The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
The Reputational Basis of Public Accountability
Open accessAbstract
This article proposes a reputation‐based approach to account for two core puzzles of accountability. The first is the misfit between behavioral predictions of the hegemonic political science framework for talking about accountability, namely, principal–agent, and empirical findings. The second puzzle is the unrivaled popularity of accountability, given evidence that supposedly accountability‐enhancing measures often lead to opposite effects. A “reputation‐informed” theoretical approach to public accountability suggests that accountability is not about reducing informational asymmetries, containing “drift,” or ensuring that agents stay committed to the terms of their mandate. Accountability—in terms of both holding and giving—is about managing and cultivating one's reputation vis‐à‐vis different audiences. It is about being seen as a reputable actor in the eyes of one's audience(s), conveying the impression of competently performing one's (accountability) roles, thereby generating reputational benefits.
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Cites
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Cited by
Sheffer, L., & Loewen, P. J. (2019) · Political Research Quarterly · doi:10.1177/1065912918775252 · Cited by 33
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability
Metcalf, J., Singh, R., Moss, E., Tafesse, E., & Watkins, E. A. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3593013.3594092 · Cited by 21
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Metadata
- Authors
- Busuioc, E. M., & Lodge, M.
- Venue
- Governance
- Publisher
- Wiley
- Published
- 2015-09-21
- Volume
- 29
- Issue
- 2
- Pages
- 247-263
- ISSN
- 0952-1895 (ISSN-L)
- 1468-0491
- OpenAlex
- W1936979584
- Cited by
- 306
- References
- 71
- FWCI
- 41.53
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.