The digital era has brought about profound changes in how music is created, distributed, and consumed, posing a need for modernizing the Dutch collective management system of music copyright to match the rapidly changing digital music industry. This study aims to identify the key stakeholders and their perceptions of the Dutch system of collective management of music copyright. Utilizing qualitative document analysis, the study examines a range of public and non-public documents, including income statements, annual reports from Collective Management Organizations (CMOs), and contracts between publishers and creators. The research is further enriched by twenty-four semi-structured interviews with key stakeholders such as composers, lyricists, music publishers, copyright lawyers, and CMO executives. The findings of the study highlight several issues like the outdated IT systems and the lack of data standardization within the system. The research also notes a contrast in organizational effectiveness: major publishers are well-organized and unified in their negotiations with Digital Service Providers (DSPs) and CMOs, effectively advocating for their rights. However, music copyright holders, despite their legal homogeneity, are either unorganized or ineffectively aligned, displaying diverse interests and varying levels of access to information, as well as differences in norms and values prioritization. The study is grounded in the economics of collective management (ECM) and makes a significant academic contribution to this field by introducing new empirical findings to ECMs core constructs and integrating theoretical perspectives. The research offers valuable insights for policymakers, industry stakeholders, and researchers, aiming to foster a more equitable music copyright management system in the digital context.
MULTIFILE
Conflict lies at the core of urban sustainability transitions and the indispensable structural changes that accompany them. In this chapter we examine the RESILIO project, a multi-actor collaboration in Amsterdam aiming to transition towards a 'climate proof' city through smart water retention systems on urban roofs. The focus is on the conflict that emerged during discussions about controlling the smart valves on the rooftops which are designed to prevent urban flooding. Using a discourse analytical framework, the study analyses participant interactions, conflicting positions, and discursive strategies employed by the partners involved in the initiative. Participants utilised several discursive strategies, including identity, stake, and accountability management, to manage their positions in the conflict and influence the discourse. The study highlights the challenges of addressing conflict that involves redefining accountability and responsibility between public and private actors in the collaborative setting of transition initiatives. By doing so the findings contribute to a deeper understanding of how conflict can shape learning processes and foster sustainable urban transitions.
Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention toward the computational interpretation of visual data. When analyzing large numbers of images, both traditional content analysis as well as cultural analytics have proven valuable. However, these techniques do not take into account the contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by online publics, bound through networked practices, these visuals should be analyzed on the level of their networked contextualization. Although machine vision is increasingly adept at recognizing faces and features, its performance in grasping the meaning of social media images remains limited. Combining automated analyses of images with platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This article explores the capacities of hashtags and retweet counts to complement the automated assessment of social media images, doing justice to both the visual elements of an image and the contextual elements encoded through the hashtag practices of networked publics.
