. Even if the studies had reported an error value, the trustworthiness of the result would not depend (...)
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  48. Mauro Dorato & Laura Felline (2010). Structural Explanations in Minkowski Spacetime: Which Account of Models? In V. Petkov (ed.), Space, Time, and Spacetime. Springer. 193-207.score: 56.0
    In this paper we argue that structural explanations are an effective way of explaining well known relativistic phenomena like length contraction and time dilation, and then try to understand how this can be possible by looking at the literature on scientific models. In particular, we ask whether and how a model like that provided by Minkowski spacetime can be said to represent the physical world, in such a way that it can successfully explain physical phenomena structurally. We conclude by (...)
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  49. Jay Odenbaugh, Models in Biology.score: 56.0
    In recent years, there has much attention given by philosophers to the ubiquitous role of models and modeling in the biological sciences. Philosophical debates has focused on several areas of discussion. First, what are models in the biological sciences? The term ‘model’ is applied to mathematical structures, graphical displays, computer simulations, and even concrete organisms. Is there an account which unifies these disparate structures? Second, scientists routinely distinguish between theories and models; however, this distinction is more difficult (...)
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