Robert Drennan (Ph.D., University of Michigan, 1975) is an archaeologist engaged in the comparative analysis of early complex societies from their beginnings to the enormous diversity of organizational patterns displayed by regional chiefdoms around the world. His research focuses on increasing our understanding of the dynamics of social change by identifying patterned variation in the trajectories of development of early complex societies. Topics emphasized in his research include regional settlement and demography, community structure at all scales, household archaeology, quantitative data analysis, spatial analysis, and GIS. These topics are all involved in his fieldwork in China, Mesoamerica, and northern South America.
Research Description
Comparative Analysis of Trajectories of Chiefdom Development
The sample of archaeologically known early complex societies ("chiefdoms") around the world is now large enough for us to move beyond cultural evolutionary typologies or simplistic dichotomies and develop the more sophisticated and nuanced concepts needed to characterize adequately the considerable variation to be observed. The Chiefdom Datasets Project is compiling a database including dozens of regions whose developmental trajectories can be compared on the basis of systematic analyses of primary archaeological data on settlement, households, burials, and public works. Its aim is to delineate patterns in the highly varied courses these trajectories followed so as to identify and understand more fully the social forces at work in them. Principal collaborators are Christian E. Peterson and C. Adam Berrey.
Early Complex Societies in Northeastern China
The Liaoning Hongshan Period Communities Project (LHPCP) focuses on the emergence and development of Hongshan (4500–3000 BCE) chiefly communities. Ongoing data collection in the area surrounding Niuheliang includes regional-scale settlement survey and study of local communities and households through intensive surface collection and small-scale stratigraphic testing. Similar fieldwork and lab analysis in the Upper Daling region was carried out from 2007 to 2014. The objective is to document the nature of human organization at household, local community, regional polity, and macro-regional scales so as to understand better the societies that produced the ceremonial architecture and elaborate burials that have attracted considerable archaeological attention. Principal collaborators are Christian E. Peterson, Lu Xueming, and Zhu Da. The project is an institutional collaboration between the University of Pittsburgh, the Liaoning Province Institute of Archaeology, and Renmin University of China. The LHPCP builds on work carried out by the Chifeng International Collaborative Archaeological Project between 1998 and 2007, with principal collaborators Katheryn M. Linduff, Zhang Zhongpei, Gideon Shelach, Ta La, Zhu Yanping, Guo Zhizhong, and Teng Mingyu.
Early Complex Societies in Colombia
The Programa de Arqueología Regional en el Alto Magdalena serves as an umbrella for a number of more focused projects whose overall aim is to document the developmental trajectories of the societies that created the archaeologically famous monumental sculpture and ceremonial/burial complexes of the Regional Classic Period (1–900 CE). The PARAM began field data collection in 1993 with regional-scale survey, followed by more intensive investigation of households at a local-community scale with shovel probes and small stratigraphic tests at close intervals. Analysis and publication of results from work through 2006 is nearing completion. The PARAM has subsequently included excavation of residential structures and associated features as well as mapping of structural remains with magnetometry and ground-penetrating radar. Principal collaborators are Víctor González Fernández and Carlos Augusto Sánchez. The PARAM builds on similar work carried out from 1983 to 1992 by the Proyecto Arqueológico Valle de la Plata. Both projects have been institutional collaborations between the University of Pittsburgh, the Universidad de los Andes, and the Instituto Colombiano de Antropología e Historia.
Early Complex Societies in Mesoamerica
The Palo Blanco Project studied Formative period (1500 BCE–250 CE) societies in Mexico's Tehuacán Valley. From 1974 to 1980 it carried out regional-scale survey and excavation at several local communities, following up Richard S. MacNeish's Tehuacán Archaeological-Botanical Project with investigation of the trajectories of development of early sedentary agricultural societies. Excavation of the Middle Formative village of Fábrica San José in 1972–1973 was carried out as part of the Valley of Oaxaca Human Ecology Project, directed by Kent V. Flannery.
Courses
Chiefdoms
Beginning as early as 10,000 years ago human communities of unprecedented scale began to emerge in many regions all around the globe. The process has continued in much more recent times as well. These larger communities, numbering at least a few hundred people, and ranging well up into the thousands, usually (but not always) became supra-local in character. Unequal, or hierarchical, relationships usually (but not always) came to occupy an important place in their social organization. The seminar takes a comparative approach to the social dynamics of this process, using the varied trajectories of chiefdom emergence in different parts of the world as an opportunity to increase our understanding of the forces that have driven this process and given the resulting societies such highly varied characteristics.
Regional Settlement, Communities, and Demography
In the absence of modern communication and transportation technologies, human social communities were constituted in patterns of interaction primarily at local and regional scales. Prehistoric interaction patterns are usually strongly reflected in the way in which a human population distributed itself across a landscape. Thus a central reason for studying ancient settlement patterns is to delineate communities in the past and reconstruct the ways in which they structured interaction of various kinds at different scales. Such an approach leads not only to purely social interaction but also to political organization and the organization of the production and distribution of goods. This seminar focuses on the social, political, and economic interpretation of regional-scale archaeological settlement patterns, once the patterns have been discerned through appropriate means of spatial analysis. All such interpretation rests finally on demographic reconstructions, so approaches to both relative and absolute demographic approximations at the regional scale are considered in depth. Finally, having discussed these features of ancient human organization that settlement analysis can tell us about, we consider how appropriate kinds of information to sustain such conclusions can be collected in the field.
Archeological Data Analysis I
An introduction to quantitative data analysis in archeology, this course covers basic principles of statistics, including exploratory analysis of batches, sampling, significance, t-tests, analysis of variance, regression, chi-quare, and estimating universe means and proportions from samples. The approach is practical, concentrating on understanding these principles so as to put them to work effectively in analyzing archeological data. Much of the statistical work is done by computer. Statistical principles are dealt with in the weekly class, computer applications in the weekly lab. No previous computer experience is required, and no previous math beyond high school algebra is needed. Familiarity with archeology, however, is assumed. This course is open only to graduate students and anthropology majors who are concentrating in archeology and have previously taken other courses in archeology.
Archeological Data Analysis II
Advanced analysis of archeological data, primarily quantitative. This course carries on where the discussion of basic statistical comparison and contrast of artifacts, features, assemblages, and sites in Archeological Data Analysis I leaves off. Topics covered include sampling, data base management, analysis of spatial distributions (GIS), computer graphics, and multivariate statistics such as factor analysis, multidimensional scaling and clustering.