Children's Understanding of Nationality.

The present thesis studies children’s understanding of nationality and how they use this understanding to make predictions about other people’s national group membership and their biases concerning distribution behaviour. The Naive Theory approach provided the theoretical framework for the studies conducted which explored different key concepts within the domain of nationality, namely inclusion criteria (both verbal and visual); nationality constancy; and the relative importance of nationality in other people’s distribution behaviour. The results of the studies demonstrate the use of a naive theory of nationality: at all ages in all studies, children were able to make systematic predictions of people’s nationality and their biases towards members of their own groups. The findings further indicate that the Naive Theory approach, which has not previously been applied to the domain of nationality, enables us to gain much better insight into children’s understanding of nationality, just as it has enabled us to gain insight into children’s cognitive development in many other domains. The studies in the current thesis were conducted in both England and Scotland, with children ranging from six to twelve years of age, and in the final study with both majority and minority group children, as it was thought that there would be significant differences in the way understanding of nationality would develop amongst these groups. Few differences were in fact found between these different groups in terms of their predictions regarding people’s nationality and their biases, indicating that children’s naive theory of nationality develops similarly overall, despite differences in the status occupied by the group. The work presented in this thesis provides new insight into children’s understanding of nationality and highlights their ability to make systematic predictions based on information provided to them, not only about national group memberships, but also what other people’s national biases might be