Explaining Crow-Omaha Kinship Structures with Anthro-informatics

纽约美国自然历史博物馆的Peter Whiteley博士（人类学）和Ward Wheeler博士（无脊椎动物学/科学计算）将改编为系统发育研究（研究不同生物有机体群体之间的进化关系）设计的软件，开发和应用一种创新的人类信息学方法来研究人类亲属关系和社会系统的跨文化数据。利用从已出版的民族志和民族志数据库中提取的数据，研究人员将使用该软件来比较与世界范围内计算亲属关系和家庭关系的历史关键系统相关的社会、文化和生态特征。在国家出现之前，亲属制度曾经组织了所有的社会制度，因此，解释亲属制度是理解人类社会进化模式的关键。要使用的软件（POY4）允许测试通过空间水平（即，通过学习行为的扩散）以及通过时间垂直（通过简单继承）的特征传播的可能性。这一点很重要，因为人类的行为既可以在不同文化之间习得，也可以在单一文化中传承下来。焦点亲属系统，似乎是进化过渡，被专家统称为克劳-奥马哈系统。需要测试的假设包括它们是否与社会组织的其他特征有独特的联系，它们是否从其他已知系统进化而来，以及某些经济和生态条件是否有利于它们的兴起和传播。这项研究将使科学家能够更好地解释特定亲属制度和其他行为现象之间的联系，从而对理解人类社会组织在时间和空间上的意义重大。资助这项研究也支持研究生教育。

Dr. Peter Whiteley (Anthropology) and Dr. Ward Wheeler (Invertebrate Zoology/Scientific Computing) of the American Museum of Natural History, New York, will adapt software designed for phylogenetic research (the study of evolutionary relatedness among various groups of biological organisms), to develop and apply an innovative anthro-informatics approach to cross-cultural data on human kinship and social systems. Using data drawn from published ethnographies and ethnographic databases, the researchers will use the software to compare social, cultural, and ecological features associated with a historically critical system of reckoning kinship and family relations worldwide. Kinship systems once organized all social systems, prior to the emergence of the state, and, therefore, explaining kinship systems is key to understanding patterns of human social evolution. The software to be used (POY4) allows for testing likelihoods of feature transmission horizontally through space (i.e., via diffusion of learned behavior) as well as vertically through time (via simple inheritance). This is important because human behavior is learned between cultures as well as passed down within single cultures. The focal kinship systems, which appear to be evolutionarily transitional, are known collectively as Crow-Omaha systems by specialists. The hypotheses to be tested include whether they have distinctive associations with other features of social organization, whether they evolve from other known systems, and whether certain economic and ecological conditions favor their rise and spread. The research will enable scientists to better explain the associations of particular kinship systems and other behavioral phenomena, resulting in significant implications for the understanding human social organization over time and space. Funding this research also supports graduate student education.