Theory-based categorization under speeded conditions

It is widely accepted that similarity influences rapid categorization, whereas theories can influence only more leisurely category judgments. In contrast, we argue that it is not the type of knowledge used that determines categorization speed, but rather the complexity of the categorization processes. In two experiments, participants learned four categories of items, each consisting of three causally related features. Participants gave more weight to cause features than to effect features, even under speeded response conditions. Furthermore, the time required to make judgments was equivalent, regardless of whether participants were using causal knowledge or base-rate information. We argue that both causal knowledge and base-rate information, once precompiled during learning, can be used at roughly the same speeds during categorization, thus demonstrating an important parallel between these two types of knowledge.     

A rose in any other font would not smell as sweet: effects of perceptual fluency on categorization

Fluency--the ease with which people process information--is a central piece of information we take into account when we make judgments about the world. Prior research has shown that fluency affects judgments in a wide variety of domains, including frequency, familiarity, and confidence. In this paper, we present evidence that fluency also plays a role in categorization judgments. In Experiment 1, participants judged a variety of different exemplars to be worse category members if they were less fluent (because they were presented in a smaller typeface). In Experiment 2, we found that fluency also affected judgments of feature typicality. In Experiment 3, we demonstrated that the effects of fluency can be reversed when a salient attribution for reduced fluency is available (i.e., the stimuli are hard to read because they were printed by a printer with low toner). In Experiment 4 we replicated these effects using a within-subject design, which ruled out the possibility that the effects were a statistical artifact caused by aggregation of data. We propose a possible mechanism for these effects: if an exemplar and its category are closely related, activation of one will cause priming of the other, leading to increased fluency. Over time, feelings of fluency come to be used as a valid cue that can become confused with more traditional sources of information about category membership.     

When similarity and causality compete in category-based property generalization

Five experiments were performed to investigate the category-based generalization of nonblank properties, properties that were novel but that were attributed to existing category features with causal explanations. Experiments 1-3 tested how such explanations interact with the well-known effects of similarity on such generalizations. The results showed that when the causal explanations were used, standard effects of typicality (Experiment 1), diversity (Experiment 2), or similarity itself (Experiment 3) were almost completely eliminated. Experiments 4 and 5 demonstrated that category-based generalizations exhibit some of the standard properties of causal reasoning; for example, an effect (i.e., a novel category property) is judged to be more prevalent when its cause (i.e., an existing category feature) is also prevalent. These findings suggest that category-based property generalization is often an instance of causal inference.     

The development of causal categorization

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 deterministic (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children's classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults.     

The role of Afrocentric features in person perception: judging by features and categories

Four studies were conducted to test the hypothesis that group-related physical features may directly activate related stereotypes, leading to more stereotypic inferences over and above those resulting from categorization. As predicted, targets with more Afrocentric features were judged as more likely to have traits stereotypic of African Americans. This effect was found with judgments of African Americans and of European Americans. Furthermore, the effect was not eliminated when a more sensitive measure of categorization processes (category accessibility) was used or when the judgement context made category distinctions salient. Of additional interest was the finding that category accessibility independently affected judgment, such that targets who could be more quickly categorized as group members were judged more stereotypically.     

Causal-based property generalization

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 causal-based 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.     

Classification in well-defined and ill-defined categories: evidence for common processing strategies

Early work in perceptual and conceptual categorization assumed that categories had criterial features and that category membership could be determined by logical rules for the combination of features. More recent theories have assumed that categories have an ill-defined structure and have prosposed probabilistic or global similarity models for the verification of category membership. In the experiments reported here, several models of categorization were compared, using one set of categories having criterial features and another set having an ill-defined structure. Schematic faces were used as exemplars in both cases. Because many models depend on distance in a multidimensional space for their predictions, in Experiment 1 a multidimensional scaling study was performed using the faces of both sets as stimuli, In Experiment 2, subjects learned the category membership of faces for the categories having criterial features. After learning, reaction times for category verification and typicality judgments were obtained. Subjects also judged the similarity of pairs of faces. Since these categories had characteristic as well as defining features, it was possible to test the predictions of the feature comparison model (Smith et al.), which asserts that reaction times and typicalities are affected by characteristic features. Only weak support for this model was obtained. Instead, it appeared that subjects developed logical rules for the classification of faces. A characteristic feature affected reaction times only when it was part of the rule system devised by the subject. The procedure for Experiment 3 was like that for Experiment 2, but with ill-defined rather than well-defined categories. The obtained reaction times had high correlations with some of the models for ill-defined categories. However, subjects' performance could best be described as one of feature testing based on a logical rule system for classification. These experiments indicate that whether or not categories have criterial features, subjects attempt to develop a set of feature tests that allow for exemplar classification. Previous evidence supporting probabilistic or similarity models may be interpreted as resulting from subjects' use of the most efficient rules for classification and the averaging of responses for subjects using different sets of rules.     

Explanation and categorization: How “why?” informs “what?”

Recent theoretical and empirical work suggests that explanation and categorization are intimately related. This paper explores the hypothesis that explanations can help structure conceptual representations, and thereby influence the relative importance of features in categorization decisions. In particular, features may be differentially important depending on the role they play in explaining other features or aspects of category membership. Two experiments manipulate whether a feature is explained mechanistically, by appeal to proximate causes, or functionally, by appeal to a function or goal. Explanation type has a significant impact on the relative importance of features in subsequent categorization judgments, with functional explanations reversing previously documented effects of ‘causal status’. The findings suggest that a feature’s explanatory importance can impact categorization, and that explanatory relationships, in addition to causal relationships, are critical to understanding conceptual representation.     

A rule-based categorization deficit in Alzheimer's disease?

This study examined the categorization processes that Alzheimer's disease (AD) patients use during assessments of semantic memory. Rule-based categorization involves the careful, analytic processing of strict criteria to determine category membership, particularly for items from graded categories with ambiguous category membership; similarity-based categorization requires an overall comparison of a test stimulus with a prototype or remembered exemplar of the category and is relatively effective for the rapid categorization of items with unambiguous category membership. To assess these processes in AD, patients were asked to decide the category membership of test stimuli for categories with poorly defined or fuzzy boundaries (e.g., VEGETABLE) and for categories with well-defined boundaries (e.g., FEMALE) and then to judge the representativeness of the test stimulus for its chosen category. A subgroup of AD patients demonstrated a typical pattern of impaired semantic memory compared to healthy control subjects; that is, difficulty deciding the category membership of test items from fuzzy categories. Among these patients, we found no deficit in category membership decisions about items taken from well-defined categories. We also found that AD patients and healthy controls do not differ in their representativeness judgments of items within a correctly judged category. These findings are most consistent with the hypothesis that rule-based categorization difficulty limits semantic memory in AD.     

Why do categorization effects occur in comparative judgment tasks?

Three experiments were conducted to understand what eliminates the symbolic distance effect for reaction times (RTs) when subjects learn that items belong to categories. Artificial city locations were judged, and artificial states served as categories. In Experiment 1, whether or not categories were presented and the amount of categorization practice were manipulated. Only those subjects who had practice categorizing cities into states showed a reduced symbolic distance effect for different-state pairs. Analyses of serial position curves indicated that categorization produced faster RTs to different-as compared with their adjacent same-state pairs and it also produced faster RTs for same-state pairs closer to the category border. The border seems to serve as an anchor and facilitates RTs. In Experiments 2a and 2b, distance judgments were made by subjects who either had or had not categorized artificial cities into states. Subjects who learned categories gave larger estimates of distance between cities belonging to different states than to cities belonging to the same state. Categorization seemed to place cities from different states farther apart in psychological space, making their locations more discriminable. This, along with the use of the category border as an anchor, might explain why categorization effects occur in this location judgment task.     

How two causes are different from one: The use of (un)conditional information in Simpson's paradox

In a causally complex world, two (or more) factors may simultaneously be potential causes of an effect. To evaluate the causal efficacy of a factor, the alternative factors must be controlled for (or conditionalized on). Subjects judged the causal strength of two potential causes of an effect that covaried with each other, thereby setting up a Simpson's paradox--a situation in which causal judgments should vary widely depending on whether or not they are conditionalized on the alternative potential cause. In Experiments 1 (table format) and 2 (trial-by-trial format), the subjects did conditionalize their judgments for one causal factor on a known alternative cause. The subjects also demonstrated that they knew what information was needed to properly make causal judgments when two potential causes are available. In Experiment 3 (trial-by-trial), those subjects who were not told about the causal mechanism by which the alternative cause operated were less likely to conditionalize on it. However, the more a subject recognized the covariation between the alternative cause and the effect, the more the subject conditionalized on it. Such behavior may arise from the interaction between bottom-up and top-down processing.     

Can semi-supervised learning explain incorrect beliefs about categories?

Three experiments with 88 college-aged participants explored how unlabeled experiences—learning episodes in which people encounter objects without information about their category membership—influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then made a large number of unsupervised categorization decisions about new items. In all three experiments, the unsupervised experience altered participants’ implicit and explicit mental category boundaries, their explicit beliefs about the most representative members of each category, and even their memory for the items encountered during the supervised learning phase. These changes were influenced by both the range and frequency distribution of the unlabeled stimuli: mental category boundaries shifted toward the middle of the range and toward the trough of the bimodal distribution of unlabeled items, whereas beliefs about the most representative category members shifted toward the modes of the unlabeled distribution. One consequence of this shift in representations is a false-consensus effect (Experiment 3) where participants, despite receiving very disparate training experiences, show strong agreement in judgments about representativeness and boundary location following unsupervised category judgments.     

The role of explanation in categorization decisions

Research into the role of explanation on the categorization process has yielded conflicting conclusions. Some theorists stress the importance of explanation, arguing that explanations provide a causal structure necessary to the categorization process. Others discount its significance, arguing that explanation is neither necessary nor sufficient for categorization. Experimentally, explanation has shown modest success in accounting for some categories but not others. Across three experiments, we test whether the central features of a category are the ones that capture the most explanatory structure. The objectives of the current study are threefold: to determine the importance of explanation in natural kind and artifact categorization; to understand the implications of feature correlations as they relate to explanation; and to further delineate the benefit of explanation outside of a functional role. Experiment 1 demonstrates that explanation plays a more dominant role in artifact versus natural kind categorization. Experiment 2 provides evidence that correlated features are neither necessary nor sufficient for categorization. Moreover, it demonstrates that, in the absence of correlation, people still rely on explanation for artifacts but not for natural kinds. Experiment 3 tests to what extent functional information underlies explanation in artifact categorization. We demonstrate that functional relations are not necessary for explanatory‐based categorization. Our results, coupled with previous evidence, suggest a dichotomous role for explanation‐based categorization. On the one hand, explanation is virtually ignored when categorizing biological kinds; on the other, explanation fosters artifact categorization. Implications for categorization and category‐specific disorder are considered.     

Effects of processing fluency on comparative performance judgments

Research has shown that performance predictions are biased by the impact of processing fluency. However, existing data are inconclusive with regard to comparative judgments of performance. In five experiments, participants in an easy condition gave more favorable comparative judgments than participants in a difficult condition. Participants judged their performance more favorably if they named colors of non-color words rather than non-matching color words (Experiment 1), if they had to generate six words of a category rather than 12 words (Experiment 2), if they had to run in place for 15 s rather than 2 min (Experiment 3), but the latter result holds only true if participants were not active in sports (Experiment 4). When 67% of the items in a recognition test were old words, participants thought that their recognition performance was better than when 33% of the items were old words, although recognition performance did not differ between groups (Experiment 5). We discuss this result in the light of recent theories about effects of processing fluency on judgments.     

The role of feature type and causal status in 4–5-year-old children's biological categorizations

The present study investigated the role of the causal status of features and feature type in biological categorizations by young children. Study 1 showed that 5-year-olds are more strongly influenced by causal features than effect features; 4-year-olds exhibit no such tendency. There therefore appears to be a conceptual change between the ages of 4 and 5 in the evaluation of the causal relations between features that characterize biological categories. The aim of Study 2 was to identify the nature of the abstract beliefs that underlie children's categorial choices. Results show that 5-year-olds base category choices on causal features only when the status of the cause is associated with an internal feature and not if the feature is merely a surface feature. Children thus use biological knowledge to perform the task.     

The effect of semantic distance in yes/no and go/no-go semantic categorization tasks

The effect of semantic distance (Lund & Burgess, 1996) was examined in three semantic categorization experiments. Experiment 1, a yes/no task that required participants to make animal/nonanimal judgments by responding to both sets of stimuli (Forster & Shen, 1996), revealed no effect of semantic distance. Experiment 2, a go/no-go task that required participants to respond to only the experimental (i.e., nonanimal) items, revealed a large effect of semantic distance. In addition, response latencies were longer and error rates were lower to the experimental items in Experiment 2 than to those in Experiment 1. These findings were replicated in Experiment 3, in which semantic distance and task condition were manipulated within subjects. We conclude that these results are consistent with (1) the view that the go/no-go tasks elicited more extensive processing of the experimental items and (2) a connectionist account of semantic activation, whereby processing is facilitated by the presence of semantic neighbors.     

Categorization as causal reasoning⋆

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 directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory.     

Influence of familiar features on diagnosis: instantiated features in an applied setting

Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can also operate at the level of individual "instantiated" features (Brooks & Hannah, 2006). The present studies examined instantiated features in medical diagnosis. Four "pseudopsychiatric" conditions, each described by four characteristic features, were taught to undergraduate psychology students. They practiced on additional cases, then were tested on new cases with features from two conditions. In Experiment 1, diagnoses associated with familiar features presented one or three times during practice were assigned a higher probability than those with novel features. Experiment 2 showed that the impact of feature frequency was dependent on its consistency with the case diagnosis. Experiment 3 showed that the effect of feature familiarity was not confined to cases with two equiprobable diagnoses. Experiment 4 showed that the effect remained after a 24 hour delay. These four studies demonstrated that features seen in practice have a greater influence on diagnosis than novel synonyms. In fact, seeing a feature once within the appropriate context (a patient case in which it is a member of the primary diagnosis) was sufficient to form a diagnostic association equivalent to instantiations seen four times in a different context. The results of these studies have implications for theories of categorization and for teaching clinical reasoning.