The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.
The challenges and limits of big data algorithms in technocratic governance
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“and an effective solution to AI-specific risks such as data or algorithmic errors, data or algorithmic bias, or even data-embedded discrimination (Janssen & Kuk, 2016).”
From Data governance: Organizing data for trustworthy Artificial Intelligence (2020) · cites this paper as Janssen & Kuk, 2016
Citations
Cites
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Flagged first, then by citations
1 of the 32 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Barocas, 2016, Big Data's Disparate Impact (August 14, 2015), California Law Review, 104
- Sandvig, 2014, Seeing the Sort: The Aesthetic and Industrial Defense of “The Algorithm”, Journal of the New Media Causes
Cited by
Sorted by citations
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611
Self-citationØlnes, S., Ubacht, J., & Janssen, M. (2017) · Government Information Quarterly · doi:10.1016/j.giq.2017.09.007 · Cited by 1,107
“These “algorithms become increasingly autonomous and invisible, they become harder for the public to detect and scrutinize their impartiality status” (Janssen & Kuk, 2016, p. 371).”
BackgroundSelf-citationFairness in Criminal Justice Risk Assessments: The State of the Art
Berk, R., Heidari, H., Jabbari, S., Kearns, M., & Roth, A. (2021) · Sociological Methods & Research · doi:10.1177/0049124118782533 · Cited by 988
Sun, T. Q., & Medaglia, R. (2019) · Government Information Quarterly · doi:10.1016/j.giq.2018.09.008 · Cited by 948
Smart cities: Advances in research—An information systems perspective
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Metadata
- Authors
- Janssen, M., & Kuk, G.
- Affiliations
- Delft University of Technology (NL)
- Nottingham Trent University (GB)
- Corresponding author
- Janssen, Marijn
- Venue
- Government Information Quarterly
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 33
- Issue
- 3
- Pages
- 371-377
- ISSN
- 0740-624X (ISSN-L)
- OpenAlex
- W2527349292
- Cited by
- 363
- References
- 32
- Citations by year
- 2026: 64 · 2025: 42 · 2024: 43 · 2023: 31 · 2022: 48 · 2021: 47 · 2020: 39 · 2019: 27 · 2018: 16 · 2017: 5 · 2016: 1
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Government Information Quarterly (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Social Sciences › Urban Studies › Smart Cities and Technologies
- Keywords
- big data algorithms, technocratic governance, algorithmic bias, algorithmic accountability, governmentality, algorithmic transparency, data curation, algorithmic discrimination, institutional logics, algorithmic governance
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