Doctoral Dissertation Improvement Grant: Yucatec Maya Medicinal Plant Knowledge Variation and Social Networks

研究生Allison L.霍普金斯，监督博士约翰R。Stepp将利用文化共识和网络分析技术的新组合，对墨西哥尤卡坦玛雅人传统药用植物知识的变异性进行研究。有相当大的研究兴趣，在传统药用植物既为他们的潜在效用，现代医学，因为他们可以告诉研究人员有关文化知识体系。药用植物知识，就像其他类型的文化知识一样，在一个文化群体中是不同的。 最近，研究人员提出，社交网络分析可能能够解释这种变异性。他们发现，社交网络包括通过社会途径获得的知识传播的途径。 因此，在社会网络中处于不同位置的人可以获得不同的信息，从而导致知识的模式化变化。 霍普金斯将通过调查网络结构（独立于个人特征）在多大程度上解释了墨西哥尤卡坦玛雅社区家庭中药用植物知识的变化来扩展这一有前途的研究方向。霍普金斯将使用自由列表的方法来收集有关民族医学条件和药用植物治疗这些条件的数据。 从自由名单，知识测试将构建，管理，并与文化共识分析进行分析。 每个参与者的共识得分将总结社区内的知识分布。 整个网络和个人网络数据将使用社交网络分析技术进行收集和分析。 最后，这两个研究链将通过使用多元回归来了解网络结构变量对知识分布的影响。 结合社会网络和文化共识的分析是一种新的方法，它将使霍普金斯确定个人谁是关键球员的传统生态知识的传递和保护，以及模式化的变异性药用植物知识。 这项研究很重要，因为它部署和测试了一种新的研究方法。此外，这项研究将有助于了解传统植物知识是如何传播和保存的。这项研究也将有助于社会科学家的教育。

Graduate student Allison L. Hopkins, supervised by Dr. John R. Stepp, will undertake research on variability in traditional medicinal plant knowledge among the Yucatec Maya of Mexico, using a novel combination of cultural consensus and network analysis techniques. There has been considerable research interest in traditional medicinal plants both for their potential utility for modern medicine and because of what they can tell researchers about cultural knowledge systems. Medicinal plant knowledge, just like other types of cultural knowledge, varies within a cultural group. Recently, researchers have suggested social network analysis may be able to explain some of this variability. They have found that social networks comprise pathways through which socially acquired knowledge is transmitted. Therefore, people in different positions within the social network have access to different information, resulting in patterned variation in knowledge. Hopkins will extend this promising research direction by investigating the question of how much network structure (independently of characteristics of the individual) explains variation in medicinal plant knowledge across households in a Yucatec Maya community in Mexico. Hopkins will use free listing methods to gather data on ethnomedical conditions and medicinal plant treatments for those conditions. From the free lists, a knowledge test will be constructed, administered, and analyzed with cultural consensus analysis. The consensus score for each participant will summarize the distribution of knowledge within the community. Whole network and personal network data will be gathered and analyzed using social network analysis techniques. Finally, these two research strands will be integrated by using multiple regression to understand the influence of network structure variables on the distribution of knowledge. Combining social network and cultural consensus analyses is a new approach and it will allow Hopkins to identify individuals who are key players in the conveyance and conservation of traditional ecological knowledge, as well as the patterned variability of medicinal plant knowledge. The research is important because it deploys and tests a new research methodology. In addition, the research will contribute to understanding how traditional plant knowledge is communicated and conserved. The research also will contribute to the education of a social scientist.________________________________________