Involuntary Resistance.

Covid-19 Governing Neoliberalism Norms Resistance

Journal

International journal of politics, culture, and society
ISSN: 0891-4486
Titre abrégé: Int J Polit Cult Soc
Pays: Germany
ID NLM: 101710975

Informations de publication

Date de publication:
23 Mar 2023
Historique:
accepted: 25 02 2023
pubmed: 26 6 2023
medline: 26 6 2023
entrez: 26 6 2023
Statut: aheadofprint

Résumé

This paper problematizes the notion of "intent" through the concept of "involuntary resistance". Departing from the narratives of employees in nursing homes in Sweden during the Covid-19 pandemic in 2020 and 2021, we suggest that neoliberal norms and a local management that capitalizes on social hierarchies (sex, age, class, etc.) were the context of the strong biopolitical state management that occurred due to the Covid-19 pandemic. The friction between different forms of governing became a seedbed for an involuntary resistance with an unclear intent against the state recommendations. This sheds light upon the need to (re)frame the current dominance of specific types of knowledge that are constructed in the field of resistance. We suggest that new paths of thought are needed-within social sciences-that work towards a wider conceptualizing of resistance, which embraces practices that lie outside the common thought of dissent.

Identifiants

pubmed: 37361706
doi: 10.1007/s10767-023-09442-5
pii: 9442
pmc: PMC10034246
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1-21

Informations de copyright

© The Author(s) 2023.

Déclaration de conflit d'intérêts

Conflict of InterestThe authors declare no competing interests.

Auteurs

Mikael Baaz (M)

University of Gothenburg, Gothenburg, Sweden.
School of Business, Economics and Law, University of Gothenburg, Gothenburg, Sweden.

Mona Lilja (M)

School of Global Studies, University of Gothenburg, Gothenburg, Sweden.

Malin Wallgren (M)

University of Gothenburg, Gothenburg, Sweden.
School of Global Studies, University of Gothenburg, Gothenburg, Sweden.

Classifications MeSH