Amsterdam as a lab. That is what Amsterdam University of Applied Sciences' three fieldlabs and its many partners have in mind. Functional illiteracy, debts, learning deficiencies or problems caused by extreme precipitation: the city contains plenty of tough issues, demanding novel approaches in which co-creation and participation by residents, social organizations and knowledge institutions are basic principles.In the fieldlabs, people try to change current practices by working with, instead of for or on behalf of those whom it concerns. But how to achieve effective learning environments between parties? How to encourage stakeholder participation in complex issues? And how to build new relations and roles?
This chapter takes a closer look at the case of Amsterdam as a particular manifestation of a film festival city. Drawing from a new dataset on festivals in the Netherlands, the data supports the view of film festivals as a highly dynamic cultural sector: Internationally acclaimed film festivals exist beside smaller festivals that are more community bound; new festivals emerge annually, and young festivals struggle to survive the three-to-five-year mark.Amsterdam holds a unique position in the Dutch film festival landscape as a third of all film festivals in the Netherlands take place in the capital city. Our data collection helps to bring parts of the city’s film infrastructure to the forefront. On the one hand, Amsterdam’s top five locations for film festival events show clear creative cities logic: The data shows just how powerful the pull of such locations is. On the other hand, we find evidence of placemaking and livable city strategies: Amsterdam’s film festivals extend into the capillaries of the city.Dedicated festival datasets may cast new perspectives on local or national festival landscapes, by revealing patterns that remain hidden in qualitative and case-study based projects. But there are also challenges to address in data-driven research on festival cultures, we name a few such as categorization of data. We conclude that such challenges can be more easily faced if more datasets, of for instance, other cities, are pursued and become available.
MULTIFILE
We studied 12 smart city projects in Amsterdam, and –among other things- analysed their upscaling potential and dynamics. Here are some of our findings:First, upscaling comes in various forms: rollout, expansion and replication. In roll-out, a technology or solution that was successfully tested and developed in the pilot project is commercialised/brought to the market (market roll-out), widely applied in an organisation (organisational roll-out), or rolled out across the city (city roll-out). Possibilities for rollout largely emerge from living-lab projects (such as Climate street and WeGo), where companies can test beta versions of new products/solutions. Expansion is the second type of upscaling. Here, the smart city pilot project is expanded by a) adding partners, b) extending the geographical area covered by the solution, or c) adding functionality. This type of upscaling applies to platform projects, for example smart cards for tourists, where the value of the solution grows with the number of participating organisations. Replication is the third and most problematic type of upscaling. Here, the solution that was developed in the pilot project is replicated elsewhere (another organisation, another part of the city, or another city). Replication can be done by the original pilot partnership but also by others, and the replication can be exact or by proxy. We found that the replication potential of projects is often limited because the project’s success is highly context-sensitive. Replication can also be complex because new contexts might often require the establishment of new partnerships. Possibilities for replication exist, though, at the level of working methods, specific technologies or tools, but variations among contexts should be taken into consideration. Second, upscaling should be considered from the start of the pilot project and not solely at the end. Ask the following questions: What kind of upscaling is envisioned? What parts of the project will have potential for upscaling, and what partners do we need to scale up the project as desired? Third, the scale-up stage is quite different from the pilot stage: it requires different people, competencies, organisational setups and funding mechanisms. Thus, pilot project must be well connected to the parent organisations, else it becomes a “sandbox” that will stay a sandbox. Finally, “scaling” is not a holy grail. There is nothing wrong when pilot projects fail, as long as the lessons are lessons learned for new projects, and shared with others. Cities should do more to facilitate learning between their smart city projects, to learn and innovate faster.
