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  1. Intentionality, Mind and Folk Psychology.Winand H. Dittrich & Stephen E. G. Lea - 1993 - Behavioral and Brain Sciences 16 (1):39-41.
    The comment addresses central issues of a "theory theory" approach as exemplified in Gopnik' and Goldman's BBS-articles. Gopnik, on the one hand, tries to demonstrate that empirical evidence from developmental psychology supports the view of a "theory theory" in which common sense beliefs are constructed to explain ourselves and others. Focusing the informational processing routes possibly involved we would like to argue that his main thesis (e.g. idea of intentionality as a cognitive construct) lacks support at least for two reasons: (...)
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  • Intentionality and Naturalism.Stephen Stich & Stephen Laurence - 1994 - Midwest Studies in Philosophy 19 (1):159-82.
    ...the deepest motivation for intentional irrealism derives not from such relatively technical worries about individualism and holism as we.
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  • Causal Theories of Mental Content.Robert D. Rupert - 2008 - Philosophy Compass 3 (2):353–380.
    Causal theories of mental content (CTs) ground certain aspects of a concept's meaning in the causal relations a concept bears to what it represents. Section 1 explains the problems CTs are meant to solve and introduces terminology commonly used to discuss these problems. Section 2 specifies criteria that any acceptable CT must satisfy. Sections 3, 4, and 5 critically survey various CTs, including those proposed by Fred Dretske, Jerry Fodor, Ruth Garrett Millikan, David Papineau, Dennis Stampe, Dan Ryder, and the (...)
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  • Self-Ascription Without Qualia: A Case Study.David J. Chalmers - 1993 - Behavioral and Brain Sciences 16 (1):35-36.
    In Section 5 of his interesting article, Goldman suggests that the consideration of imaginary cases can be valuable in the analysis of our psychological concepts. In particular, he argues that we can imagine a system that is isomorphic to us under any functional description, but which lacks qualitative mental states, such as pains and color sensations. Whether or not such a being is empirically possible, it certainly seems to be logically possible, or conceptually coherent. Goldman argues from this possibility to (...)
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  • Knowing Thyself, Knowing the Other: They're Not the Same.Jonathan Schull & J. David Smith - 1992 - Behavioral and Brain Sciences 15 (1):166-167.
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  • Representational Development and Theory-of-Mind Computations.David C. Plaut & Annette Karmiloff-Smith - 1993 - Behavioral and Brain Sciences 16 (1):70-71.
  • Approaches, Assumptions, and Goals in Modeling Cognitive Behavior.Richard E. Pastore & David G. Payne - 1986 - Behavioral and Brain Sciences 9 (4):665-666.
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  • The Role of Concepts in Perception and Inference.David R. Olson & Janet Wilde Astington - 1993 - Behavioral and Brain Sciences 16 (1):65-66.
  • Composition in Distributional Models of Semantics.Jeff Mitchell & Mirella Lapata - 2010 - Cognitive Science 34 (8):1388-1429.
    Vector-based models of word meaning have become increasingly popular in cognitive science. The appeal of these models lies in their ability to represent meaning simply by using distributional information under the assumption that words occurring within similar contexts are semantically similar. Despite their widespread use, vector-based models are typically directed at representing words in isolation, and methods for constructing representations for phrases or sentences have received little attention in the literature. This is in marked contrast to experimental evidence (e.g., in (...)
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  • The Psychology of Abstraction.David Kelley & Janet Krueger - 1984 - Journal for the Theory of Social Behaviour 14 (1):43–67.
  • More on the Ineliminable Intentional: A Reply to Churchland.Richard Double - 1987 - Journal for the Theory of Social Behaviour 17 (2):219–225.
  • The Cognitive Structure of Social Categories.Kathleen Dahlgren - 1985 - Cognitive Science 9 (3):379-398.
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  • Sense Generation: A “Quasi‐Classical” Approach to Concepts and Concept Combination.Bradley Franks - 1995 - Cognitive Science 19 (4):441-505.
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  • A Modular Neural Network Model of Concept Acquisition.Philippe G. Schyns - 1991 - Cognitive Science 15 (4):461-508.
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  • Combining Prototypes: A Selective Modification Model.Edward E. Smith, Daniel N. Osherson, Lance J. Rips & Margaret Keane - 1988 - Cognitive Science 12 (4):485-527.
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  • Efficient Creativity: Constraint‐Guided Conceptual Combination.Fintan J. Costello & Mark T. Keane - 2000 - Cognitive Science 24 (2):299-349.
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  • Conceptual Combination with Prototype Concepts.Edward E. Smith & Daniel N. Osherson - 1984 - Cognitive Science 8 (4):337-361.
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  • The Pathologies of Standard Analytic Epistemology.Michael Bishop & J. D. Trout - 2005 - Noûs 39 (4):696-714.
    Standard Analytic Epistemology (SAE) names a contingently clustered class of methods and theses that have dominated English-speaking epistemology for about the past half-century. The major contemporary theories of SAE include versions of foundationalism, coherentism, reliabilism, and contextualism. While proponents of SAE don’t agree about how to define naturalized epistemology, most agree that a thoroughgoing naturalism in epistemology can’t work. For the purposes of this paper, we will suppose that a naturalistic theory of epistemology takes as its core, as its starting-point, (...)
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  • Knowledge Organization, Categories, and Ad Hoc Groups: Folk Medical Models Among Mexican Migrants in Nashville.Norbert Ross, Jonathan Maupin & Catherine A. Timura - 2011 - Ethos: Journal of the Society for Psychological Anthropology 39 (2):165-188.
  • The Essence of Essentialism.George E. Newman & Joshua Knobe - 2019 - Mind and Language 34 (5):585-605.
    Over the past several decades, psychological essentialism has been an important topic of study, incorporating research from multiple areas of psychology, philosophy and linguistics. At its most basic level, essentialism is the tendency to represent certain concepts in terms of a deeper, unobservable property that is responsible for category membership. Originally, this concept was used to understand people’s reasoning about natural kind concepts, such as TIGER and WATER, but more recently, researchers have identified the emergence of essentialist-like intuitions in a (...)
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  • Neoclassical Concepts.Derek Leben - 2015 - Mind and Language 30 (1):44-69.
    Linguistic theories of lexical semantics support a Neoclassical Theory of concepts, where entities like CAUSE, STATE, and MANNER serve as necessary conditions for the possession of individual event concepts. Not all concepts have a neoclassical structure, and whether or not words participate in regular linguistic patterns such as verbal alternations will be proposed as a probe for identifying whether their corresponding concepts do indeed have such structure. I show how the Neoclassical Theory supplements existing theories of concepts and supports a (...)
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  • A Two‐Stage Model of Category Construction.Woo-Kyoung Ahn & Douglas L. Medin - 1992 - Cognitive Science 16 (1):81-121.
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  • The Logic of Plausible Reasoning: A Core Theory.Allan Collins & Ryszard Michalski - 1989 - Cognitive Science 13 (1):1-49.
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  • On the Interaction of Theory and Data in Concept Learning.Edward J. Wisniewski & Douglas L. Medin - 1994 - Cognitive Science 18 (2):221-281.
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  • Models of Concepts.Benjamin Cohen & Gregory L. Murphy - 1984 - Cognitive Science 8 (1):27-58.
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  • Categorization as Causal Reasoning⋆.Bob Rehder - 2003 - Cognitive Science 27 (5):709-748.
    A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are (...)
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  • Comprehending Complex Concepts.Gregory L. Murphy - 1988 - Cognitive Science 12 (4):529-562.
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  • Cultural Preferences for Formal Versus Intuitive Reasoning.Ara Norenzayan, Edward E. Smith, Beom Jun Kim & Richard E. Nisbett - 2002 - Cognitive Science 26 (5):653-684.
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  • Anthropology in Cognitive Science.Andrea Bender, Edwin Hutchins & Douglas Medin - 2010 - Topics in Cognitive Science 2 (3):374-385.
    This paper reviews the uneven history of the relationship between Anthropology and Cognitive Science over the past 30 years, from its promising beginnings, followed by a period of disaffection, on up to the current context, which may lay the groundwork for reconsidering what Anthropology and (the rest of) Cognitive Science have to offer each other. We think that this history has important lessons to teach and has implications for contemporary efforts to restore Anthropology to its proper place within Cognitive Science. (...)
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  • Artificial Intelligence and Law: How to Get There From Here.L. Thorne Mccarty - 1990 - Ratio Juris 3 (2):189-200.
    . This paper offers a survey of the current state of Artificial Intelligence and Law, and makes recommendations for future research. Two main areas of investigation are discussed: the practical work on intelligent legal information systems, and the theoretical work on computational models of legal reasoning. In both areas, the knowledge representation problem is identified as the most important issue facing this field.
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  • Misconceived Causal Explanations for Emergent Processes.Michelene T. H. Chi, Rod D. Roscoe, James D. Slotta, Marguerite Roy & Catherine C. Chase - 2012 - Cognitive Science 36 (1):1-61.
    Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes’ necks get longer over generations, or how ink dropped into water appears to “flow”). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as being (...)
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  • What Difference Reveals About Similarity.Eyal Sagi, Dedre Gentner & Andrew Lovett - 2012 - Cognitive Science 36 (6):1019-1050.
    Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ—that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, (...)
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  • Human Semi-Supervised Learning.Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu - 2013 - Topics in Cognitive Science 5 (1):132-172.
    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and (...)
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  • Kant and Nonconceptual Content.Robert Hanna - 2005 - European Journal of Philosophy 13 (2):247-290.
  • Are False Beliefs Representative Mental States?Karen Bartsch & David Estes - 1993 - Behavioral and Brain Sciences 16 (1):30-31.
  • The Psychologist's Fallacy.Philip David Zelazo & Douglas Frye - 1993 - Behavioral and Brain Sciences 16 (1):89-90.
  • On Learning New Primitives in the Language of Thought: Reply to Rey.Susan Carey - 2014 - Mind and Language 29 (2):133-166.
    A theory of conceptual development must provide an account of the innate representational repertoire, must characterize how these initial representations differ from the adult state, and must provide an account of the processes that transform the initial into mature representations. In Carey, 2009 (The Origin of Concepts), I defend three theses: 1) the initial state includes rich conceptual representations, 2) nonetheless, there are radical discontinuities between early and later developing conceptual systems, 3) Quinean bootstrapping is one learning mechanism that underlies (...)
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  • Ontological Minimalism About Phenomenology.Susanna Schellenberg - 2011 - Philosophy and Phenomenological Research 83 (1):1-40.
    I develop a view of the common factor between subjectively indistinguishable perceptions and hallucinations that avoids analyzing experiences as involving awareness relations to abstract entities, sense-data, or any other peculiar entities. The main thesis is that hallucinating subjects employ concepts (or analogous nonconceptual structures), namely the very same concepts that in a subjectively indistinguishable perception are employed as a consequence of being related to external, mind-independent objects or property-instances. These concepts and nonconceptual structures are identified with modes of presentation types. (...)
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  • Art Concept Pluralism.Christy Mag Uidhir & P. D. Magnus - 2011 - Metaphilosophy 42 (1-2):83-97.
    Abstract: There is a long tradition of trying to analyze art either by providing a definition (essentialism) or by tracing its contours as an indefinable, open concept (anti-essentialism). Both art essentialists and art anti-essentialists share an implicit assumption of art concept monism. This article argues that this assumption is a mistake. Species concept pluralism—a well-explored position in philosophy of biology—provides a model for art concept pluralism. The article explores the conditions under which concept pluralism is appropriate, and argues that they (...)
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  • Representational Analyticity.Jack C. Lyons - 2005 - Mind and Language 20 (4):392–422.
    The traditional understanding of analyticity in terms of concept containment is revisited, but with a concept explicitly understood as a certain kind of mental representation and containment being read correspondingly literally. The resulting conception of analyticity avoids much of the vagueness associated with attempts to explicate analyticity in terms of synonymy by moving the locus of discussion from the philosophy of language to the philosophy of mind. The account provided here illustrates some interesting features of representations and explains, at least (...)
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  • Memory Errors Reveal a Bias to Spontaneously Generalize to Categories.Shelbie L. Sutherland, Andrei Cimpian, Sarah-Jane Leslie & Susan A. Gelman - 2015 - Cognitive Science 39 (5):1021-1046.
    Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that—beyond simply being able to perform such generalizations—people are biased to generalize to categories, such that they routinely make spontaneous, implicit category generalizations from information that licenses such generalizations. To demonstrate the existence of this bias, we asked participants to perform a task in which category generalizations would distract from the main goal (...)
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  • Making Probabilistic Relational Categories Learnable.Wookyoung Jung & John E. Hummel - 2015 - Cognitive Science 39 (6):1259-1291.
    Theories of relational concept acquisition based on structured intersection discovery predict that relational concepts with a probabilistic structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate the learning of such categories. Experiment 1 showed that changing the task from a category-learning task to choosing the “winning” object in each stimulus greatly facilitated participants' ability to learn probabilistic relational categories. Experiments 2 and 3 further investigated the mechanisms underlying this (...)
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  • 3. Concepts in the Brain.Antonio R. Damasio - 1989 - Mind and Language 4 (1-2):24-28.
  • Two Concepts of Concept.Muhammad ali KhAlidi - 1995 - Mind and Language 10 (4):402-22.
    Two main theories of concepts have emerged in the recent psychological literature: the Prototype Theory (which considers concepts to be self-contained lists of features) and the Theory Theory (which conceives of them as being embedded within larger theoretical networks). Experiments supporting the first theory usually differ substantially from those supporting the second, which suggests that these the· ories may be operating at different levels of explanation and dealing with different entities. A convergence is proposed between the Theory Theory and the (...)
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  • Spiders in the Web of Belief: The Tangled Relations Between Concepts and Theories.Frank C. Keil - 1989 - Mind and Language 4 (1-2):43-50.
  • Three Distinctions About Concepts and Categorization.Edward E. Smith - 1989 - Mind and Language 4 (1-2):57-61.
  • New Inquiries Into Truth and Meaning.Shaun Nichols - 1993 - Mind and Language 8 (1):157-161.
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  • Ordinary Constraints on the Semantics of Living Kinds: A Commonsense Alternative to Recent Treatments of Natural-Object Terms.Scott Atran - 1987 - Mind and Language 2 (1):27-63.
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  • Knowledge Organization, Categories, and Ad Hoc Groups: Folk Medical Models Among Mexican Migrants in Nashville.Norbert Ross, Jonathan Maupin & Catherine A. Timura - 2011 - Ethos: Journal of the Society for Psychological Anthropology 39 (2):165-188.
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  • Animal Concepts: Content and Discontent.Nick Chater & Cecilia Heyes - 1994 - Mind and Language 9 (3):209-246.