Journal Article

Managing Public Service: The Harmonization of Datafication and Managerialism in the Development of a News-Sorting Algorithm

Publication

Abstract

This article studies the algorithmic project News values at Swedish public service radio, from the perspective of datafied managerialism. Drawing on ethnographic observations and interviews with managers the study shows how the project, that outwardly works to automate news-sorting algorithmically, was employed to generate data about a number of internal journalistic activities, for a variety of purposes. Data was perceived of as a type of capital that could engender, amongst other things, increased knowledge about the internal workings of the organization, thus making it easier to audit its activities, and to standardize the practice of news-valuation throughout SR. Importantly, these goals were not planned in advance, but emerged over the course of the project. The results show how longitudinal approaches to algorithms and data-collection could benefit journalism studies, as they provide a more comprehensive picture of how data are operationalized in journalistic organizations.

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About the Authors

Jörgen Rahm-Skågeby

Rahm-Skågeby is an associate professor (docent) in media studies at Stockholm university. He holds a PhD in informatics geared towards interaction design and Human-Computer Interaction; a BSSc in information and media science (including behavioura... Read more

Andreas Widholm

Andreas Widholm is Associate Professor of journalism in the Department of Media Studies at Stockholm University, Sweden. He received his PhD from the same department in 2011. His research addresses the relationship between media, politics and cult... Read more

Reference

Rahm-Skågeby, J., Rolandsson, T. and Widholm, A. (2022). Managing Public Service: The Harmonization of Datafication and Managerialism in the Development of a News-Sorting Algorithm. Digital Journalism. Available at: https://www.tandfonline.com/doi/full/10.1080/21670811.2022.2119151 [Accessed 27 Nov. 2022]. doi: https://doi.org/10.1080/21670811.2022.2119151.