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

博士论文改进补助金：尤卡坦玛雅药用植物知识变异和社交网络

• 批准号: 0719053
• 负责人: John Stepp
• 金额: $ 1.5万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0719053&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Improvement; Grant; Yucatec

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.________________________________________

研究生艾莉森·L·霍普金斯将在约翰·R·斯特普博士的指导下，利用文化共识和网络分析技术的新组合，对墨西哥尤卡特克玛雅人传统药用植物知识的变异性进行研究。人们对传统药用植物的研究兴趣很大，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关于文化知识体系的内容。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，社交网络分析或许能够解释这种差异。他们发现，社交网络包括传播社交知识的途径。因此，在社交网络中处于不同位置的人可以访问不同的信息，从而导致知识的模式化差异。霍普金斯大学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特克玛雅社区家庭之间药用植物知识的差异这一问题来扩展这一有希望的研究方向。霍普金斯大学将使用免费列出的方法来收集有关民族医疗状况和针对这些状况的药用植物治疗的数据。从免费列表中，将构建、管理和分析一项知识测试，并进行文化共识分析。每个参与者的共识得分将总结社区内知识的分布情况。将使用社交网络分析技术收集和分析整个网络和个人网络数据。最后，将这两个研究线索通过多元回归进行整合，以了解网络结构变量对知识分布的影响。将社会网络和文化共识分析结合起来是一种新的方法，它将使霍普金斯大学能够识别在传播和保护传统生态知识以及药用植物知识的模式化可变性方面发挥关键作用的个人。这项研究之所以重要，是因为它部署和测试了一种新的研究方法。此外，这项研究将有助于理解传统植物知识是如何交流和保存的。这项研究也将有助于社会型scientist.________________________________________的教育