Gatekeeping studies in the cultural industries increasingly draw attention to transnational networks, revealing that decision-making is decentralised through gatekeepers operating from different levels in the marketplace. This brings into focus a new line of enquiry revolving around the nature of such relationships. This paper situates an analysis of transnational gatekeeping and networking arrangements within the longstanding tradition of neo-institutional and Bourdieusian theory. Through a typology of the search and selection strategies developed by distributors in the Dutch film market, it explores their decision-making practices, demonstrating how institutional factors, taste judgements and networking arrangements work together in specific transnational contexts. This reveals that networking arrangements serve the purpose of information sharing, but, more specifically, also act as a social influence through which decision-making is evaluated and confirmed. It therefore becomes clear that reliance on transnational networks adds significant weight to decision-making processes.
This paper discusses a methodology that seeks to address one of the challenges in working with a range of data in mixed-methods audience research, which is how to sort, order and categorise different data so that they can be systematically combined and interrogated. The methodology was developed as part of the "Beyond the Multiplex: audiences for specialised films in English regions" (BtM) project. This project required a mixed methods approach using surveys, interviews, focus groups and document analysis to explore the richness of audience experiences and trends in the context of regional film policy. This required a mixed methods approach using surveys, interviews, focus groups and document analysis. The project utilised a data model approach that uses the principles of a computational ontology in order to sort, order and categorise data for systematic interrogation. The paper discusses methods, data, coding, and the use of a data model to support data analysis. We argue that this approach enables the cross referencing of data that provides a rich, multilayered and relational understanding of film audiences but requires time and attention to data management and coding. Although, additionally it also forms the basis of an open access data resource for future research.
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