Feature taxonomy: What type of features do children associate with categories and how do they fare in predicting category judgments?

The present study investigates category intension in school-aged children and adults at two different levels of abstraction (i.e., superordinate and basic level) for two category types (i.e., artefacts and natural kinds). We addressed two critical questions: what kind of features do children and adults generate to define semantic categories and which features predict category membership judgment best at each abstraction level? Overall, participants generated relatively more entity features for natural kinds categories, compared to artefact categories, as well as for basic level categories, compared to superordinate categories. Furthermore, the results showed that older children and adults generated relatively more entity features than younger children. Finally, situation features play the most important role in the prediction of category judgments at both levels of abstraction. Theoretical implications and comparable results from previous studies are described in detail.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children.

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children's category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults.

Native-likeness in second language lexical categorization reflects individual language history and linguistic community norms.

SECOND LANGUAGE LEARNERS FACE A DUAL CHALLENGE IN VOCABULARY LEARNING: First, they must learn new names for the 100s of common objects that they encounter every day. Second, after some time, they discover that these names do not generalize according to the same rules used in their first language. Lexical categories frequently differ between languages (Malt et al., 1999), and successful language learning requires that bilinguals learn not just new words but new patterns for labeling objects. In the present study, Chinese learners of English with varying language histories and resident in two different language settings (Beijing, China and State College, PA, USA) named 67 photographs of common serving dishes (e.g., cups, plates, and bowls) in both Chinese and English. Participants' response patterns were quantified in terms of similarity to the responses of functionally monolingual native speakers of Chinese and English and showed the cross-language convergence previously observed in simultaneous bilinguals (Ameel et al., 2005). For English, bilinguals' names for each individual stimulus were also compared to the dominant name generated by the native speakers for the object. Using two statistical models, we disentangle the effects of several highly interactive variables from bilinguals' language histories and the naming norms of the native speaker community to predict inter-personal and inter-item variation in L2 (English) native-likeness. We find only a modest age of earliest exposure effect on L2 category native-likeness, but importantly, we find that classroom instruction in L2 negatively impacts L2 category native-likeness, even after significant immersion experience. We also identify a significant role of both L1 and L2 norms in bilinguals' L2 picture naming responses.

Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts.

Features are at the core of many empirical and modeling endeavors in the study of semantic concepts. This article is concerned with the delineation of features that are important in natural language concepts and the use of these features in the study of semantic concept representation. The results of a feature generation task in which the exemplars and labels of 15 semantic categories served as cues are described. The importance of the generated features was assessed by tallying the frequency with which they were generated and by obtaining judgments of their relevance. The generated attributes also featured in extensive exemplar by feature applicability matrices covering the 15 different categories, as well as two large semantic domains (that of animals and artifacts). For all exemplars of the 15 semantic categories, typicality ratings, goodness ratings, goodness rank order, generation frequency, exemplar associative strength, category associative strength, estimated age of acquisition, word frequency, familiarity ratings, imageability ratings, and pairwise similarity ratings are described as well. By making these data easily available to other researchers in the field, we hope to provide ample opportunities for continued investigations into the nature of semantic concept representation. These data may be downloaded from the Psychonomic Society's Archive of Norms, Stimuli, and Data, www.psychonomic.org/archive.

Talking about walking: biomechanics and the language of locomotion.

What drives humans around the world to converge in certain ways in their naming while diverging dramatically in others? We studied how naming patterns are constrained by investigating whether labeling of human locomotion reflects the biomechanical discontinuity between walking and running gaits. Similarity judgments of a student locomoting on a treadmill at different slopes and speeds revealed perception of this discontinuity. Naming judgments of the same clips by speakers of English, Japanese, Spanish, and Dutch showed lexical distinctions between walking and running consistent with the perceived discontinuity. Typicality judgments showed that major gait terms of the four languages share goodness-of-example gradients. These data demonstrate that naming reflects the biomechanical discontinuity between walking and running and that shared elements of naming can arise from correlations among stimulus properties that are dynamic and fleeting. The results support the proposal that converging naming patterns reflect structure in the world, not only acts of construction by observers.

Determining the dimensionality in spatial representations of semantic concepts.

When multidimensional scaling solutions are used to study semantic concepts, the dimensionality of the optimal configuration has to be determined. Several strategies have been proposed to choose the appropriate dimensionality. In the present paper, the traditional dimensionality choice criteria were evaluated and compared to a method based on the prediction of an external criterion. Two studies were conducted in which typicality of an exemplar within a semantic concept was predicted from its distance to the concept centroid. In contrast to the low-dimensional solutions selected by the traditional methods, predictions of an external criterion improved with additional dimensions up till dimensionalities that were much higher than what is common in the literature. This suggests that traditional methods underestimate the richness of semantic concepts as revealed in spatial representations derived from similarity measures.

Measures of similarity in models of categorization.

This paper concerns the use of similarities based on geometric distance in models of categorization. Two problematic implications of such similarities are outlined. First, in a comparison between two stimuli, geometric distance implies that matching features are not taken into account. Second, missing features are assumed not to exist. Only nonmatching features enter into calculations of similarity. A new model is constructed that is based on the ALCOVE model (Kruschke, 1992), but it uses a feature-matching similarity measure (see, e.g., Tversky, 1977) rather than a geometric one. It is an on-line model in the sense that both dimensions and exemplars are constructed during the categorization process. The model accounts better than ALCOVE does for data with missing features (Experiments 1 and 2) and at least as well as ALCOVE for a data set without missing features (Nosofsky, Kruschke, & McKinley, 1992). This suggests that, at least for some stimulus materials, similarity in categorization is more akin to a feature-matching procedure than to geometric distance calculation.

Dutch norm data for 13 semantic categories and 338 exemplars.

A data set is described that includes eight variables gathered for 13 common superordinate natural language categories and a representative set of 338 exemplars in Dutch. The category set contains 6 animal categories (reptiles, amphibians, mammals, birds, fish, and insects), 3 artifact categories (musical instruments, tools, and vehicles), 2 borderline artifact-natural-kind categories (vegetables and fruit), and 2 activity categories (sports and professions). In an exemplar and a feature generation task for the category nouns, frequency data were collected. For each of the 13 categories, a representative sample of 5-30 exemplars was selected. For all exemplars, feature generation frequencies, typicality ratings, pairwise similarity ratings, age-of-acquisition ratings, word frequencies, and word associations were gathered. Reliability estimates and some additional measures are presented. The full set of these norms is available in Excel format at the Psychonomic Society Web archive, www.psychonomic.org/archive/.