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Digitization or equality

When government automation covers some, but not all citizens

Bibliographic Data

ID12079986
AuthorsKarl Kristian Larsson (0000-0001-8743-7659, OsloMet – Oslo Metropolitan University, corresponding author)
Year2020
Volume38
Issue1
Pages101547-101547
Publication date2020-12-16
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGovernment Information Quarterly (JOURNAL)
Journal identifiersISSN: 0740-624X • E-ISSN: 1872-9517
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.giq.2020.101547
OpenAlexW3112137988
LanguageEN
Citations received66
References cited29

This paper presents an empirical study of automation in government digital systems. Previous studies have found that automated systems are not suited to cover all citizens equally and may cause administrative burdens on excluded citizens. The case presented in this study is the automated system for awarding child benefits in Norway. Based on data from the national registry, most recipients are awarded the benefit automatically. However, some citizens are not covered by the automation and must apply manually. The theoretical framing of the study combines modern and classic views of how citizens access public services by combining theory from recent literature on administrative burdens and the older theory of access. The data analysis is done with process mining, an innovative method of sorting and understanding data. The findings support previous findings of how registry data and automated computer systems in government can create inequality in service quality. Furthermore, the findings also show that low-income citizens are disproportionally required to apply manually. The study addresses questions concerning why automated systems fail to cover all citizens and the potential challenges generated by this exclusion when governments rely on computer systems in delivering welfare programmes. These are important considerations, as government digitalisation is increasingly innovating with automated systems to deliver public services

Automation · Cover (algebra · Data science · Digitization · Framing (construction · Government (linguistics · Telecommunications · Computer Science · E-Government and Public Services · Engineering · Local Government Finance and Decentralization · Privacy, Security, and Data Protection

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Unique citing works66
Citations per year13,2
Citation span2021 - 2026 (6)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 65
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