The Potential of Participedia as a Crowdsourcing Tool for Comparative Analysis of Democratic Innovations

For two reasons, our capacity for systematic comparison of innovative participatory democratic processes remains limited. First, the category of participatory democratic innovations remains relatively vague when compared to more traditional democratic institutions and practices. Second, until recently there existed no large-sample databases that captured relevant variables in the practice of democratic innovation. The lone exception to these patterns is the Participedia database, located online. Participedia is well placed to respond to the two obstacles to systematic comparative research on democratic innovation. First, its crowdsourced data collection strategy means that many of the cases on the platform are not well known and have not been the subject of sustained academic analysis. Second, the data captured in the articles provides the basis for systematic comparative analysis of democratic innovations both within type (e.g., participatory budgeting, mini-publics) and across types. The platform allows for systematic content analysis of text descriptions and/or statistical analysis of the datasets generated from the structured data fields. This article describes the data about innovative participatory democratic processes available from Participedia, and furnishes examples of the kinds of quantitative and qualitative insights about those processes that Participedia enables.

Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems

In this study we analyse the emerging patterns of regional collaboration for innovation projects in China, using official government statistics of 30 Chinese regions. We propose the use of Ordinal Multidimensional Scaling and Cluster analysis as a robust method to study regional innovation systems. Our results show that regional collaborations amongst organisations can be categorised by means of eight dimensions: public versus private organisational mindset; public versus private resources; innovation capacity versus available infrastructures; innovation input (allocated resources) versus innovation output; knowledge production versus knowledge dissemination; and collaborative capacity versus collaboration output. Collaborations which are aimed to generate innovation fell into 4 categories, those related to highly specialised public research institutions, public universities, private firms and governmental intervention. By comparing the representative cases of regions in terms of these four innovation actors, we propose policy measures for improving regional innovation collaboration within China.