Abstract

PIP: In this review of the literature, the author focuses on the changes in demographic anthropology, generally since 1970, with greater emphasis on the literature since 1980. 20 years ago the literature on population in the field of anthropology was sparse, inconsistent, and frequently full of factual and logical errors. Part of the problem was that anthropologists did not apply demographic techniques to their research. In the 1980s, communication between anthropology and demography has increased significantly. Methodological advances in demography have helped anthropologists overcome problems in describing and estimating parameters of populations. New techniques include estimations of demographic parameters from the close study of kinship, computer simulations, model life tables, and techniques in paleodemography. The author discusses microanalysis and includes examples of some of the best known and most detailed quantitative studies of small populations from the 1970s and 1980s. The author then reviews macrostudies where attention is directed to the problems of boundedness of small populations and their rates of change and influence from outside over time, including 1) basic research on concepts; 2) primate population and social organization; 3) paleodemography; 4) population problems in huter-gatherer studies; 5) population problems in archeology; 6) the origin of agriculture; and 7) diet and population. Next the author discusses theoretical overviews of 3 areas of demography: 1) population and demography, 2) population and social structure, and 3) population and cultural evolution. Implications for future research include 1) creating a standard methodology for studying populations; 2) creating a clear vocabulary; 3) publishing in high quality journals; 4) establishing a data bank to encourage secondary analysis of materials and their use in comparative studies; 5) reconsidering and republishing previous research; 6) saving raw data, producing descriptive tables, and making them available for colleagues; and 7) refusing to allow good ideas to be squelched by existing data.