Strengthening the role of evidence in policy‐making is increasingly seen as crucial for the quality and legitimacy of public policies. Both among practitioners and scholars, there is a growing awareness that evidence‐informed policy‐making not only depends on the rigor and relevance of the research, science communication or features of policy‐makers. It also depends on how expertise arrangements in public organizations are organized . Yet, we currently lack a solid understanding of how organization matters for the role of evidence in policy‐making. The article presents an organizational‐theoretical perspective on how the formal organization of public bureaucracies shapes evidence use in policy‐making, with important implications for both analysis and design of expertise arrangements in public administration. The article thereby sets a new research agenda at the intersection of organizational theory and scholarship on evidence and policy‐making, which speaks directly to public administration practice.
{"title":"Evidence and Policy‐Making: An Organizational Approach","authors":"Johan Christensen","doi":"10.1111/puar.70051","DOIUrl":"https://doi.org/10.1111/puar.70051","url":null,"abstract":"Strengthening the role of evidence in policy‐making is increasingly seen as crucial for the quality and legitimacy of public policies. Both among practitioners and scholars, there is a growing awareness that evidence‐informed policy‐making not only depends on the rigor and relevance of the research, science communication or features of policy‐makers. It also depends on how expertise arrangements in public organizations are <jats:italic>organized</jats:italic> . Yet, we currently lack a solid understanding of <jats:italic>how</jats:italic> organization matters for the role of evidence in policy‐making. The article presents an organizational‐theoretical perspective on how the formal organization of public bureaucracies shapes evidence use in policy‐making, with important implications for both analysis and design of expertise arrangements in public administration. The article thereby sets a new research agenda at the intersection of organizational theory and scholarship on evidence and policy‐making, which speaks directly to public administration practice.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"107 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145382292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"\u0000Futures for the Public Sector. By G. Bouckaert, A. Hondeghem, T. Steen, and S. Van de Walle (eds), Leuven: Leuven University Press, 2025. ISBN: 978-9-46-270450-3\u0000","authors":"Tom Christensen, Per Lægreid","doi":"10.1111/puar.70054","DOIUrl":"https://doi.org/10.1111/puar.70054","url":null,"abstract":"<h2> Conflicts of Interest</h2>\u0000<p>The authors declare no conflicts of interest.</p>","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"39 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145396547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"\u0000Rethinking Democratic Innovation: Cultural Clashes and the Reform of Democracy. By Frank Hendriks, Oxford: Oxford University Press, 2023. 288 pp. £78 (hardback). ISBN: 978-0-19-284829-1\u0000","authors":"Nicole Curato","doi":"10.1111/puar.70052","DOIUrl":"https://doi.org/10.1111/puar.70052","url":null,"abstract":"<h2> Conflicts of Interest</h2>\u0000<p>The author declares no conflicts of interest.</p>","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"20 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145396706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marc E. B. Picavet, Peter Maroni, Amardeep Sandhu, Kevin C. Desouza
Generating strategic foresight for public organizations is a resource‐intensive and non‐trivial effort. Strategic foresight is especially important for governments, which are increasingly confronted by complex and unpredictable challenges and wicked problems. With advances in machine learning, information systems can be integrated more creatively into the strategic foresight process. We report on an innovative pilot project conducted by an Australian state government that leveraged generative artificial intelligence (AI), specifically large language models, for strategic foresight using a design science approach. The project demonstrated AI's potential to enhance scenario generation for strategic foresight, improve data processing efficiency, and support human decision‐making. However, the study also found that it is essential to balance AI automation with human expertise for validation and oversight. These findings highlight the importance of iterative design to develop robust AI tools for strategic foresight which, alongside stakeholder engagement and process transparency, build trust and ensure practical relevance.
{"title":"Human–Machine Collaboration for Strategy Foresight: The Case of Generative AI","authors":"Marc E. B. Picavet, Peter Maroni, Amardeep Sandhu, Kevin C. Desouza","doi":"10.1111/puar.70048","DOIUrl":"https://doi.org/10.1111/puar.70048","url":null,"abstract":"Generating strategic foresight for public organizations is a resource‐intensive and non‐trivial effort. Strategic foresight is especially important for governments, which are increasingly confronted by complex and unpredictable challenges and wicked problems. With advances in machine learning, information systems can be integrated more creatively into the strategic foresight process. We report on an innovative pilot project conducted by an Australian state government that leveraged generative artificial intelligence (AI), specifically large language models, for strategic foresight using a design science approach. The project demonstrated AI's potential to enhance scenario generation for strategic foresight, improve data processing efficiency, and support human decision‐making. However, the study also found that it is essential to balance AI automation with human expertise for validation and oversight. These findings highlight the importance of iterative design to develop robust AI tools for strategic foresight which, alongside stakeholder engagement and process transparency, build trust and ensure practical relevance.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"1 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Do no harm (DNH) represents a foundational moral framework for public administration ethics. Prohibitive moral principles, rather than aspirational values, provide a more coherent and operational basis for ethical public service—even when confronting demands for proactive intervention. Bernard Gert's theory of common morality reveals how rationality and impartiality underpin moral rules designed to prevent fundamental harms, while acknowledging challenges of defining and ranking competing harms. This approach mirrors the U.S. Constitution and Bill of Rights, which constrain governmental action to protect individual rights. We further develop the DNH framework by examining free speech issues in higher education and extend its relevance to other controversial policy settings through a comparative ethical analysis that illustrates how institutions can navigate between harmful action and harmful inaction. DNH offers morally grounded guidance for ethical decision-making amid democratic tensions and political pressures.
{"title":"Do No Harm: A Foundational Moral Framework for Public Administration","authors":"Travis Ruddle, Darin Gates, David Hart","doi":"10.1111/puar.70038","DOIUrl":"https://doi.org/10.1111/puar.70038","url":null,"abstract":"Do no harm (DNH) represents a foundational moral framework for public administration ethics. Prohibitive moral principles, rather than aspirational values, provide a more coherent and operational basis for ethical public service—even when confronting demands for proactive intervention. Bernard Gert's theory of common morality reveals how rationality and impartiality underpin moral rules designed to prevent fundamental harms, while acknowledging challenges of defining and ranking competing harms. This approach mirrors the U.S. Constitution and Bill of Rights, which constrain governmental action to protect individual rights. We further develop the DNH framework by examining free speech issues in higher education and extend its relevance to other controversial policy settings through a comparative ethical analysis that illustrates how institutions can navigate between harmful action and harmful inaction. DNH offers morally grounded guidance for ethical decision-making amid democratic tensions and political pressures.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"39 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145241343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
William G. Resh, Yongjin Ahn, Weijie Wang, Keunyoung Eli Lee
As shutdowns have increased in frequency and length for the US federal government, such dysfunction may impact the federal government's ability to retain talent. In December of 2018 through January of 2019, the US federal government and its workforce endured the longest shutdown in its history. However, we know little about that shutdown's effects on the US federal civil service labor market. In this paper, we examine the intervening impact of the 2018–2019 government shutdown on personnel separations. Through the collection of data sources, we assess the shutdown's impact using two-way fixed effects difference-in-differences models of both whether an agency was shut down and whether the percentage of workers who were temporarily furloughed in an agency could adequately capture the “intensity” of that shutdown. Results indicate that the 2019 shutdown impacted separations and that it did so in distinct ways across different cohorts of employees in affected agencies. This work helps inform those who study or practice strategic workforce development about the impacts of political events on labor dynamics.
{"title":"Employee Turnover Effects of the 2018–2019 United States Federal Government Shutdown","authors":"William G. Resh, Yongjin Ahn, Weijie Wang, Keunyoung Eli Lee","doi":"10.1111/puar.70032","DOIUrl":"https://doi.org/10.1111/puar.70032","url":null,"abstract":"As shutdowns have increased in frequency and length for the US federal government, such dysfunction may impact the federal government's ability to retain talent. In December of 2018 through January of 2019, the US federal government and its workforce endured the longest shutdown in its history. However, we know little about that shutdown's effects on the US federal civil service labor market. In this paper, we examine the intervening impact of the 2018–2019 government shutdown on personnel separations. Through the collection of data sources, we assess the shutdown's impact using two-way fixed effects difference-in-differences models of both whether an agency was shut down and whether the percentage of workers who were temporarily furloughed in an agency could adequately capture the “intensity” of that shutdown. Results indicate that the 2019 shutdown impacted separations and that it did so in distinct ways across different cohorts of employees in affected agencies. This work helps inform those who study or practice strategic workforce development about the impacts of political events on labor dynamics.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"24 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145241951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrian Ritz, Kristina S. Weißmüller, Lorenza Micacchi, Samir P. Gomezjurado
Attracting talent to public administration is a highly relevant issue of practical concern and scholarly debate. Building on unique survey data of 424 individuals who switched jobs to join public administration, this study explores public employer attractiveness in a multi‐incentive setting, accounting for the experiences of a less explored population (i.e., job switchers) that may have different preferences regarding public sector employment compared with the more commonly investigated student samples. Combining fit theory and the expectancy‐disconfirmation model, this study reveals that intrinsic attributes and person‐job fit significantly predict job switchers' perceptions of public employer attractiveness. In contrast, extrinsic attributes—both instrumental and symbolic—are less influential factors. Moreover, public service‐related attributes have an unexpected negative effect for non‐sector switchers, suggesting a “belated” reality shock effect. These novel insights suggest public management should adopt more nuanced recruitment and retention strategies in the face of labor shortages and the war for talent.
{"title":"Job Switching Motives and Employer Attractiveness: A Comparative Analysis of Sector Switchers and Non‐Sector Switchers","authors":"Adrian Ritz, Kristina S. Weißmüller, Lorenza Micacchi, Samir P. Gomezjurado","doi":"10.1111/puar.70047","DOIUrl":"https://doi.org/10.1111/puar.70047","url":null,"abstract":"Attracting talent to public administration is a highly relevant issue of practical concern and scholarly debate. Building on unique survey data of 424 individuals who switched jobs to join public administration, this study explores public employer attractiveness in a multi‐incentive setting, accounting for the experiences of a less explored population (i.e., job switchers) that may have different preferences regarding public sector employment compared with the more commonly investigated student samples. Combining fit theory and the expectancy‐disconfirmation model, this study reveals that intrinsic attributes and person‐job fit significantly predict job switchers' perceptions of public employer attractiveness. In contrast, extrinsic attributes—both instrumental and symbolic—are less influential factors. Moreover, public service‐related attributes have an unexpected negative effect for non‐sector switchers, suggesting a “belated” reality shock effect. These novel insights suggest public management should adopt more nuanced recruitment and retention strategies in the face of labor shortages and the war for talent.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"85 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elections are essential for democracy, but the turbulence and uncertainty they bring can disrupt the functioning of public organizations. This study investigates how elections may trigger dysfunctional interpersonal dynamics and behaviors among civil servants. We specifically examine the relationship between elections and both increased interpersonal conflicts within public organizations and heightened counterproductive behaviors among civil servants. Using a longitudinal pretest–posttest design and panel regression analysis, we compare behavioral variables of 283 career civil servants during Brazil's polarized election of 2022 to those of 2023 (post‐election). The findings indicate that elections, as situations of political instability, are associated with increased dysfunctional behaviors among civil servants, particularly in public organizations with higher susceptibility to politicization.
{"title":"Bureaucrats in Campaigns: Elections Increase Dysfunctional Behaviors Among Civil Servants","authors":"Gustavo M. Tavares, Joana Story, Gabriela Lotta","doi":"10.1111/puar.70046","DOIUrl":"https://doi.org/10.1111/puar.70046","url":null,"abstract":"Elections are essential for democracy, but the turbulence and uncertainty they bring can disrupt the functioning of public organizations. This study investigates how elections may trigger dysfunctional interpersonal dynamics and behaviors among civil servants. We specifically examine the relationship between elections and both increased interpersonal conflicts within public organizations and heightened counterproductive behaviors among civil servants. Using a longitudinal pretest–posttest design and panel regression analysis, we compare behavioral variables of 283 career civil servants during Brazil's polarized election of 2022 to those of 2023 (post‐election). The findings indicate that elections, as situations of political instability, are associated with increased dysfunctional behaviors among civil servants, particularly in public organizations with higher susceptibility to politicization.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"39 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prior research has found disparities in the allocation of disaster relief funds in the U.S. However, little attention has been paid to the role of bureaucracy in public assistance (PA) fund allocation that possibly contributes to these inequalities. This study examines whether minority bureaucratic representation promotes the allocation of PA funds in counties with more socially vulnerable populations. Multilevel modeling is utilized to test the hypotheses, using a panel dataset of 8608 county‐year observations from U.S. counties for the years 2006 to 2019. The results show that the level of disaster relief funding does not increase in proportion to disaster damage for socially vulnerable communities to the same extent as it does for less vulnerable communities. In addition, in highly vulnerable counties, PA funds relative to damage tend to be allocated at a higher rate as the share of minority officials increases, narrowing the existing gap between high‐ and low‐vulnerability counties.
{"title":"Social Vulnerability, Equity, and Representative Bureaucracy: Evidence From the Allocation of Disaster Assistance Fund in the United States","authors":"Sungyoon Lee, Gang Chen","doi":"10.1111/puar.70029","DOIUrl":"https://doi.org/10.1111/puar.70029","url":null,"abstract":"Prior research has found disparities in the allocation of disaster relief funds in the U.S. However, little attention has been paid to the role of bureaucracy in public assistance (PA) fund allocation that possibly contributes to these inequalities. This study examines whether minority bureaucratic representation promotes the allocation of PA funds in counties with more socially vulnerable populations. Multilevel modeling is utilized to test the hypotheses, using a panel dataset of 8608 county‐year observations from U.S. counties for the years 2006 to 2019. The results show that the level of disaster relief funding does not increase in proportion to disaster damage for socially vulnerable communities to the same extent as it does for less vulnerable communities. In addition, in highly vulnerable counties, PA funds relative to damage tend to be allocated at a higher rate as the share of minority officials increases, narrowing the existing gap between high‐ and low‐vulnerability counties.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"220 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145188469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When algorithmic decision‐making systems fail to function as intended, they become conduits for administrative error and risk producing arbitrary determinations through the very technologies meant to prevent them. Analysis of 71 federal and state court dockets contesting algorithm‐based determinations in disability, unemployment, and nutrition assistance programs shows how this risk manifests in practice. Findings show that deviations from legally prescribed outcomes occur when the translation of statutory requirements into computational logic is compromised by flawed data, problematic design choices, or inherent system limitations. These algorithmic administrative errors are neither isolated glitches nor purely technical problems; they constitute a systemic governance problem that cuts across legal, organizational, and technical domains. Addressing them requires coordinated oversight across all three areas, rather than reliance on post hoc troubleshooting.
{"title":"How Do Algorithmic Decision‐Making Systems Used in Public Benefits Determinations Fail? Insights From Legal Challenges","authors":"Esra Gules‐Guctas","doi":"10.1111/puar.70043","DOIUrl":"https://doi.org/10.1111/puar.70043","url":null,"abstract":"When algorithmic decision‐making systems fail to function as intended, they become conduits for administrative error and risk producing arbitrary determinations through the very technologies meant to prevent them. Analysis of 71 federal and state court dockets contesting algorithm‐based determinations in disability, unemployment, and nutrition assistance programs shows how this risk manifests in practice. Findings show that deviations from legally prescribed outcomes occur when the translation of statutory requirements into computational logic is compromised by flawed data, problematic design choices, or inherent system limitations. These algorithmic administrative errors are neither isolated glitches nor purely technical problems; they constitute a systemic governance problem that cuts across legal, organizational, and technical domains. Addressing them requires coordinated oversight across all three areas, rather than reliance on post hoc troubleshooting.","PeriodicalId":48431,"journal":{"name":"Public Administration Review","volume":"22 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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