If different languages map words onto referents in different ways, bilinguals must either (a) learn and maintain separate mappings for their two languages or (b) merge them and not be fully native-like in either. We replicated and extended past findings of cross-linguistic differences in word-to-referent mappings for common household objects using Belgian monolingual speakers of Dutch and French. We then examined word-to-referent mappings in Dutch-French bilinguals by comparing the way they named in their two languages. We found that the French and Dutch bilingual naming patterns converged on a common naming pattern, with only minor deviations. Through the mutual influence of the two languages, the category boundaries in each language move towards one another and hence diverge from the boundaries used by the native speakers of either language. Implications for the organization of the bilingual lexicon are discussed.
Two studies investigated how convergence between linguistic representations in Dutch-French bilinguals affects the centers and boundaries of lexical categories for common household objects. In Study 1, correlations between typicality ratings for roughly corresponding categories were higher for bilinguals in their two languages than for monolinguals in each language, indicating that bilingual prototypes converge. In Study 2, fewer dimensions were needed to linearly separate bilingual than monolingual categories, and bilinguals showed fewer violations of similarity-based naming. Implications for theories of the bilingual lexicon are discussed.
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/.
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