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Social Innovation and Democratic Leadership

Communities and Social Change from Below

Marc Parés, Sonia M. Ospina and Joan Subirats

This book explores new forms of democracy in practice following the 2011 global uprisings; democracy that comes from below, by and for the ‘have-nots’. Combining theories of social innovation and collective leadership, it analyses how disadvantaged communities have addressed the effects of economic recession in two global cities: Barcelona and New York.
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Methodological appendix

Marc Parés, Sonia M. Ospina and Joan Subirats

Extract

Our four case studies come from two different cities in two different countries in which the Great Recession has had very different effects and been met with very different institutional responses. We selected two neighbourhoods in each city, taking into account both their vulnerability and the effects the Great Recession produced in them. Thus, our case selection was made on the basis of choosing neighbourhoods that were all hit by the recession but varied in terms of their vulnerability.

The principal unit of analysis of this research is the neighbourhood. However, we have used a multiple-case research design with embedded units of analysis (Yin 2003). In each neighbourhood (case), we focused on the following units of analysis:

In each city, we selected the case studies according to a theoretical replication rationale; that is, with the aim of observing contrasting results for anticipatable reasons (Yin 2003). We were very careful to select comparable neighbourhoods within each city. The proposition to be tested through the selection of the case studies was:

Those neighbourhoods with a greater level of civic capacity produce socially innovative initiatives that are more effective and have a greater chance of being scalable.

Thus, in each city we selected one neighbourhood rich in civic capacity (Sants and South Bronx) and another with lesser civic capacity (Nou Barris Nord and Bushwick). The comparison between the two cities was made according to a literal replication rationale, with the aim of predicting similar results...

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