How Do Elected Officials Evaluate Performance? Goal Preferences, Governance Preferences, and the Process of Goal Reprioritization
Open accessAbstract
Performance data allows politicians to exert accountability over public organizations, even as ideological biases can affect how they interpret such data. However, we know little about how motivated decision-makers prioritize goals when facing multiple pieces of contradictory performance data that reflect the competing goals of public services. Such goal conflict is an inherent aspect of public management. To understand its implications for the use of performance data, we develop a theory of goal reprioritization. We start by assuming that elected officials have preferences between specific policy goals, and about governance processes—such as a preference for public or private service provision. When elected officials face contradictory pieces of performance data, governance preferences drive performance evaluations to the point that they are willing to reweight their goal preferences to minimize cognitive dissonance. We offer experimental evidence of this process, showing that elected officials asked to evaluate school performance reprioritize between two distinct policy goals for schools—test scores and student well-being—to fit with their governance preferences. Reprioritization is an attractive strategy since it allows elected officials to claim they are using performance data, even as underlying governance preferences lead them to set aside the evaluative goal-based criteria by which they would otherwise make performance evaluations. In other words, preferences concerning the nature of government can trump goal preferences when decision-makers use performance data.
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Decision-makers are prone to selectively seek and interpret information in light of preexisting stereotypes, beliefs, and social identities.
“Following a motivated reasoning logic, this growing body of literature has established that decision-makers are prone to selectively seek and interpret information in light of preexisting stereotypes, beliefs, and social identities.”
From Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice (2023) · cites this paper as Christensen et al. 2018
Searches for motivated reasoning, selective interpretation, stereotypes, and social identities found no relevant passage from the paper’s full text. The indexed results returned only abstract or bibliographic material, which cannot establish this verdict under the specified evidence rule. (LLM, conf=0.69)
Experimental — accuracy not yet measuredDecision-makers assign greater weight to information congruent with prior beliefs and contest inputs that contradict them.
“They assign greater weight to information congruent with prior beliefs and contest inputs that contradict them”
From Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice (2023) · cites this paper as Christensen et al. 2018
Searches for prior-belief congruence, confirmation bias, and contradictory performance data returned no substantive passage outside the Abstract (no page given). The available body-text passages therefore do not establish that decision-makers give greater weight to congruent information or contest contradictory inputs. (LLM, conf=0.68)
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The case for motivated reasoning.
Kunda, Z. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.108.3.480 · Cited by 9,022 · see citing works
Interpreting performance information: Motivated reasoning or unbiased comprehension.
Baekgaard, M., & Serritzlew, S. (2016) · Public Administration Review · doi:10.1111/puar.12406 · Cited by 188 · see citing works
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Alon-Barkat, S., & Busuioc, M. (2023) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/muac007 · Cited by 469 · see citing works
- Authors
- Christensen, J., Dahlmann, C. M., Mathiasen, A. H., Moynihan, D. P., & Petersen, N. B. G.
- Affiliations
- Aarhus University (DK)
- Ministry of Finance (IL)
- The Ministry for Economic Affairs and the Interior
- University of Wisconsin–Madison (US)
- Corresponding author
- Moynihan, Donald P
- Venue
- Journal of Public Administration Research and Theory
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-02-06
- Volume
- 28
- Issue
- 2
- Pages
- 197-211
- ISSN
- 1053-1858 (ISSN-L)
- 1477-9803
- OpenAlex
- W4243055431
- Cited by
- 74
- References
- 3
- Citations by year
- 2026: 8 · 2025: 2 · 2024: 11 · 2023: 5 · 2022: 14 · 2021: 12 · 2020: 12 · 2019: 7 · 2018: 3
- FWCI
- 20.74
- Type
- journal article
- Language
- en
- Open access
- green
- pure.au.dk
- Licence
- Locations
- Journal of Public Administration Research and Theory (publishedVersion)
- Topics
- Social Sciences › Public Administration › Public Policy and Administration Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Keywords
- performance evaluation, elected officials, goal preferences, cognitive dissonance, academic performance, test scores, student well-being, accountability, public sector management
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