Radiocarbon Data, Bayesian Modeling, and Alternative Historical Frameworks

Abstract

ABSTRACTThis article employs comparative Bayesian chronology building to formally evaluate the quality of a legacy radiocarbon dataset from the southern Appalachian region of the southeastern United States and to interrogate the assumptions that form the basis of the extant chronological narrative for the region. By incorporating alternative assumptions into Bayesian models, a number of alternative chronological frameworks are developed and compared to one another to yield insights into the development of sociopolitical complexity across southern Appalachia between AD 600 and 1600. The treatment of alternative chronological models as working hypotheses concerning the timing, tempo, and nature of sociopolitical transformations makes use of legacy radiocarbon datasets in developing new research trajectories including the encouragement of renewed field- and lab-based investigations. As such, this article provides a case study to illustrate the value of Bayesian chronological modeling in assessing legacy radiocarbon datasets and reevaluating extant chronological frameworks. Beyond initial evaluation of extant datasets and narratives, the methods and procedures outlined below can be used to form baseline models against which newly acquired data can be formally incorporated and interpreted.