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Record W4407351343 · doi:10.1111/psj.70001

Editorial introduction: Advancing policy frontiers—Governance, learning, and innovation in policy studies

2025· editorial· en· W4407351343 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePolicy Studies Journal · 2025
Typeeditorial
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPolicy learningCorporate governancePolitical sciencePublic administrationRegional scienceEngineering ethicsEconomicsSociologyManagementEngineeringComputer science

Abstract

fetched live from OpenAlex

Welcome to the first issue of Policy Studies Journal (PSJ) for 2025! This issue features 11 exceptional contributions—seven regular articles and four research notes, showcasing a range of topics that enhance our understanding of policy processes and outcomes. Each article reflects the journal's commitment to fostering rigorous research and innovative analysis in policy studies. As we begin this new volume, we are pleased to announce some changes within our editorial team. Dr. Heasun Choi from the University of Arkansas and Dr. Davor Mondom from Syracuse University have stepped down from their roles as Managing Editors. Their dedication and leadership have been instrumental in shaping the journal's direction, and we extend our sincere gratitude for their contributions. To support the journal's continued growth, we are excited to welcome Ms. Erica Ivins from Syracuse University as our new Managing Editor. We also welcome three new Editorial Assistants from the University of Arkansas—Ms. Rinjisha Roy, Ms. Annette Nyoni, and Mr. Travis Wagher. Their skills and enthusiasm will undoubtedly strengthen the editorial team and help us maintain the high standards our contributors and readers have come to expect. The year 2024 was a milestone year for PSJ, marked by several remarkable achievements that underscore the journal's extended influence and the vibrancy of the policy community. The number of submissions reached an unprecedented high, with 615 new manuscripts submitted, compared to 498 in 2023 and an average of 350 annually in prior years. This surge is a testament to the journal's reputation as a leading outlet for high-quality policy scholarship. We are deeply grateful to all the authors who chose to submit their work to PSJ. This increase in submissions was accompanied by a significant expansion in our peer review process. In 2024, we sent out over 2290 invitations to referees, representing a 122% increase from the previous year. Approximately 38% of invited reviewers submitted thoughtful, constructive, and detailed feedback, which authors have frequently acknowledged as invaluable, regardless of the outcome of their submissions. The contributions of these referees are essential to maintaining the integrity and quality of PSJ publications. Notably, the USA, Germany, China, the UK, Switzerland, Canada, Sweden, Italy, the Netherlands, and Denmark were the top contributing countries to our review process. We extend our deep gratitude to all reviewers for their expertise and dedication to advancing the field. PSJ also made significant strides in publication output in 2024, with a total of 55 articles published—a 67% increase compared to the previous year. Nearly 45% of these articles were made openly accessible, reflecting our commitment to broadening the reach and impact of policy research. In addition, PSJ achieved a new milestone in readership. Articles from the journal were accessed over 314,060 times in 2024, a significant increase from 208,300 full-text views in 2019. This growing engagement highlights the global reach and impact of the journal. The top countries for readership included the USA, UK, China, Australia, Germany, the Netherlands, Canada, Sweden, South Korea, and Hong Kong. We are thrilled to see PSJ articles resonating with readers worldwide and contributing to critical policy discussions. As we reflect on the successes of 2024, we are filled with optimism and enthusiasm for the year ahead. The achievements of the past year would not have been possible without the unwavering support of our authors, reviewers, and readers. Thank you for your dedication to advancing policy research and for making PSJ a cornerstone of scholarly discourse. With this strong foundation, we look forward to continuing to serve as a platform for innovative and impactful research in 2025 and beyond. Now, we would like to discuss 11 outstanding articles introduced in this issue, which highlight the complex and evolving nature of policy theory research. This collection examines themes ranging from governance structures, policy diffusion, and bureaucratic functions to administrative burdens and the role of political will in fostering innovation. Several articles explore how governance frameworks—especially polycentric governance—facilitate learning, coordination, and adaptation. Others explicate the mechanisms of policy diffusion and learning across jurisdictions, shedding light on the intergovernmental dynamics that shape policy adoption. Additionally, contributions to bureaucratic policy analysis, client credibility in service implementation, and public attitudes toward administrative burdens provide important insights into policy design and public administration. Finally, the research notes engage with pressing contemporary challenges, such as information filtering in legislative settings, the identification of core components in policy design, and how environmental disasters influence public perceptions of technological solutions. Together, these articles reflect the diversity and intellectual richness of policy studies today, advancing the field through empirical rigor and theoretical innovation. In their lead article “Learning in polycentric governance: Insights from the California Delta Science Enterprise,” Lubell et al. (2025) examine how polycentric governance structures influence policy learning through the case of the California Delta Science Enterprise. They integrate the collective learning framework and ecology of games framework to assess individual and forum-level drivers of perceived learning across the adaptive management cycle. Their findings emphasize the role of social factors—such as leadership, trust, and engagement—as key determinants of learning, rather than administrative or financial resource constraints. This study underscores the importance of fostering strong social networks and institutional trust in governance systems to facilitate effective learning and policy adaptation. In their article “Can overarching rules and coordination in polycentric governance help achieve pre-identified institutional goals over time? Evidence from farmland governance in southeastern France,” Kassis and Bertrand (2025) investigate the effectiveness of overarching rules and coordination mechanisms in polycentric governance through the case of farmland governance in southeastern France. The study explores how governance actors design and implement rules to achieve institutional goals, particularly in adapting to the local food supply challenge. The findings reveal an institutional mismatch, where governance changes occur at the organizational level but fail to translate into a transformation of rules-in-use. This analysis highlights the complexities of achieving long-term institutional change in polycentric governance and underscores the need for deeper rule-based reforms to address evolving policy challenges. In their article “Interlocal learning mechanisms and policy diffusion: The case of new energy vehicles finance in Chinese cities,” Liu et al. (2025) explore the role of interlocal learning mechanisms in policy diffusion through an analysis of financial subsidies for new energy vehicles in Chinese cities. Their study provides direct evidence of how intergovernmental site visits promote policy diffusion but also demonstrates how hierarchical government strategies can weaken this effect. The findings highlight the nuanced dynamics of policy learning and diffusion, revealing that the initiators and thematic focus of learning interactions condition the effectiveness of knowledge transfer. This research contributes to our understanding of how policy learning unfolds across jurisdictions and the factors that shape its impact on policy adoption. In their article “The triangle of bureaucratic policy analysis and the professional types of high-level civil servants: Empirical evidence from Southern Europe,” Capano et al. (2025) examine the analytical capacities and professional roles of high-level civil servants in Southern Europe, proposing a framework known as the “triangle of bureaucratic policy analysis.” Through a large-scale survey of senior civil servants in Greece, Italy, Portugal, and Spain, they classify these officials into three professional types: the political generalist, the manager, and the legal advisor. Each type is distinguished by a particular combination of policy analytical capacities, sources of information, and policy work. This framework offers a valuable comparative lens for understanding how bureaucratic expertise and information use shape policymaking across different institutional contexts. In their article “I paid into it with every paycheck I earned: How benefit type and beneficiary contributions shape attitudes about increasing or decreasing administrative burdens for social protections,” Haeder and Sylvester (2025) explore how perceptions of administrative burdens in social protection programs are shaped by benefit type and beneficiary contributions. Using a nationally representative survey, they assess public support for burden-increasing measures, such as in-person interviews and documentation requirements, as well as burden-reducing policies, such as presumptive eligibility. Their findings highlight the role of political ideology and racial attitudes in shaping preferences, with conservatives and those high in racial resentment favoring increased burdens and liberals and those with low racial resentment preferring reduced burdens. This study underscores the complex interplay of policy design, public perception, and administrative burden in shaping access to social benefits. In their article “Client credibility judgment: A source of inequity in street-level implementation,” Kang and Lee (2025) investigate how street-level bureaucrats rely on client credibility judgments in policy implementation, particularly in policing and welfare programs. Their study uses a mixed-methods approach to examine police investigations of women's sexual assault accusations, revealing that male investigators were less likely than female investigators to find these claims credible. Interviews with investigators highlight how stereotypes influence decision-making, often to the disadvantage of marginalized groups. The authors argue that increasing workforce diversity could help mitigate these biases, emphasizing the broader implications for equitable policy implementation in various domains beyond policing. In their article “Can reducing learning costs improve public support for means-tested benefit programs?” Porumbescu et al. (2025) discuss how reducing learning costs affects public support for means-tested benefit programs, focusing on the Supplemental Nutrition Assistance Program (SNAP) in the United States. Using a pre-registered survey experiment, they find that simplifying information about SNAP's application process and eligibility criteria lowers learning costs and enhances both public support and the perceived deservingness of beneficiaries. Their findings suggest that improving public understanding of social programs through clearer communication strategies can mitigate negative perceptions and increase program accessibility. This study offers valuable insights into the role of information structure in shaping public attitudes toward social welfare policies. In their research note “Information is cheap, but filtering is costly: Congressional investment in reference resources,” Craig and Russell (2025) analyze how members of Congress manage the overwhelming flow of policy information by investing in reference resources and news media. Using congressional disbursement data from the 116th and 117th Congress, they find that freshman lawmakers are more likely to allocate funds for external information filtering to navigate the complexities of legislative work. Their findings indicate that such investments are not driven by partisanship or ideology but rather by institutional experience, with junior legislators relying more on curated information sources. This study sheds light on the crucial role of information management in legislative decision-making and the costs associated with filtering vast amounts of policy-relevant data. In their research note “Unpacking core components for policy design: A comparison of synthesis approaches,” Lemire et al. (2025) explore different synthesis approaches for identifying core components of policy interventions in evidence-based policy design. Their research compares four methodologies—distillation and matching, meta-regression, framework synthesis, and qualitative comparative analysis—to assess which elements contribute most to policy success. The findings highlight how refining core component analysis can enhance policymakers' ability to determine what works, in which contexts, and for whom. This study advances the field by emphasizing the importance of precise, evidence-based policy design tailored to diverse implementation settings. In their research note “Political will as a source of policy innovation,” Shen (2025) examines the role of political will in driving drastic policy innovation, particularly in response to global challenges such as climate change and pandemics. Using the case of low-carbon city experimentation in China, this study defines political will as a combination of authority, capacity, and legitimacy among key decision-makers. The findings reveal that strong political will is linked to the enactment and implementation of bold, innovative policies, even amidst leadership transitions. This research underscores the importance of institutionalizing political will to ensure the longevity of transformative policy initiatives across different governance contexts. Finally, in their research note “Environmental disasters and ecomodernist beliefs: Insights from a quasi-natural experiment,” Sundström (2024) investigates how environmental disasters impact ecomodernist beliefs—the idea that technology can resolve environmental challenges. Using a quasi-natural experiment leveraging public opinion survey data collected during the Fukushima-Daiichi nuclear disaster, this study finds that exposure to the catastrophe significantly weakened public confidence in technological solutions to environmental problems. The effect was most substantial among more educated individuals, suggesting that beliefs shift when risks associated with technology become apparent. The findings provide broader insights into how public perceptions of science-driven environmental policies are shaped by real-world crises, with implications for climate change policy and risk communication strategies. As we conclude this editorial, we reflect not only on the scholarship presented here but also on the continued evolution of the Policy Studies Journal. We introduced changes in our editorial team, marked new milestones in submissions and readership, and reaffirmed our commitment to supporting rigorous policy research. The articles in this issue take us across diverse policy research topics, from governance and bureaucratic analysis to political will, environmental risk, and legislative decision-making. These studies remind us of the power of knowledge in shaping policy, especially in uncertain times. In an era where democratic institutions face stress tests, let us remain steadfast in our pursuit of open discourse, evidence-based policy, and institutional resilience. Until our next issue in May, we wish you continued curiosity, thoughtful scholarship, and the collective wisdom to navigate the challenges ahead. Thank you!

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.096
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.397
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it