Naming and Categorization in Healthy Participants: Crowded Domains and Blurred Effects of Gender

The study of category-specific effects has produced compelling insights into the structure, organization and functioning of cognitive processes. According to some accounts, the greater intra-category structural similarity for living things (LT) contributes to faster access to superordinate pictorial information, making LT easier to classify than structurally dissimilar items (i.e., nonliving things: NLT). Conversely, LT would be harder to name than NLT, as they must compete with within-domain structurally similar items in order to be properly discriminated. Additionally, it has been reported that men perform better with NLT than women, whereas women surpass men with LT but the reasons for this remain unclear. In the current study, we explored both the visual crowding hypothesis and the effects of gender by testing the performance of 40 healthy participants in classification and naming tasks. Analyses revealed that LT were classified significantly faster than NLT (η p 2 = .11), but named significantly slower (η p 2 = .25). Interestingly, the same results persisted after removing atypical categories that are known to distort the interpretation of data from the analyses. Moreover, we did not find the expected effects of gender. Men were more accurate than women naming NLT (η p 2 = .13), and women did not surpass men in any task.