Your browser doesn't support javascript.
Pandemic modelling and model citizens: Governing COVID-19 through predictive models, sovereignty and discipline.
Sandset, Tony; Villadsen, Kaspar.
  • Sandset T; Centre for Sustainable Healthcare Education, Faculty of Medicine, University of Oslo, Norway.
  • Villadsen K; Department of Management, Politics and Philosophy, Copenhagen Business School, Denmark.
Sociol Rev ; 71(3): 624-641, 2023 May.
Article in English | MEDLINE | ID: covidwho-2318921
ABSTRACT
Pandemic modelling functions as a means of producing evidence of potential events and as an instrument of intervention that Tim Rhodes and colleagues describe as entangling science into social practices, calculations into materializations, abstracts into effects and models into society. This article seeks to show how a model society evinced through mathematical models produces a model not only for society but also for citizens, showing them how to act in a certain model manner that prevents an anticipated pandemic future. To this end, we analyse political speeches by various Norwegian ministers to elucidate how various model-based COVID-19 responses enact a 'model citizen'. Theoretically, we combine Rhodes et al.'s arguments with Foucault's concepts of law, discipline and security, thus showing what a model society might imply for the model citizen. Finally, we conclude that although the model society is largely informed by epidemiological models and liberal biopolitics that typically place responsibility on individual subjects, sovereign state power remains manifestly present in the speeches' rhetoric.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Sociol Rev Year: 2023 Document Type: Article Affiliation country: 00380261221102023

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Sociol Rev Year: 2023 Document Type: Article Affiliation country: 00380261221102023