Doctoral Dissertation Research: The Differential Influence of Three Types of Elites

博士论文研究：三类精英的不同影响

• 批准号: 2001886
• 负责人: Aaron Major
• 金额: $ 1.55万
• 依托单位: SUNY at Albany
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2001886&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Differential; Influence

This project examines and compares the effects of influence exerted by three different categories of elites on an important security-related area of deliberation. The project will investigate the proposition that the usual assumption of the preeminence of the economic elite is not valid in this area. Data will come from a variety of compiled journals, magazines, and official texts from 1990 to 2019. These will be analyzed using computer-assisted content analysis and narrative analysis. Findings are likely to be relevant for other areas of deliberation as well and will be informative for those concerned with security decision-making.The data come from a representative corpus of texts compiled from official reports, journals and magazines, and different kinds of official records. The corpus covers the three categories of elites and their discourse in this area, with approximately one million words for each one. The dates covered are from 1990 to 2019. Data analysis will integrate multiple computer-assisted content analysis and qualitative narrative analysis techniques. Structural Topic Model and Concept Mover’s Distance will be used to compare and contrast the focus of each category of elite. Qualitative narrative analysis, Concept Mover’s Distance, and Text Network Analysis will be used on two different issues to investigates how different elites have shaped narratives.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

本项目考察并比较了三种不同类型的精英对一个重要的安全相关审议领域所施加的影响。该项目将调查这样一个命题，即经济精英卓越的通常假设在这一领域是无效的。数据将来自1990年至2019年的各种汇编期刊、杂志和官方文本。这些将使用计算机辅助内容分析和叙事分析进行分析。调查结果也可能与其他审议领域有关，并将为那些与安全决策有关的人提供资料。这些数据来自官方报告、期刊和杂志以及各种官方记录汇编的具有代表性的文本语料库。该语料库涵盖了该领域的三类精英及其话语，每一类约100万字。涵盖的日期为1990年至2019年。数据分析将整合多种计算机辅助内容分析和定性叙事分析技术。结构话题模型和概念推动者的距离将被用来比较和对比每一类精英的焦点。定性叙事分析、概念推动者的距离和文本网络分析将在两个不同的问题上使用，以调查不同的精英如何塑造叙事。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。