The Probabilistic Threshold

A formalization of the Threshold Theory, called the Probabilistic Threshold Model, is introduced. According to the Threshold Theory semantic categorization decisions come about through the placement of a threshold criterion along a dimension that represents items’ similarity to the category representation. The adequacy of this theory is assessed by applying the Probabilistic Threshold Model to categorization data for eight natural language categories and subjecting it to a formal test. In validating the model special care is given to its ability to account for interand intra-individual differences in categorization and their relationship with item typicality. Extensions of the Probabilistic Threshold Model that can be used to uncover the nature of category representations and the sources of categorization differences are discussed.