This paper explores how consumers’ ethical food consumption practices, mediated by mobile phone applications (apps), are transformed into digital data. Based on a review of studies on the digitalization of ethical consumption practices and food apps, we find that previous research, while valuable, fails to acknowledge and critically examine the digital labor required to perform digitalized ethical food consumption. In this paper, we call for research on how digital labor underlies the digitalization of ethical food consumption and develop a conceptual (...) framework that supports this research agenda. Our proposed conceptual framework builds on three interconnected analytical concepts—datafication, affordances and digital labor—that enable the study of digital labor as an infrastructural element of digitalized food consumption. We illustrate our conceptual framework through our previous research concerning Buycott, a US-based mobile app whose stated aim is to facilitate consumers’ ethical purchasing decisions. Using the walkthrough method, we consider how the Buycott app engages user-generated data and what implications this holds for consumers. The app’s infrastructure, we suggest, connects ethical consumption and digital labor. A richer understanding of the digital food economy, we propose, enables social scientists not only to elucidate how consumers engage in digital labor, but also to contribute to the development of new data governance structures in the digital food economy. We therefore call for social scientists interested in food, consumption and the digital economy to contribute to a new research agenda for studying everyday food digitalization by empirically examining how ethical consumption apps implicate ethical consumers’ work. (shrink)

Background The ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership. Main body In this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk mitigation, as well as technological, economic, (...) and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks. Conclusion Undifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society. (shrink)

Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue that there is also much to be learned from studying how professionals in the healthcare (...) field affectively engage with this strong European narrative in concrete big data projects. We followed twelve hospital-based big data pilots in eight European countries and interviewed 145 professionals between 2018 and 2020. In this study, we introduce the metaphor of dreams to describe how professionals link the big data promises to their own frustrations, ideas, values and experiences with healthcare. Our research answers the question: how do professionals in concrete data-driven initiatives affectively engage with European Union's data hopes in their ‘dreams’ – and with what consequences? We describe the dreams of being seen, of timeliness, of connectedness and of being in control. Each of these dreams emphasizes certain aspects of the grand narrative of big data in Europe, makes particular assumptions and has different consequences. We argue that including attention to these dreams in our work could help shine an additional critical light on the big data developments and stimulate the development of responsible data-driven healthcare. (shrink)