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Cited by 575

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

New Media and the Coproduction of Safety: An Empirical Analysis of Dutch Practices

Open access
Meijer, Albert Jacob·2014·The American Review of Public Administration

Abstract

The new media have been argued to strengthen the coproduction of safety by reducing the costs of interactions between government and citizens and providing new communicative potential. Does that lead to relevant additional input from citizens in police work? Or are preexisting interactions reproduced online? This empirical study of police practices in the Netherlands shows that new media indeed strengthen the coproduction of safety by enabling the police to reach more citizens and contact them 24/7. The police build new connections to citizens: mediated citizen networks form an important addition to offline networks. The costs are reduced most in a situation where new media replace face-to-face contacts between police and citizens, that is, in the coproduction of police patrol work. The article concludes that new media support the trend of responsibilization: the police use new media to build virtual networks with citizens and engage them anywhere and anytime in the coproduction of safety.

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Metadata

Authors
Meijer, A. J.
Venue
The American Review of Public Administration
Published
2012-08-29
Volume
44
Issue
1
Pages
17-34
ISSN
  • 0275-0740 (ISSN-L)
  • 1552-3357
OpenAlex
W2074642238
Cited by
575
References
5
FWCI
240.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: New Media and the Coproduction of Safety: An Empirical Analysis of Dutch Practices. https://app.cochat.ai/papers/10.1177/0275074012455843
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Meijer, A. J. (2014). New Media and the Coproduction of Safety: An Empirical Analysis of Dutch Practices. The American Review of Public Administration. https://doi.org/10.1177/0275074012455843

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.