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Kinship Based Demographic Simulation of Societal Processes

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Abstract

The social boundaries of small scale human societies are defined through culturally defined kin relations that transcend the specifics of the genealogical relationships produced through procreation. Kinship knowledge is culturally defined, distributed knowledge that provides structure for the persons produced through demographic processes. However, the interplay between the demographic system and the cultural system has been difficult to model. Genealogical data are static and do not show how the vagaries of demographic processes affect implementation of a culturally defined, conceptual system. Demographic simulations can provide the dynamic dimension, but usually lack information on how the changing demographic makeup of a population affects application of culturally defined rules relating to marriage, reproduction, residence and the like. This paper presents results obtained from implementation of a multi-agent, demographically driven, simulation of a hunting and gathering group in which each agent is imbued with cultural knowledge that affects decisions to be made about marriage, reproduction and place of residence. The goal is to assess the implications of demographic processes, ego-centered decision making, and culturally determined structures (kin relations, social groupings and the like) for the resulting social system. Questions addressed in the simulation are based on ethnographic observations and it is shown that the simulation provides an effective means to assess the validity of hypotheses about the ethnographic observations.

Suggested Citation

  • Dwight Read, 1998. "Kinship Based Demographic Simulation of Societal Processes," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(1), pages 1-1.
  • Handle: RePEc:jas:jasssj:1997-1-1
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    Cited by:

    1. Dwight Read, 2010. "Agent-based and multi-agent simulations: coming of age or in search of an identity?," Computational and Mathematical Organization Theory, Springer, vol. 16(4), pages 329-347, December.

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