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  1. Philosophy of Modeling: Neglected Pages of History.Karlis Podnieks - 2018 - Baltic Journal of Modern Computing 6 (3):279–303.
    The work done in the philosophy of modeling by Vaihinger (1876), Craik (1943), Rosenblueth and Wiener (1945), Apostel (1960), Minsky (1965), Klaus (1966) and Stachowiak (1973) is still almost completely neglected in the mainstream literature. However, this work seems to contain original ideas worth to be discussed. For example, the idea that diverse functions of models can be better structured as follows: in fact, models perform only a single function – they are replacing their target systems, but for different purposes. (...)
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  • Affect, behavioural schemas and the proving process.Annie Selden, John Selden & Kerry McKee - 2010 - International Journal for Mathematical Education in Science and Technology 41 (2):199-215.
    In this largely theoretical article, we discuss the relation between a kind of affect, behavioural schemas and aspects of the proving process. We begin with affect as described in the mathematics education literature, but soon narrow our focus to a particular kind of affect – nonemotional cognitive feelings. We then mention the position of feelings in consciousness because that bears on the kind of data about feelings that students can be expected to be able to report. Next we introduce the (...)
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  • Inference during reading.Gail McKoon & Roger Ratcliff - 1992 - Psychological Review 99 (3):440-466.
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  • Language, linguistics and cognition.Giosue Baggio, Michiel van Lambalgen & Peter Hagoort - 2012 - In Ruth M. Kempson, Tim Fernando & Nicholas Asher (eds.), Philosophy of linguistics. Boston: North Holland.
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  • On spatial symbols.William E. Smythe & Paul A. Kolers - 1979 - Behavioral and Brain Sciences 2 (4):568-569.
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  • Naturalistic Cognition: A Research Paradigm for Human-Centered Design.Peter Storkerson - 2010 - Journal of Research Practice 6 (2):Article M12.
    Naturalistic thinking and knowing, the tacit, experiential, and intuitive reasoning of everyday interaction, have long been regarded as inferior to formal reason and labeled primitive, fallible, subjective, superstitious, and in some cases ineffable. But, naturalistic thinking is more rational and definable than it appears. It is also relevant to design. Inquiry into the mechanisms of naturalistic thinking and knowledge can bring its resources into focus and enable designers to create better, human-centered designs for use in real-world settings. This article makes (...)
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  • A neo-Cartesian alternative.David Caplan - 1985 - Behavioral and Brain Sciences 8 (1):6-7.
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  • Cognitive self-organization and neural modularity.Stephen Grossberg - 1985 - Behavioral and Brain Sciences 8 (1):18-19.
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  • Models in science and mental models in scientists and nonscientists.William F. Brewer - 2001 - Mind and Society 2 (2):33-48.
    This paper examines the form of mental representation of scientific theories in scientists and nonscientists. It concludes that images and schemas are not the appropriate form of mental representation for scientific theories but that mental models and perceptual symbols do seem appropriate for representing physical/mechanical phenomena. These forms of mental representation are postulated to have an analogical relation with the world and it is this relationship that gives them strong explanatory power. It is argued that the construct of naïve theories (...)
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  • The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • Precis of the modularity of mind.Jerry A. Fodor - 1985 - Behavioral and Brain Sciences 8 (1):1-42.
    The Modularity of Mind proposes an alternative to the or view of cognitive architecture that has dominated several decades of cognitive science. Whereas interactionism stresses the continuity of perceptual and cognitive processes, modularity theory argues for their distinctness. It is argued, in particular, that the apparent plausibility of New Look theorizing derives from the failure to distinguish between the (correct) claim that perceptual processes are inferential and the (dubious) claim that they are unencapsidated, that is, that they are arbitrarily sensitive (...)
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  • Formal thought disorder and logical form: A symbolic computational model of terminological knowledge.Luis M. Augusto & Farshad Badie - 2022 - Journal of Knowledge Structures and Systems 3 (4):1-37.
    Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational model (...)
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  • Mapping the Visual Icon.Sam Clarke - 2022 - Philosophical Quarterly 72 (3):552-577.
    It is often claimed that pre-attentive vision has an ‘iconic’ format. This is seen to explain pre-attentive vision's characteristically high processing capacity and to make sense of an overlap in the mechanisms of early vision and mental imagery. But what does the iconicity of pre-attentive vision amount to? This paper considers two prominent ways of characterising pre-attentive visual icons and argues that neither is adequate: one approach renders the claim ‘pre-attentive vision is iconic’ empirically false while the other obscures its (...)
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  • Emergence of scientific understanding in real-time ecological research practice.Luana Poliseli - 2020 - History and Philosophy of the Life Sciences 42 (4):1-25.
    Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies (...)
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  • Learning the Concept of Function With Dynamic Visualizations.Tobias Rolfes, Jürgen Roth & Wolfgang Schnotz - 2020 - Frontiers in Psychology 11.
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  • When Can Making a Drawing Hinder Problem Solving? Effect of the Drawing Strategy on Linear Overgeneralizations and Problem Solving.Janina Krawitz & Stanislaw Schukajlow - 2020 - Frontiers in Psychology 11.
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  • Reasoning, rationality, and representation.Wade Munroe - 2020 - Synthese 198 (9):8323-8345.
    Recently, a cottage industry has formed with the goal of analyzing reasoning. The relevant notion of reasoning in which philosophers are expressly interested is fixed through an epistemic functional description: reasoning—whatever it is—is our personal-level, rationally evaluable means of meeting our rational requirements through managing and updating our attitudes. Roughly, the dominant view in the extant literature as developed by Paul Boghossian, John Broome, and others is that reasoning is a rule-governed operation over propositional attitudes that results in a change (...)
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  • Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation.Nicola Angius - 2019 - Minds and Machines 29 (3):397-416.
    The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...)
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  • What is Sustainable Theory? A Luhmannian Perspective on the Science of Conceptual Systems.Vladislav Valentinov & Steven E. Wallis - 2017 - Foundations of Science 22 (4):733-747.
    Sustainability is an important topic for understanding and developing our society. For scholars who want their academic contributions to have an impact, sustainability is important for our conceptual systems. Because our conceptual systems share similarities with our social systems, we may investigate their characteristics to gain insight into how both may be achieved or at least understood. Theories of the humanities as well as the social/behavioral sciences are changing very rapidly. They are fragile and few seem to have any longevity. (...)
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  • Computers Are Syntax All the Way Down: Reply to Bozşahin.William J. Rapaport - 2019 - Minds and Machines 29 (2):227-237.
    A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.
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  • Language as a Necessary Condition for Complex Mental Content: A Review of the Discussion on Spatial and Mathematical Thinking. [REVIEW]Arkadiusz Gut & Robert Mirski - 2018 - Roczniki Filozoficzne 66 (3):33-56.
    In this article we review the discussion over the thesis that language serves as an integrator of contents coming from different cognitive modules. After presenting the theoretical considerations, we examine two strands of empirical research that tested the hypothesis — spatial cognition and mathematical cognition. The idea shared by both of them is that each is composed of two separate modules processing information of a specific kind. For spatial thinking these are geometric information about the location of the object and (...)
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  • Capturing the scientific imagination.Fiora Salis & Roman Frigg - 2019 - In Arnon Levy & Peter Godfrey-Smith (eds.), The Scientific Imagination. New York, US: Oup Usa.
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  • On the demystification of mental imagery.Stephen M. Kosslyn, Steven Pinker, George E. Smith & Steven P. Shwartz - 1979 - Behavioral and Brain Sciences 2 (4):535-548.
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  • Framing-effects approach: A theoretical and methodological critique.Bertram Scheufele - 2004 - Communications 29 (4):401-428.
    The article deals with research on framing effects. First, I will start with classifying different approaches on framing. Subsequently, I will provide a definition of the concepts of frame, schema and framing, expand on framing research conducted so far – both theoretically and operationally. Having this equipment at hand, I will initiate a discussion on studies of framing-effects in terms of theory, methods and empirical results. This discussion leads to the conclusion that studies on framing effects are insufficiently concerned with (...)
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  • Uses of cognitive science to science education.W. Jung - 1993 - Science & Education 2 (1):31-56.
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  • The how, what, and why of mental imagery.Stephen M. Kossyln, Steven Pinker, George E. Smith & Steven P. Shwartz - 1979 - Behavioral and Brain Sciences 2 (4):570-581.
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  • The demands of mental travel: demand characteristics of mental imagery experiments.Charles L. Richman, David B. Mitchell & J. Steven Reznick - 1979 - Behavioral and Brain Sciences 2 (4):564-565.
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  • On demystifying the mental for psychology.Edward Sankowski - 1979 - Behavioral and Brain Sciences 2 (4):565-566.
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  • Al, imagery, and theories.Roger C. Schank - 1979 - Behavioral and Brain Sciences 2 (4):566-566.
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  • The image-like and the language-like.Benny Shanon - 1979 - Behavioral and Brain Sciences 2 (4):566-567.
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  • Metaphor versus reality in the understanding of imagery: the path from function to structure.Peter W. Sheehan - 1979 - Behavioral and Brain Sciences 2 (4):567-568.
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  • On the function of mental imagery.David L. Waltz - 1979 - Behavioral and Brain Sciences 2 (4):569-570.
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  • Imagery without arrays.Geoffrey Hinton - 1979 - Behavioral and Brain Sciences 2 (4):555-556.
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  • Mental visualization in nonlaboratory situations.Ian M. L. Hunter - 1979 - Behavioral and Brain Sciences 2 (4):556-557.
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  • The “thoughtless imagery” controversy.P. N. Johnson-Laird - 1979 - Behavioral and Brain Sciences 2 (4):557-558.
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  • The imagery debate: a controversy over terms and cognitive styles.Janice M. Keenan & Richard K. Olson - 1979 - Behavioral and Brain Sciences 2 (4):558-559.
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  • A conceptual, an experimental, and a modeling question about imagery research.R. Duncan Luce - 1979 - Behavioral and Brain Sciences 2 (4):559-560.
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  • The imprecision of mental imagery.Thomas P. Moran - 1979 - Behavioral and Brain Sciences 2 (4):560-560.
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  • Images, models, and human nature.Ulric Neisser - 1979 - Behavioral and Brain Sciences 2 (4):561-561.
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  • Computational versus operational approaches to imagery.Allan Paivio - 1979 - Behavioral and Brain Sciences 2 (4):561-561.
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  • Imagery theory: not mysterious – just wrong.Zenon Pylyshyn - 1979 - Behavioral and Brain Sciences 2 (4):561-563.
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  • Conscious and nonconscious imagery.Alan Richardson - 1979 - Behavioral and Brain Sciences 2 (4):563-564.
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  • So many models – So little time.Jerome A. Feldman - 1979 - Behavioral and Brain Sciences 2 (4):551-552.
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  • Images, memory, and perception.Alastair Hannay - 1979 - Behavioral and Brain Sciences 2 (4):552-553.
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  • Understanding mental imagery: interpretive metaphors versus explanatory models.Frederick Hayes-Roth - 1979 - Behavioral and Brain Sciences 2 (4):553-554.
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  • Mental Imagery and mystification.John Hell - 1979 - Behavioral and Brain Sciences 2 (4):554-555.
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  • Modeling the mind's eye.Lynn A. Cooper - 1979 - Behavioral and Brain Sciences 2 (4):550-551.
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  • On interpretative processes in imagery.Manuel de Vega - 1979 - Behavioral and Brain Sciences 2 (4):551-551.
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  • Imagining the purpose of imagery.Robert P. Abelson - 1979 - Behavioral and Brain Sciences 2 (4):548-549.
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  • Matters of definition in the demystification of mental imagery.John S. Antrobus - 1979 - Behavioral and Brain Sciences 2 (4):549-550.
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