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

研究生Allison L. Hopkins将在John R. Stepp博士的指导下，利用文化共识和网络分析技术的新组合，对墨西哥尤卡泰克玛雅人传统药用植物知识的可变性进行研究。人们对传统药用植物有相当大的研究兴趣，这既是因为它们对现代医学的潜在效用，也是因为它们可以告诉研究人员有关文化知识体系的信息。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，社会网络分析可能能够解释这种差异。他们发现，社会网络包含了通过社会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变化。霍普金斯将通过调查网络结构（独立于个体特征）在多大程度上解释墨西哥尤卡泰克玛雅社区家庭间药用植物知识的差异来扩展这个有前途的研究方向。霍普金斯大学将使用免费的清单方法来收集有关民族医学条件和针对这些条件的药用植物治疗的数据。从自由列表中，知识测试将被构建、管理，并通过文化共识分析进行分析。每个参与者的共识分数将总结社区内知识的分布。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，将这两个研究方向结合起来，运用多元回归的方法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分析是一种新的方法，它将使霍普金斯大学能够确定在传统生态知识的传播和保护中发挥关键作用的个人，以及药用植物知识的模式可变性。这项研究很重要，因为它部署并测试了一种新的研究方法。此外，该研究将有助于了解传统植物知识如何传播和保存。的研究也将有助于教育社会学家 .________________________________________

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.________________________________________