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While there have been controversial attempts to link conclusions from sociobiological studies of animal populations to humans, few behavioral scientists or anthropologists have made serious progress. In this work, Austin Hughes presents a unique and well-defined theoretical approach to human social behavior that is rooted in evolutionary biology and sociobiology, and which is additionally viewed as a direct continuation of the structural-functional tradition in anthropological research. Using mathematical and statistical techniques, Hughes applies the principles of kin selection theory--which states that natural selection can favor social acts that increase the fitness of both individuals and their relatives--to anthropological data. Among the topics covered are the subdivision of kin groups, selection of leaders in traditional societies, patronage systems, and the correspondence between social and biological kinship. The author concludes that patterns of concentration of relatedness are more important than average relatedness for predicting social behavior. He also shows that social interactions can often be predicted on the basis of common genetic interest in dependent offspring. The result is a major contribution to the field of behavioral biology.
This work investigates whether the principles of evolutionary biology and kin selection theory can provide a rigorous, predictive framework for understanding complex human social behavior. Austin L. Hughes, a scholar in the field of behavioral biology, bridges the gap between sociobiological animal studies and the structural-functional tradition of anthropology. By utilizing mathematical and statistical modeling, he argues that social interactions are often driven by common genetic interests and that the concentration of relatedness within groups is a primary predictor of social outcomes.
What You Will Find
Experts recognize this text as a significant attempt to formalize the intersection of evolutionary biology and anthropological research. Readers frequently note the technical density of the prose, which requires a foundational understanding of both statistical methods and evolutionary theory.
Page Count:
176
Publication Date:
1988-02-11
Publisher:
Oxford University Press
ISBN-10:
019505234X
ISBN-13:
9780195052343
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