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Amsterdam film festival city

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.

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Examining strategic diversity communication on social media using supervised machine learning: Development, validation and future research directions

In this paper, we present a digital tool named Diversity Perspectives in Social Media (DivPSM) which conducts automated content analysis of strategic diversity communication in organizational social media posts, using supervised machine-learning. DivPSM is trained to identify whether a post makes mention of diversity or a diversity-related issue, and to subsequently code for the presence of three diversity dimensions (cultural/ethnic/racial, gender, and LHGBTQ+ diversity) and three diversity perspectives (the moral, market, and innovation perspectives). In Study 1, we describe the training and validation of the instrument, and examine how it performs compared to human coders. Our findings confirm that DivPSM is sufficiently reliable for use in future research. In study 2, we illustrate the type of data that DivPSM generates, by analyzing the prevalence of strategic diversity communication in social media posts (n = 84,561) of large organizations in the Netherlands. Our results show that in this context gender diversity is most prevalent, followed by LHGBTQ+ and cultural/ethnic/racial diversity. Furthermore, gender diversity is often associated with the innovation perspective, whereas LHGBTQ+ diversity is more often associated with the moral perspective. Cultural/ethnic/racial diversity does not show strong associations with any of the perspectives. Theoretical implications and directions for future research are discussed at the end of the paper.

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Examining strategic diversity communication on social media using supervised machine learning: Development, validation and future research directions
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State Machines

Today, we live in a world where every time we turn on our smartphones, we are inextricably tied by data, laws and flowing bytes to different countries. A world in which personal expressions are framed and mediated by digital platforms, and where new kinds of currencies, financial exchange and even labor bypass corporations and governments. Simultaneously, the same technologies increase governmental powers of surveillance, allow corporations to extract ever more complex working arrangements and do little to slow the construction of actual walls along actual borders. On the one hand, the agency of individuals and groups is starting to approach that of nation states; on the other, our mobility and hard-won rights are under threat. What tools do we need to understand this world, and how can art assist in envisioning and enacting other possible futures?This publication investigates the new relationships between states, citizens and the stateless made possible by emerging technologies. It is the result of a two-year EU-funded collaboration between Aksioma (SI), Drugo More (HR), Furtherfield (UK), Institute of Network Cultures (NL), NeMe (CY), and a diverse range of artists, curators, theorists and audiences. State Machines insists on the need for new forms of expression and new artistic practices to address the most urgent questions of our time, and seeks to educate and empower the digital subjects of today to become active, engaged, and effective digital citizens of tomorrow.Contributors: James Bridle, Max Dovey, Marc Garrett, Valeria Graziano, Max Haiven, Lynn Hershman Leeson, Francis Hunger, Helen Kaplinsky, Marcell Mars, Tomislav Medak, Rob Myers, Emily van der Nagel, Rachel O’Dwyer, Lídia Pereira, Rebecca L. Stein, Cassie Thornton, Paul Vanouse, Patricia de Vries, Krystian Woznicki.

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State Machines