Cited by 23E-Government and Public ServicesDigital Accessibility for DisabilitiesDisability Rights and Representation

A stigma power perspective on digital government service avoidance

Open access
Pethig, Florian, Kroenung, Julia, Noeltner, Markus·2021·Government Information Quarterly

Integrity signals

Registry

Crossref · 10.1016/j.giq.2020.101545

Cites

11 of 11 references verified0 citation errors · 0 not checkable

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  • People with disabilities, residents of rural areas, and the unemployed are mentioned as vulnerable groups in second place.

    “Additionally, people with disabilities (e.g., Republic of Bulgaria, 2020; Government of Italy, 2020; Pethig et al. 2021), residents of rural areas (e.g., Government of Navarra, 2021; Government of Madrid, 2022), and the unemployed (e.g., Andersen et al. 2019; Government of Portugal, 2020), are mentioned as vulnerable groups in second place.”

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Authors
Pethig, F., Kroenung, J., & Noeltner, M.
Affiliations
University of Mannheim (DE)
Corresponding author
Pethig, Florian
Venue
Government Information Quarterly
Publisher
Elsevier BV
Published
2021-04
Volume
38
Issue
2
Pages
101545
ISSN
0740-624X (ISSN-L)
OpenAlex
W3128712236
Cited by
23
References
11
Citations by year
2026: 4 · 2025: 8 · 2024: 7 · 2023: 2 · 2022: 1 · 2021: 1
FWCI
9.14
Type
journal article
Language
en
Open access
Locations
  • Government Information Quarterly (publishedVersion)
  • MADOC (University of Mannheim) (submittedVersion, cc-by-nc-nd)
Funders
Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
Topics
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
  • Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
  • Social Sciences › Safety Research › Disability Rights and Representation
Keywords
digital public services, people with disabilities, digital divide, stereotyping, discrimination, internet anxiety, marginalized citizens

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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