Search results for 'Categorization' (try it on Scholar)

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  1.  37
    B. A. C. Saunders & J. van Brakel (1997). Are There Nontrivial Constraints on Colour Categorization? Behavioral and Brain Sciences 20 (2):167-179.
    In this target article the following hypotheses are discussed: (1) Colour is autonomous: a perceptuolinguistic and behavioural universal. (2) It is completely described by three independent attributes: hue, brightness, and saturation: (3) Phenomenologically and psychophysically there are four unique hues: red, green, blue, and yellow; (4) The unique hues are underpinned by two opponent psychophysical and/or neuronal channels: red/green, blue/yellow. The relevant literature is reviewed. We conclude: (i) Psychophysics and neurophysiology fail to set nontrivial constraints on colour categorization. (ii) (...)
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  2.  37
    Evan Heit & Stephen P. Nicholson (2016). Missing the Party: Political Categorization and Reasoning in the Absence of Party Label Cues. Topics in Cognitive Science 8 (2):697-714.
    This research addressed theoretical approaches in political science arguing that the American electorate is either poorly informed or dependent on party label cues, by assessing performance on political judgment tasks when party label information is missing. The research materials were created from the results of a national opinion survey held during a national election. The experiments themselves were run on nationally representative samples of adults, identified from another national electoral survey. Participants saw profiles of simulated individuals, including information about demographics (...)
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  3.  48
    Yasmina Jraissati (2013). Proving Universalism Wrong Does Not Prove Relativism Right: Considerations on the Ongoing Color Categorization Debate. Philosophical Psychology (3):1-24.
    For over a century, the question of the relation of language to thought has been extensively discussed in the case of color categorization, where two main views prevail. The relativist view claims that color categories are relative while the universalistic view argues that color categories are universal. Relativists also argue that color categories are linguistically determined, and universalists that they are perceptually determined. Recently, the argument for the perceptual determination of color categorization has been undermined, and the relativist (...)
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  4.  19
    Sung-Joo Lim & Lori L. Holt (2011). Learning Foreign Sounds in an Alien World: Videogame Training Improves Non-Native Speech Categorization. Cognitive Science 35 (7):1390-1405.
    Although speech categories are defined by multiple acoustic dimensions, some are perceptually weighted more than others and there are residual effects of native-language weightings in non-native speech perception. Recent research on nonlinguistic sound category learning suggests that the distribution characteristics of experienced sounds influence perceptual cue weights: Increasing variability across a dimension leads listeners to rely upon it less in subsequent category learning (Holt & Lotto, 2006). The present experiment investigated the implications of this among native Japanese learning English /r/-/l/ (...)
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  5.  18
    Eric Hauser (2011). Generalization: A Practice of Situated Categorization in Talk. [REVIEW] Human Studies 34 (2):183-198.
    This paper analyzes four instances in talk of generalization about people, that is, of using statements about one or more people as the basis of stating something about a category. Generalization can be seen as a categorization practice which involves a reflexive relationship between the generalized-from person or people and the generalized-to category. One thing that is accomplished through generalization is instruction in how to understand the identity of the generalized-from person or people, so in addition to being understood (...)
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  6.  37
    Soonja Choi & Kate Hattrup (2012). Relative Contribution of Perception/Cognition and Language on Spatial Categorization. Cognitive Science 36 (1):102-129.
    This study investigated the relative contribution of perception/cognition and language-specific semantics in nonverbal categorization of spatial relations. English and Korean speakers completed a video-based similarity judgment task involving containment, support, tight fit, and loose fit. Both perception/cognition and language served as resources for categorization, and allocation between the two depended on the target relation and the features contrasted in the choices. Whereas perceptual/cognitive salience for containment and tight-fit features guided categorization in many contexts, language-specific semantics influenced (...) where the two features competed for similarity judgment and when the target relation was tight support, a domain where spatial relations are perceptually diverse. In the latter contexts, each group categorized more in line with semantics of their language, that is, containment/support for English and tight/loose fit for Korean. We conclude that language guides spatial categorization when perception/cognition alone is not sufficient. In this way, language is an integral part of our cognitive domain of space. (shrink)
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  7.  19
    Brett K. Hayes & Bob Rehder (2012). The Development of Causal Categorization. Cognitive Science 36 (6):1102-1128.
    Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were (...)
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  8.  20
    Jennifer Summerville & Barbara Adkins (2007). Enrolling the Citizen in Sustainability: Membership Categorization, Morality and Civic Participation. Human Studies 30 (4):429-446.
    This article examines the common-sense and methodical ways in which “the citizen” is produced and enrolled as an active participant in “sustainable” regional planning. Using Membership Categorization Analysis, we explicate how the categorization procedures in the Foreword of a draft regional planning policy interactionally produce the identity of “the citizen” and “civic values and obligations” in relation to geographic place and institutional categories. Furthermore, we show how positioning practices establish a relationship between authors (government) and readers (citizens) where (...)
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  9.  9
    Peter Eglin & Stephen Hester (1999). “You're All a Bunch of Feminists:” Categorization and the Politics of Terror in the Montreal Massacre. [REVIEW] Human Studies 22 (2-4):253-272.
    Following Sacks's model membership categorization analysis (MCA) of a suicidal person's conclusion 'I have no one to turn to,' the paper examines in MCA terms a political actor's twin conclusions that murder-suicide is a rational course of action. The case in question is the killer's reasoning in the Montreal Massacre as revealed in his reported announcement at the scene (notably 'You're all a bunch of feminists. I hate feminists') and recovered suicide letter (for example, 'For why persevere to exist (...)
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  10.  18
    Yasmina Jraissati (2014). On Color Categorization: Why Do We Name Seven Colors in the Rainbow? Philosophy Compass 9 (6):382-391.
    What makes it the case that we draw the boundary between “blue” and “green” where we draw it? Do we draw this boundary where we draw it because our perceptual system is biologically determined in this way? Or is it culture and language that guide the way we categorize colors? These two possible answers have shaped the historical discussion opposing so-called universalists to relativists. Yet, the most recent theoretical developments on color categorization reveal the limits of such a polarization.
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  11.  11
    Cornelia Zelinsky-Wibbelt (2000). Discourse and the Continuity of Reference: Representing Mental Categorization. Mouton De Gruyter.
    Chapter Introduction This work deals with two contrasting, but mutually interrelated capabilities of the human mind: reference and categorization. ...
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  12.  8
    Bob Rehder (2003). Categorization as Causal Reasoning⋆. Cognitive Science 27 (5):709-748.
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  13.  31
    Paul Egré, Vincent de Gardelle & David Ripley (2013). Vagueness and Order Effects in Color Categorization. Journal of Logic, Language and Information 22 (4):391-420.
    This paper proposes an experimental investigation of the use of vague predicates in dynamic sorites. We present the results of two studies in which subjects had to categorize colored squares at the borderline between two color categories (Green vs. Blue, Yellow vs. Orange). Our main aim was to probe for hysteresis in the ordered transitions between the respective colors, namely for the longer persistence of the initial category. Our main finding is a reverse phenomenon of enhanced contrast (i.e. negative hysteresis), (...)
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  14. Robert Briscoe (forthcoming). Color Categorization. In Derek Brown & Fiona Macpherson (eds.), Routledge Handbook on the Philosophy of Colour. Routledge.
  15. Lena Jayyusi (1984). Categorization and the Moral Order. Routledge and Kegan Paul.
    INTRODUCTION My underlying concern in this work is with the sociological analysis and description of members' practical activities and their practical ...
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  16.  30
    Benjamin M. Rottman, Dedre Gentner & Micah B. Goldwater (2012). Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena. Cognitive Science 36 (5):919-932.
    We investigated the understanding of causal systems categories—categories defined by common causal structure rather than by common domain content—among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the (...)
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  17.  6
    Nancy W. Ingling (1972). Categorization: A Mechanism for Rapid Information Processing. Journal of Experimental Psychology 94 (3):239.
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  18.  7
    Valentina Gliozzi, Julien Mayor, Jon‐Fan Hu & Kim Plunkett (2009). Labels as Features (Not Names) for Infant Categorization: A Neurocomputational Approach. Cognitive Science 33 (4):709-738.
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  19.  20
    Evan Heit & Stephen P. Nicholson (2010). The Opposite of Republican: Polarization and Political Categorization. Cognitive Science 34 (8):1503-1516.
    Two experiments examined the typicality structure of contrasting political categories. In Experiment 1, two separate groups of participants rated the typicality of 15 individuals, including political figures and media personalities, with respect to the categories Democrat or Republican. The relation between the two sets of ratings was negative, linear, and extremely strong, r = −.9957. Essentially, one category was treated as a mirror image of the other. Experiment 2 replicated this result, showing some boundary conditions, and extending the result to (...)
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  20.  1
    Caroline Michel, Olivier Corneille & Bruno Rossion (2007). Race Categorization Modulates Holistic Face Encoding. Cognitive Science 31 (5):911-924.
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  21.  2
    Elizabeth F. Loftus (1973). Category Dominance, Instance Dominance, and Categorization Time. Journal of Experimental Psychology 97 (1):70.
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  22. Shimon Edelman & Sharon Duvdevani-Bar (1997). Similarity-Based Viewspace Interpolation and the Categorization of 3D Objects. In Proc. Edinburgh Workshop on Similarity and Categorization.
    Visual objects can be represented by their similarities to a small number of reference shapes or prototypes. This method yields low-dimensional (and therefore computationally tractable) representations, which support both the recognition of familiar shapes and the categorization of novel ones. In this note, we show how such representations can be used in a variety of tasks involving novel objects: viewpoint-invariant recognition, recovery of a canonical view, estimation of pose, and prediction of an arbitrary view. The unifying principle in all (...)
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  23.  11
    Michelle C. St Clair, Padraic Monaghan & Michael Ramscar (2009). Relationships Between Language Structure and Language Learning: The Suffixing Preference and Grammatical Categorization. Cognitive Science 33 (7):1317-1329.
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  24.  6
    Elizabeth F. Loftus & Ronald W. Scheff (1971). Categorization Norms for Fifty Representative Instances. Journal of Experimental Psychology 91 (2):355.
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  25.  4
    Bob McMurray, Joel L. Dennhardt & Andrew Struck‐Marcell (2008). Context Effects on Musical Chord Categorization: Different Forms of Top‐Down Feedback in Speech and Music? Cognitive Science 32 (5):893-920.
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  26.  2
    Raymond S. Nickerson (1967). Categorization Time with Categories Defined by Disjunctions and Conjunctions of Stimulus Attributes. Journal of Experimental Psychology 73 (2):211.
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  27.  2
    Janet H. Walker (1973). Pronounceability Effects on Word-Nonword Encoding in Categorization and Recognition Tasks. Journal of Experimental Psychology 99 (3):318-322.
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  28. Frank Alvarez-Pereyre (ed.) (2008). Catégories Et Catégorisation: Une Perspective Interdisciplinaire. Peeters.
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  29.  9
    M. T. H. Chi, P. J. Feltovich & R. Glaser (1981). Categorization and Representation of Physics Problems by Experts and Novices. Cognitive Science 5 (2):121-52.
    The representation of physics problems in relation to the organization of physics knowledge is investigated in experts and novices. Four experiments examine the existence of problem categories as a basis for representation; differences in the categories used by experts and novices; differences in the knowledge associated with the categories; and features in the problems that contribute to problem categorization and representation. Results from sorting tasks and protocols reveal that experts and novices begin their problem representations with specifiably different problem (...)
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  30.  31
    Cilia Witteman & Andreas Glöckner (2011). Beyond Dual-Process Models: A Categorisation of Processes Underlying Intuitive Judgement and Decision Making. Thinking and Reasoning 16 (1):1-25.
    Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinction between intuitive and deliberate processes but provide no further differentiation within both categories. We go beyond these models and argue that intuition is not a homogeneous concept, but a label used for different cognitive mechanisms. We suggest that these mechanisms have to be (...)
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  31.  65
    Andreas Glöckner & Cilia Witteman (2010). Beyond Dual-Process Models: A Categorisation of Processes Underlying Intuitive Judgement and Decision Making. Thinking and Reasoning 16 (1):1 – 25.
    Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinction between intuitive and deliberate processes but provide no further differentiation within both categories. We go beyond these models and argue that intuition is not a homogeneous concept, but a label used for different cognitive mechanisms. We suggest that these mechanisms have to be (...)
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  32. Robert Thornberg (2008). A Categorisation of School Rules. Educational Studies 34 (1):25-33.
    The aim of this paper is to investigate and describe the content in school rules by developing a category system of school rules, and thus making the logic behind different types of rules in school explicit. Data were derived from an ethnographic study conducted in two primary schools in Sweden. In order to analyse the data, grounded theory methodology was adapted. The analysis resulted in a category system of school rules, containing the following main categories: (a) relational rules, (b) structuring (...)
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  33.  11
    Jeremy N. Bailenson, Michael S. Shum, Scott Atran, Douglas L. Medin & John D. Coley (2002). A Bird's Eye View: Biological Categorization and Reasoning Within and Across Cultures. Cognition 84 (1):1-53.
    Many psychological studies of categorization and reasoning use undergraduates to make claims about human conceptualization. Generalizability of findings to other populations is often assumed but rarely tested. Even when comparative studies are conducted, it may be challenging to interpret differences. As a partial remedy, in the present studies we adopt a 'triangulation strategy' to evaluate the ways expertise and culturally different belief systems can lead to different ways of conceptualizing the biological world. We use three groups (US bird experts, (...)
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  34.  10
    Y. Coello & Y. DelevoYeturrell (2007). Embodiment, Spatial Categorisation and Action. Consciousness and Cognition 16 (3):667-683.
    Despite the subjective experience of a continuous and coherent external world, we will argue that the perception and categorisation of visual space is constrained by the spatial resolution of the sensory systems but also and above all, by the pre-reflective representations of the body in action. Recent empirical data in cognitive neurosciences will be presented that suggest that multidimensional categorisation of perceptual space depends on body representations at both an experiential and a functional level. Results will also be resumed that (...)
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  35.  6
    David Danks (2010). Theory Unification and Graphical Models in Human Categorization. Causal Learning:173--189.
    Many different, seemingly mutually exclusive, theories of categorization have been proposed in recent years. The most notable theories have been those based on prototypes, exemplars, and causal models. This chapter provides “representation theorems” for each of these theories in the framework of probabilistic graphical models. More specifically, it shows for each of these psychological theories that the categorization judgments predicted and explained by the theory can be wholly captured using probabilistic graphical models. In other words, probabilistic graphical models (...)
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  36.  5
    Douglas L. Medin & Scott Atran (2004). The Native Mind: Biological Categorization and Reasoning in Development and Across Cultures. Psychological Review 111 (4):960-983.
    . This paper describes a cross-cultural and developmental research project on naïve or folk biology, that is, the study of how people conceptualize nature. The combination of domain specificity and cross-cultural comparison brings a new perspective to theories of categorization and reasoning and undermines the tendency to focus on “standard populations.” From the standpoint of mainstream cognitive psychology, we find that results gathered from standard populations in industrialized societies often fail to generalize to humanity at large. For example, similarity-driven (...)
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  37.  80
    Stevan Harnad (2005). To Cognize is to Categorize: Cognition is Categorization. In C. Lefebvre & H. Cohen (eds.), Handbook of Categorization. Elsevier.
    2. Invariant Sensorimotor Features ("Affordances"). To say this is not to declare oneself a Gibsonian, whatever that means. It is merely to point out that what a sensorimotor system can do is determined by what can be extracted from its motor interactions with its sensory input. If you lack sonar sensors, then your sensorimotor system cannot do what a bat's can do, at least not without the help of instruments. Light stimulation affords color vision for those of us with the (...)
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  38. Eric Dietrich (2010). Analogical Insight: Toward Unifying Categorization and Analogy. Cognitive Processing 11 (4):331-.
    The purpose of this paper is to present two kinds of analogical representational change, both occurring early in the analogy-making process, and then, using these two kinds of change, to present a model unifying one sort of analogy-making and categorization. The proposed unification rests on three key claims: (1) a certain type of rapid representational abstraction is crucial to making the relevant analogies (this is the first kind of representational change; a computer model is presented that demonstrates this kind (...)
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  39.  1
    S. John (2014). Patient Preference Predictors, Apt Categorization, and Respect for Autonomy. Journal of Medicine and Philosophy 39 (2):169-177.
    In this paper, I set out two ethical complications for Rid and Wendler’s proposal that a “Patient Preference Predictor” (PPP) should be used to aid decision making about incapacitated patients’ care. Both of these worries concern how a PPP might categorize patients. In the first section of the paper, I set out some general considerations about the “ethics of apt categorization” within stratified medicine and show how these challenge certain PPPs. In the second section, I argue for a more (...)
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  40.  32
    Bence Nanay (2013). Artifact Categorization and the Modal Theory of Artifact Function. Review of Philosophy and Psychology 4 (3):515-526.
    Philosophers and psychologists widely hold that artifact categories – just like biological categories – are individuated by their function. But recent empirical findings in psychology question this assumption. My proposal is to suggest a way of squaring these findings with the central role function should play in individuating artifact categories. But in order to do so, we need to give up on the standard account of artifact function, according to which function is fixed by design, and replace it with a (...)
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  41.  41
    George Psathas (1999). Studying the Organization in Action: Membership Categorization and Interaction Analysis. [REVIEW] Human Studies 22 (2-4):139-162.
    A current set of concerns in ethnomethodology and conversation analysis includes the question of how conversation analysis (CA) can deal with studies of social structure or studies of talk in institutional settings.In this paper a focus is placed on how the accomplishment of "work" and "categorization" are interrelated. Two particular instances are examined: a ski school and a package delivery service. Membership categorization is shown to be a complex, on-going, interactive accomplishment. The parties act in ways that are (...)
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  42.  1
    K. Jameson (2010). Where in the World Color Survey is the Support for Color Categorization Based on the Hering Primaries. In Jonathan D. Cohen & Mohan Matthen (eds.), Color Ontology and Color Science. MIT Press.
    This chapter focuses on a factor widely considered by the standard view to be the basis for color-naming phenomena and explores some plausible, comparatively uninvestigated factors that might underlie color naming. These are illustrated, in part, through a reexamination of World Color Survey data as it has been presented by Kuehni. The aim of this chapter is to examine the appropriateness of the Hering opponent-color construct as a theoretical foundation for explaining patterns of color naming in datasets like the WCS, (...)
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  43. E. Rosch (1978). Principles of Categorization [Електронний Ресурс]/Eleonora Rosch. In Eleanor Rosch & Barbara Lloyd (eds.), Cognition and Categorization. Lawrence Elbaum Associates.
     
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  44.  2
    Kurt Hugenberg, Steven G. Young, Donald F. Sacco & Michael J. Bernstein (2011). Social Categorization Influences Face Perception and Face Memory. In Andy Calder, Gillian Rhodes, Mark Johnson & Jim Haxby (eds.), Oxford Handbook of Face Perception. Oxford University Press.
    Contained in the face is a vast body of social information, both fixed and flexible. Across multiple lines of converging evidence it has become increasingly clear that face processing is subject to one of the most potent and best understood of social cognitive phenomena: social categorization. This article reviews this research at the juncture of social psychology and face perception showing the interplay between social categorization and face processing. It lays out evidence indicating that social categories are extracted (...)
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  45.  21
    Reese M. Heitner (2004). The Cyclical Ontogeny of Ontology: An Integrated Developmental Account of Object and Speech Categorization. Philosophical Psychology 17 (1):45 – 57.
    More than a decade of experimental research confirms that external linguistic information provided in the form of word labels can induce a "mutually exclusive" bias against double naming and lead children to infer the name of novel objects and parts. Linguistic labels have also been shown to encourage more sophisticated reasoning, particularly with respect to superordinate and atypical object categorization. By contrast, however, the inverse possibility that the linguistic labeling of basic-level objects may also developmentally support the kind of (...)
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  46.  18
    James T. Townsend, Kam M. Silva, Jesse Spencer-Smith & Michael J. Wenger (2000). Exploring the Relations Between Categorization and Decision Making with Regard to Realistic Face Stimuli. Pragmatics and Cognitionpragmatics and Cognition 8 (1):83-105.
    Categorization and decision making are combined in a task with photorealistic faces. Two different types of face stimuli were assigned probabilistically into one of two fictitious groups; based on the category, faces were further probabilistically assigned to be hostile or friendly. In Part I, participants are asked to categorize a face into one of two categories, and to make a decision concerning interaction. A Markov model of categorization followed by decision making provides reasonable fits to Part I data. (...)
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  47.  7
    Paula Rubio-Fernández, Bart Geurts & Chris Cummins (forthcoming). Is an Apple Like a Fruit? A Study on Comparison and Categorisation Statements. Review of Philosophy and Psychology:1-24.
    Categorisation models of metaphor interpretation are based on the premiss that categorisation statements and comparison statements are fundamentally different types of assertion. Against this assumption, we argue that the difference is merely a quantitative one: ‘x is a y’ unilaterally entails ‘x is like a y’, and therefore the latter is merely weaker than the former. Moreover, if ‘x is like a y’ licenses the inference that x is not a y, then that inference is a scalar implicature. We defend (...)
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  48.  29
    Scott Atran, Douglas I. Medin & Norbert Ross (2002). Thinking About Biology. Modular Constraints on Categorization and Reasoning in the Everyday Life of Americans, Maya, and Scientists. Mind and Society 3 (2):31-63.
    This essay explores the universal cognitive bases of biological taxonomy and taxonomic inference using cross-cultural experimental work with urbanized Americans and forest-dwelling Maya Indians. A universal, essentialist appreciation of generic species appears as the causal foundation for the taxonomic arrangement of biodiversity, and for inference about the distribution of causally-related properties that underlie biodiversity. Universal folkbiological taxonomy is domain-specific: its structure does not spontaneously or invariably arise in other cognitive domains, like substances, artifacts or persons. It is plausibly an innately-determined (...)
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  49.  15
    Gregory Ashby & Michael B. Casale (2005). Empirical Dissociations Between Rule-Based and Similarity-Based Categorization. Behavioral and Brain Sciences 28 (1):15-16.
    The target article postulates that rule-based and similarity-based categorization are best described by a unitary process. A number of recent empirical dissociations between rule-based and similarity-based categorization severely challenge this view. Collectively, these new results provide strong evidence that these two types of category learning are mediated by separate systems.
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  50.  2
    Jeffrey Stibel (2006). Categorization and Technology Innovation. Pragmatics and Cognition 14 (2):343-356.
    Theories on categorization have led to numerous technical innovations. Starting with artificial intelligence and neural models, scientists have leveraged psychological theories to drive forward innovative technology. More recently, software companies and Internet firms have implemented high technology software developed from cognitive theory. One class of systems rooted in the philosophical tradition stresses the importance of explanation and function. Another focuses on feature similarity and rule-based reasoning. Both approaches have had modest success and solve fundamental problems, but neither has achieved (...)
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