Testing Assumptions in Deliberative Democratic Design: A Preliminary Assessment of the Efficacy of the Participedia Data Archive as an Analytic Tool

Abstract

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.

Keywords

public participation, empirical deliberative theory, crowd-sourcing, civic engagement

How to Cite

Gastil J. & Richards Jr R. & Ryan M. & Smith G., (2017) “Testing Assumptions in Deliberative Democratic Design: A Preliminary Assessment of the Efficacy of the Participedia Data Archive as an Analytic Tool”, Journal of Public Deliberation 13(2). doi: https://doi.org/10.16997/jdd.277

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Authors

John Gastil (Pennsylvania State University)
Robert C. Richards Jr (Pennsylvania State University)

Matt Ryan (University of Southampton)

Graham Smith (University of Southampton)

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Creative Commons Attribution 4.0

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This article has been peer reviewed.

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