Cultural Consensus Theory

Cultural Consensus Theory (CCT) is an information pooling methodology for discovering knowledge or beliefs shared by selected groups of individuals. It first appeared in the 1980s as a statistical tool for ethnographic studies in anthropology, and since then it has been greatly expanded for use in many other situations in the social, behavioral, and cognitive sciences. CCT consists of formal cognitive models for different questionnaire designs, for example, true/false, ordered category, or continuous. The data format consists of the responses of group members to each of a series of questionnaire items. CCT models specify the consensus truth for the items as latent parameters, along with other parameters for respondent knowledge level, response bias, and item difficulty. Mixture CCT models have been developed where there may be several subgroups, each with its own set of consensus truths. Bayesian hierarchical inference has been developed for all of the CCT models, and the inference determines if there is evidence for one or more consensus truths in the response data, and if so, it estimates them as well as the other parameters of the model. Freely available software packages exist for conducting the inference.