检验协商民主设计中的假设:参与性数据档案作为分析工具效能的初步评估

John Gastil, R. Richards, Matt Ryan, Graham Smith
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引用次数: 21

摘要

在较小的社会尺度上,协商民主理论可以被重新表述为一种投入-过程-产出模型。我们提出了这样一个模型,以提出关于公民参与过程的背景和设计如何塑造其中发生的审议,以及审议对参与者和随后的政策制定的影响的假设。为了验证这些说法,我们从Participedia.net(一个采用自我导向的众包策略来收集世界各地参与性机构和审议性干预的数据的研究平台)中提取并编码了案例研究。我们解释并面对编码和分析parepedia案例所面临的挑战,包括管理可靠性问题和丢失数据。尽管存在这些困难,但对编码案例的回归分析显示出令人信服的结果,这为我们的一般理论模型提供了相当大的支持。最后,我们反思了我们的研究结果对审议理论、民主创新的设计以及参与百科全书作为数据档案的效用的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing Assumptions in Deliberative Democratic Design: A Preliminary Assessment of the Efficacy of the Participedia Data Archive as an Analytic Tool
At smaller social scales, deliberative democratic theory can be restated as an input-process-output model. We advance such a model to formulate hypotheses about how the context and design of a civic engagement process shape the deliberation that takes place therein, as well as the impact of the deliberation on participants and subsequent policymaking. To test those claims, we extract and code case studies from Participedia.net, a research platform that has adopted a self-directed crowd-sourcing strategy to collect data on participatory institutions and deliberative interventions around the world. We explain and confront the challenges faced in coding and analyzing the Participedia cases, which involves managing reliability issues and missing data. In spite of those difficulties, regression analysis of the coded cases shows compelling results, which provide considerable support for our general theoretical model. We conclude with reflections on the implications of our findings for deliberative theory, the design of democratic innovations, and the utility of Participedia as a data archive.
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