this article. We also thank Denise Hatton, Tisha Baldwin, Joshua Nathan, Helen Sullivan, and Julia Wenzlaff for collecting data. Some of the stimulus materials used in Experiments 1 and 2 are adapted from the stimulus materials used in Rehder and Hastie (1997) and we thank them for inspiring many of the features and objects used in these studies. This project was supported by a National Science Foundation Grant (NSF-SBR 9515085) and a National Institute of Mental Health Grant (RO1 MH57737) given to Woo-kyoung Ahn, a National Science Foundation Graduate Fellowship to Nancy Kim, and a National Institute of Mental Health Postdoctoral Fellowship (MH10888-01A1) to Mary Lassaline

Abstract: Cognitive categories in the geographic realm appear to manifest certain special features as contrasted with categories for objects at surveyable scales. We have argued that these features reflect specific ontological characteristics of geographic objects. This paper presents hypotheses as to the nature of the features mentioned, reviews previous empirical work on geographic categories, and presents the results of pilot experiments that used English-speaking subjects to test our hypotheses. Our experiments show geographic categories to be similar to their non-geographic counterparts in the ways in which they generate instances of different relative frequencies at different levels. Other tests, however, provide preliminary evidence for the existence of important differences in subjects ’ categorizations of geographic and non-geographic objects, and suggest further experimental work especially with regard to the role in cognitive categorization of different types of objectboundaries at different scales.

Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization.

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causalbased generalization (CBG) view included effects of an existing feature’s base rate (Experiment 1), the direction of the causal relations (Experiments 2 and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to-be-generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes. Keywords: Causal-based induction; Generalization; Causal reasoning 1.

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.

this paper to answer." (p. 163)

Abstract not found

Abstract not found

Two experiments examined the impact of causal relations between features on categorization by adults and 5-6-year-old children. Participants learned about artificial categories containing instances with two causally related features and two non-causal 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 deterministic (Experiment 1), but showed additional influences of causal status and centrality when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. These results suggest that the generative model [Rehder, B. (2003). A causalmodel theory of conceptual representation and categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 1141-1159] provides a good account of causal categorization in both children and adults. Children’s Causal Categorization 3 It is well established that causal knowledge plays an important role in adult categorization and

The literature on concept development is highly contentious because there is a lot at stake. The processes that give rise to categories are at the very core of how we understand human cognition. In broad strokes, the debate is about whether categories reflect internal representations that are highly stable symbolic proposition-like and manipulated via logical operators or, whether they are probabilistic, context-dependent, and derived from bundles of correlated features and ordinary processes of perceiving and remembering (for reviews, see, Komatsu, 1992; Murphy & Medin, 1989; E. Smith, 1989; E. Smith & Medin, 1981. The literature appears to cycle through these two classes of accounts, advancing with each pass through but never quite leaving these two general points of view. Many of the contentious issues in the developmental literature on concepts and categories are variants of this debate. Accordingly, this review begins with a brief history of theories of categories. This is as history of back-and-forth transitions between a focus on more the more stable and the more probabilistic aspects of categories and it is a debate that is not resolved. However, by either view, categories result from internal representations that capture the structure in the world. Accordingly, the review of the developmental literature is organized with respect to recent advances in understanding outside-the-mind factors that organize and recruit the cognitive processes that create categories: the statistical regularities in the learning environment, the cognitive tasks and the nested time scales of the internal processes they recruit, and the body which is the interface between the external world and cognition. Back – and – forth theories. 2 Traditionally, categories are viewed as discrete bounded things that are stable over time and context. In this view, categories are enduringly real, object-like, truly out there in the world and also in our heads. Thus, theorists in this tradition write about categories being acquired, discovered, and possessed. The boundedness and stability expected of categories is well exemplified in the following quote from Keil (1994): Shared mental structures are assumed to be constant across repeated categorizations of the same set of instances and different from other categorizations. When I think