Dissertation Research: Effects of Civic Engagement and Cognitive Repertoires on Political Participation

许多关于公民社会和政治参与的研究都假定民主公民身份与公民社会的活动直接和积极相关。然而，很少有研究检验这一假设，也没有提供公民参与和政治活动之间的关系的机制。这项博士论文研究将探索公民参与和政治参与之间的经验关系，以及支撑这种关系的政治-文化机制。第一阶段将使用现有的调查数据(美国公民参与研究和一般社会调查)来模拟公民参与、效能、公民技能和政治参与之间的关系。将特别注意区分不同类型和不同数量的公民和政治参与的影响，并了解背景和网络对参与的影响。第二阶段将根据第一阶段的调查结果将参与者招募到重点小组。焦点小组将研究公民和政治经历、政治的“认知剧目”和政治参与之间的关系。将对成绩单进行分析，以了解参与者构建政治参与思想的方式。将制定一种系统的、可复制的方法，对重点小组和其他文本数据进行编码和解释。将开发一个软件包和标准--QCML--定性编码标记语言--来实施这一方法。

Much research on civil society and political participation assumes that democratic citizenship is directly and positively related to activity in civil society. However, little research tests this assumption or offers a mechanism for the relationship between civic engagement and political activity. This doctoral dissertation research will explore the empirical relationship between civic engagement and political participation and the political-cultural mechanisms that underlie that relationship. The first phase will use existing survey data (American Citizen Participation Study and General Social Survey) to model the relationships among civic engagement, efficacy, civic skills, and political participation. Particular attention will be paid to differentiating effects of different kinds and amounts of civic and political participation, and to understanding context and network effects on participation. The second phase will recruit participants into focus groups based on the findings from the first section. The focus groups will examine the relationships among civic and political experiences, "cognitive repertoires" of politics, and political participation. Transcripts will be analyzed for the ways participants structure thought on political involvement. A systematic, replicable methodology for coding and interpreting focus group and other textual data will be developed. A software package and standard - QCML, the Qualitative Coding Markup Language - will be developed to implement this methodology.