Can Reducing Learning Costs Improve Public Support for Means-Tested Benefit Programs?

by Gregory Porumbescu, Stephanie Walsh, & Andrea Hetling 

This study examines how lowering learning costs in means-tested benefit programs, such as the Supplemental Nutrition Assistance Program (SNAP), influences public support and perceptions of beneficiary deservingness. Drawing on educational psychology research (cognitive load theory) and policy feedback theory, we investigate how the structure and clarity of information about SNAP’s eligibility and application process influence learning costs, public support, and attitudes. Through a pre-registered dose-response survey experiment, our findings show that improving the clarity of SNAP information reduces learning barriers, increasing support and positive perceptions of beneficiaries. This study is guided by two testable hypotheses:  

  1. Reducing learning costs improves comprehension drawing on educational psychology cognitive load theory. 
  2. Improved comprehension increases public support based on policy feedback theory. 

To test these hypotheses, we performed a dose-response survey experiment involving 1,677 New Jersey residents. Participants were assigned randomly to one of four groups: a control group that was given no information, and three treatment groups that were given increasingly clearer and more structured information on SNAP. The treatments were: 

Flyer: A low-structuring treatment with minimal structuring of content.
Screener: A tool that breaks the content into bite-sized, manageable chunks, mimicking state-level eligibility screens.
Video: A how-to tutorial walking participants through the eligibility process. 

After being exposed to the treatment, each participant answered a series of questions related to SNAP, with the number of questions they answered correctly comprising the dependent variable, their SNAP comprehension score. To analyze the data, we employed a one-way analysis of variance (ANOVA) to evaluate whether differences exist across the control and three treatment groups. We utilized planned contrasts to determine if the means differed significantly across each treatment group. To analyze the relationship between comprehension and program support measures, we used ordinary least squares regressions. The mediation framework improves upon traditional methods by leveraging the potential outcomes framework. By modeling intermediate pathways explicitly, this method offers improved estimates of indirect effects compared to the associations produced by standard mediation techniques.

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Figure 2. Distribution of SNAP comprehension score by treatment group. 

As shown in figure 2, providing structured, digestible information significantly enhances study participants’ knowledge. The video treatment group, which received the clearest presentation, had the highest comprehension levels, followed by the screener group. The flyer treatment group, with the least structured data, had the lowest comprehension. In addition, differences by participant racial identity emerged, as Black non-Hispanic participants show a stronger inverse relationship between SNAP understanding and perceived deservingness compared to other groups. These findings underscore the importance of comprehension in shaping attitudes toward SNAP policies. 

Findings also revealed significant indirect effects on SNAP approval, perceived deservingness, and support for increased funding. Higher comprehension connects reduced learning costs to greater support. This indicates that simplifying information delivery about complex benefit programs can enhance public approval and engagement. These results align with policy feedback theory, highlighting the importance of accessible information in shaping support for means-tested policies such as SNAP. 

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Figure 3. Indirect effects of content structure on different aspects of SNAP support. 

Empirically, the findings show that reducing learning costs not only improves knowledge but also increases support for programs like SNAP, improves positive perceptions of program beneficiaries, and draws support for program funding. These effects could carry over to other complex safety net programs like Temporary Assistance Needy Families (TANF) and Medicaid, with policy communication implications extending beyond the reduction of learning cost. 

You can read the original article in Policy Studies Journal at

Porumbescu, Gregory, Stephanie Walsh and Andrea Hetling. 2025. “ Can Reducing Learning Costs Improve Public Support For Means-tested Benefit Programs?.” Policy Studies Journal 53(1): 135–157. https://doi.org/10.1111/psj.12578.

About the Authors

Gregory Porumbescu (PhD, Seoul National University) is an associate professor in the Department of Public Administration and Policy at the University of Georgia‘s School of Public and International Affairs (SPIA). His research centers on understanding the implications of technology for government transparency and accountability. Dr. Porumbescu‘s work has been published in journals such as the Journal of Public Administration Research and Theory, Public Administration Review, Governance, and Social Science & Medicine. Prior to joining SPIA, Dr. Porumbescu served as an associate professor at Rutgers University–Newark. There, he was a co-founding principal investigator for the New Jersey State Policy Lab, an initiative dedicated to enhancing evidence based policy making in state governments. During his time at Rutgers, he was also appointed to serve on the AI, Equity, and Literacy Working Group, contributing to Governor Phil Murphy‘s New Jersey AI task force. Dr. Porumbescu‘s research has been supported by organizations such as the National Science Foundation, Korean Research Foundation, and the New Jersey Office of the Secretary of Higher Education.

Stephanie Walsh is Assistant Director of the Heldrich Center. She earned her doctorate in planning and public policy at Rutgers University. She also holds a Master‘s degree in public policy. Stephanie also serves as the Director of the New Jersey Statewide Data System, overseeing the governance, research agenda, and publications that use the linked longitudinal data. Her research interests focus on how data can inform public programs and policies to better support service delivery and improve individual outcomes.

Andrea Hetling is a Professor at the Edward J. Bloustein School of Planning and Public Policy at Rutgers University. Dr. Hetling‘s research interests focus on how public programs and policies can support economic well-being and financial stability among vulnerable populations, including families living in poverty and survivors of intimate partner violence. In 2019, Andrea was selected as one of only five Family Self-Sufficiency and Stability Research Network (FSSRN) Scholars and awarded a five-year grant by the US Department of Health & Human Services, Administration for Children and Families. Before getting her Ph.D., Andrea worked as a program administrator at a domestic violence agency, focusing on advocacy and development issues. As a strong believer in the public impact of applied policy research, Andrea regularly connects her research projects with her teaching and mentoring and to her service to the greater community.

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Advocacy Groups, Policy Subsidies, and Policy Change: The Case of Teacher Evaluations

by Leslie K. Finger

In many policy areas, powerful interest groups—such as labor unions or industry associations—shape and protect the status quo. When these vested interests have significant financial and political clout, how do policymakers manage to enact major reforms against their preferences? My paper examines this question through the lens of teacher evaluation policy in the U.S., revealing that advocacy groups play a crucial role in facilitating policy change by providing what I call policy subsidies: information, resources, and capacity that enable reform-minded policymakers to push past entrenched opposition.

My primary research question is: How are powerful interest groups with a stake in the status quo overcome? In the case of teacher evaluations, many states moved to incorporate student growth measures—often derived from standardized testing—as a sizable portion of their teacher evaluation systems despite fierce resistance from teachers’ unions. I investigate why some states were more successful than others in adopting and sustaining these reforms, focusing on the role of advocacy groups in supporting policy change.

Teachers’ unions have long been among the most influential state-level interest groups, using their financial resources and political leverage to shape education policy. Given their strength, it would be expected that states would avoid implementing teacher evaluations that include student achievement as a key factor. Yet, from 2009 to 2015, a growing number of states adopted such provisions. Why?

I argue that advocacy groups—such as education reform organizations—provided information (i.e., policy ideas, analysis, data) and capacity (i.e., time-consuming actions). I call these assets policy subsidies. By reducing the costs associated with enacting and implementing controversial reforms, policy subsidies can make it easier for policymakers to challenge vested interests and push through significant policy changes.

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To test this theory, I conducted a 50-state quantitative analysis of teacher evaluation policymaking between 2010 and 2011 and case studies of Minnesota and Wisconsin, two states that took different policy paths. The study tested two primary hypotheses:

Hypothesis 1: States where advocacy groups provide policy subsidies are more likely to implement policy change opposed by vested interests than those without such groups.

Hypothesis 2: States where those in power are open to change are more likely to implement significant policy change opposed by vested interests than those without such politicians in power.

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My quantitative analysis showed that states where advocacy groups were active were significantly more likely to pass teacher evaluation reforms (see Figure 1). The effect of advocacy groups was strongest in states where Republicans controlled the legislature. In these states, advocacy groups helped craft policies that successfully incorporated student achievement as a “significant” factor in teacher evaluations (see Table 5). My case studies of Minnesota and Wisconsin illustrate this dynamic in action. In Minnesota, advocacy groups worked closely with Republican lawmakers to provide both technical policy assistance and political support, leading to the adoption of evaluation reforms. In contrast, Wisconsin—despite similar political conditions where Republicans were in control—lacked strong advocacy group engagement, and teacher evaluation reform was delegated to the bureaucracy, where, in the absence of advocacy group involvement, the student achievement provision was compromised during implementation..

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This study demonstrates that interest group influence is not absolute; advocacy groups can play a decisive role in shifting policy outcomes by lowering the costs of reform, even where vested interests are strong. Additionally, having policymakers favorable to a particular policy is not enough to overcome vested interests— policymakers need interest group allies to help them craft and implement those policies that might otherwise be stopped in their tracks by powerful interest groups. The concept of policy subsidies extends beyond education, offering insights into how policy entrepreneurs in other domains—such as climate change, healthcare, or labor policy—can challenge entrenched interests.

You can read the original article in Policy Studies Journal at

Finger, Leslie K. 2024. “ Advocacy Groups, Policy Subsidies, and Policy Change: The Case of Teacher Evaluations.” Policy Studies Journal 52 (4): 777–808. https://doi.org/10.1111/psj.12538.

About the Author

Leslie K. Finger is an Assistant Professor of Political Science at the University of North Texas. Her research focuses on interest groups, policymaking, and state and local politics with a focus on education policy. Her work has appeared in various journals, including Perspectives on Politics, Governance, Policy Studies Journal, Interest Groups & Advocacy, American Politics Research, and State Politics & Policy.

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Learning in Polycentric Governance: Insights from the California Delta Science Enterprise

by Tara Pozzi, Mark Lubell, Tanya Heikkila, Andrea K. Gerlak, & Pamela Rittelmeyer

Science enterprises play an increasingly important role in shaping the policy process. While existing literature explores the nexus of science and decision-making, research is limited by a lack of empirical institutional analysis—specifically how science is shaped by and a feature of governance institutions. To address this gap, we integrate the ecology of games framework (EGF) and collective learning framework (CLF) to examine how polycentric systems of science actors and forums influence policy-relevant learning. This exploration is guided by three types of hypotheses to account for diverse actors:

  1.  Individual-level hypotheses consider how organizational affiliation, professional involvement, forum participation, and expertise on diverse issues of individual actors participating in a science enterprise may shape perceived learning.
  2. Forum-level hypotheses consider how variance in forum social dynamics, institutional structure, and functional domain characteristics may shape perceived learning.
  3. The learning stage hypothesis suggests that the perceived level of learning will be lower at later stages of the adaptive management cycle.

In 2021, we conducted a survey of science actors involved in managing and governing the California Delta. The survey participants were individuals who produce, interpret, or use science for Delta policymaking, including academics, government agency officials, and nonprofit and community representatives. Respondents were identified through a purposive sampling, using the Delta Science Program to disseminate the survey electronically to numerous listservs. The survey measured core perceptions of the regional science forums, such as extent of professional involvement and participation, expertise of diverse issues, leadership effectiveness, representative engagement, coordination, resources, and forum purpose.

To analyze the data, we estimated four generalized linear multi-level models using Bayesian methods. The models analyze the effect of individual- and forum-level variables on perceived learning across different science forums, with a separate model for a composite scale and each stage of the adaptive management cycle.

As illustrated in Figure 5, the social and institutional attributes of science forums are the most important drivers of learning, relative to the human and financial capital attributes of the forums or the level of individual actor engagement. For example, the variables of leadership, trust, and coordination consistently have the largest positive influence on all learning stages of adaptive management, whereas the resources variable is consistently less positive. This finding suggests that administrative and financial resource limitations are less important for learning than social drivers.

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Figure 5. Bayesian plot for learning models associated with “plan,” “do,” and “evaluate and respond” stages of adaptive management, and combined stages.

Through integrating two policy process frameworks, we have created a new theoretical basis for analyzing policy-related learning within polycentric governance systems. Our Bayesian approach allowed us to visualize the changing importance of social dynamics versus administrative resources across developmental stages of scientific forums. As polycentric systems grow over time, resources pose less limitations on their effectiveness. Our forum-level results also reaffirm findings in a comparative case study that social capital plays an important role in policy-related learning. The findings shed light on how science shapes and is shaped by the policy process, providing valuable insights into how policy-relevant learning occurs in polycentric governance systems.

You can read the original article in Policy Studies Journal at

Lubell, Mark, Tara Pozzi, Tanya Heikkila, Andrea K. Gerlak and Pamela Rittelmeyer. 2025. “ Learning in Polycentric Governance: Insights From the California Delta Science Enterprise.” Policy Studies Journal 53(1): 7–28. https://doi.org/10.1111/psj.12581.

About the Authors


Tara Pozzi is a PhD candidate in the Graduate Group in Ecology at the University of California, Davis. Her research focuses on how governance networks influence climate adaptation policy and planning.



Mark Lubell is a Professor in the Department of Environmental Science and Policy at University of California Davis. His research focuses on human behavior and the role of governance institutions in solving collective action problems and facilitating cooperation.


Tanya Heikkila is a Professor in the School of Public Affairs at University of Colorado Denver. Her work investigates how conflict and collaboration arise in policy processes, and what types of institutions support collaboration, learning, and conflict resolution.


Andrea K. Gerlak is a Professor in the School of Geography and Development and Director of the Udall Center for Studies in Public Policy at the University of Arizona. Her work addresses institutions, learning,  and governance of environmental challenges.


Pamela Rittelmeyer is a Senior Regulatory Analyst of energy efficiency programs at the California Public Utilities Commission.  Her work centers around better understanding various perspectives of environmental problems and supporting policy development.

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Interlocal learning mechanisms and policy diffusion: The case of new energy vehicles in Chinese Cities

by Weixing Liu, Liang Ma, Xuan Wang, & Hongtao Yi

While policy diffusion based on learning mechanisms has received extensive scholarly interest, this literature has at least two limitations. First, policy learning is usually identified through indirect evidence, such as geographical proximity or successful policy innovations adopted in other jurisdictions. Second, measures of policy learning are used without considering how they interact with other factors. 

To address these limitations, our study measures policy learning through field learning conducted by local government officials, using the case of Chinese local financial subsidy policy for new energy vehicles (NEVs). Site visits from local government officials offer a direct mechanism of policy learning by enabling policymakers to exchange strategies and information with peers about the “know-how” of policy implementation. 

H1: When city i initiates policy learning from city j, policy innovation is more likely to diffuse from city j to city i.

We also examine the moderating effect of top-down mandates on . While governments learn from each other, they are also embedded in a multi-level regime, in which higher level authorities mandate or incentivize subordinate governments to adopt policies they favor. If the top-down signals are strong, peer-to-peer learning may be weakened.

H2: The adoption of the focal policy by the superior government will attenuate the impact of policy learning on policy diffusion across jurisdictions.

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Figure 1. The theoretical framework and hypothesis

To test these hypotheses, we collected data on the adoption of NEV policies in 282 cities between 2014 and 2018. The key independent variable captures interlocal learning between cities. To identify site visits, we searched for the keywords of “visits and learning” and “learning and exchange” on official websites and official papers in the cities. To examine the role of top-down mandates, we included a variable indicating whether NEV policies had been adopted by the superior government. Finally, we controlled for other horizontal diffusion mechanisms.

Using a directed EHA method based on a logit model, we find that the direct information exchange between local governments can significantly promote the diffusion of the NEVs’ local financial subsidy policies between cities. However, the purpose for the site visit has different implications on the diffusion of the policy. Empirical results indicate that compared with policy learning within public services, urbanization, government management, and cooperative projects, learning in the field of economic development, which is more related to the NEVs financial subsidy policy, can significantly promote the diffusion of policy innovation.

Consistent with H2, the results also show that policy behavior signals from a superior government can replace or decrease the impact of interlocal policy learning on policy diffusion. Lastly, the research shows that the level of authority of the government official who conducts the site visit plays a role in the adoption of the policy. That is to say, the more authority that the visiting government official has, the higher the chance of adoption of that policy in the other city. 

In summary, the findings indicate that policy learning plays a crucial role in policy diffusion, and governments can leverage site visits and other learning approaches to facilitate policy adoption. While conventional information channels help policymakers to learn about emerging policy innovations, face-to-face interactions may be more influential in policy diffusion. Particularly for leading government officials with scarce attention to specific policies, their dedicated site visits could boost policy learning and then policy diffusion and spread.

You can read the original article in Policy Studies Journal at

Liu, Weixing, Liang Ma, Xuan Wang and Hongtao Yi. 2025. “ Interlocal Learning Mechanisms and Policy Diffusion: The Case of New Energy Vehicles Finance in Chinese Cities.” Policy Studies Journal 53(1): 49–68. https://doi.org/10.1111/psj.12576.

About the Authors

Weixing Liu is an assistant professor at the School of Government, University of International Business and Economics. His research focuses on policy process, environmental policy, and networks.

Liang Ma is a professor at the School of Government at Peking University. His research interests include digital governance and performance management.

Xuan Wang is an assistant professor at the National School of Development at Peking University. His research interests include tax policy, China’s economy, and policy innovations.

Hongtao Yi is a professor at Askew School of Public Administration and Policy at Florida State University. His research interest focuses on network governance and environmental policy.

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Not a Public Good, but a Public Responsibility: Rethinking AMR Governance

by Isaac Weldon

Governance failures often stem from a fundamental error: misdiagnosing what needs to be governed. As Nobel Prize laureate Elinor Ostrom argued, different types of goods—whether private, public, or common-pool—create distinct collective action problems, each demanding tailored solutions. When policymakers misidentify a resource or conflate its nature with how it should be governed, they risk applying the wrong tools and crafting ineffective policies. These misdiagnoses plague many of today’s biggest challenges, from climate change to biodiversity loss and global health.

Effective governance begins with defining what resources are being managed, how they are being depleted, and what institutional arrangements are necessary to sustain them. In a recent Policy Studies Journal article, my co-authors and I applied this logic to antimicrobial resistance (AMR), one of the world’s most pressing health challenges.

AMR—the third leading cause of global mortality—occurs when microbes evolve resistance to antimicrobial drugs like antibiotics, rendering treatments ineffective. Every use of antimicrobials increases this risk, and millions still lack access to these lifesaving medicines. AMR governance requires balancing conservation with equitable access and innovation, yet current policies struggle because they misdiagnose the problem itself.

Central to AMR are two distinct types of goods:

  • Antimicrobials (the physical pills) are private goods: They are excludable (they require prescriptions and money to access) and rivalrous (one person’s use prevents another from using the same dose). Historically, the default governance model for antimicrobials has been market-driven, relying on intellectual property protections and pricing mechanisms to incentivize production and ration use.
  • Antimicrobial effectiveness (the ability of these drugs to work over time) is a common-pool resource: It is non-excludable (difficult to prevent people from benefiting from it) and rivalrous (overuse diminishes effectiveness for all). Markets fail to govern this resource because firms and individuals benefit from selling and consuming more antimicrobials, not from ensuring long-term effectiveness.

But the nature of a resource does not dictate how it should be governed. Just because antimicrobials are private goods does not mean they should be left to market forces alone. Many excludable and rivalrous private goods—such as electricity and water—are publicly regulated because they are essential and generate widespread externalities. However, the fact that antimicrobial effectiveness is critical for public health does not mean it should be framed as a public good. Unlike true public goods, antimicrobial effectiveness is rivalrous—a distinction that shapes its governance. The pill (a private good) and its effectiveness (a common-pool resource) are distinct but interconnected, and their governance must reflect this.

In short: antimicrobials are private goods, antimicrobial effectiveness is a common-pool resource, and their governance must be a public responsibility.

AMR is not an isolated case. Climate change, biodiversity loss, and global health challenges all suffer when the wrong governance model is applied to the wrong kind of resource. Misidentifying the nature of a resource, or conflating its nature with its optimal governance regime, leads to mismatches that render solutions ineffective.

Better governance starts with better problem definitions. If we fail to define what is being governed, we will continue applying the wrong solutions—at great cost to human health and the planet.

You can read the original article in Policy Studies Journal at

Weldon, Isaac, Kathleen Liddell, Susan Rogers Van Katwyk, Steven J. Hoffman, Timo Minssen, Kevin Outterson, Stephanie Palmer, A. M. Viens and Jorge Viñuales. 2024. “ Analyzing Antimicrobial Resistance As a Series of Collective Action Problems.” Policy Studies Journal 52(4): 833–856. https://doi.org/10.1111/psj.12552.

About the Author

Isaac Weldon is an Assistant Professor of Law with the Centre for Advanced Studies in Bioscience Innovation Law (CeBIL) at the University of Copenhagen and an Investigator with the Global Strategy Lab at York University, Toronto. His research investigates antimicrobial resistance, emerging pandemic threats, and sustaining our planetary health. Recent works have also been featured in Perspectives on Politics and Globalization and Health.

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The Power of Political Will in Driving Policy Innovation

by Shiran Victoria Shen

In a world facing climate crises, pandemics, and geopolitical shifts, governments must embrace bold policy innovation.  Scholars have long examined the drivers of policy change—ranging from economic conditions to policy diffusion and entrepreneurial leadership. Yet, one critical but underexplored factor is political will.

In my recent Policy Studies Journal article, I argue that political will is a key driver of drastic policy innovation—policy changes so bold that they redefine governmental priorities and novel policy instruments that any jurisdiction has rarely tested in the country. Using China’s low-carbon city experimentation as a case study, I show that strong political will among local leaders significantly increased the likelihood of drastically innovative climate policy measures being adopted and implemented.

What Is Political Will?

Political will is the commitment of key decision-makers (i.e., elected politicians in democracies or political leaders in autocracies) to enact and implement policies, even at political or financial risk. It consists of three key components:

  1. Authority – The power to enact and enforce policies
  2. Capacity – The fiscal, human, and administrative resources to implement them effectively
  3. Legitimacy – Stakeholder acceptance, which is crucial for garnering support and reducing resistance

Political will is distinct from political power.  While power provides the means, political will determines whether leaders use that power to drive bold policy change.

How Political Will Shapes Drastic Policy Innovation

China’s low-carbon city pilot provides a suitable setting to study political will. Unlike many centrally led pilots, this initiative required cities to voluntarily apply and commit their own resources. My research examines the second batch of pilot cities, which were selected based on leadership engagement, demonstrability, and locally driven decarbonization strategies.

Political will is gauged by the Leader of the Low-Carbon City Construction Leading Group (LCCLG). I found that cities where the prefectural party secretary—the highest-ranking local official—steered the LCCLG were significantly more likely to introduce and implement drastically innovative climate policies. These leaders not only set ambitious goals but also effectively mobilized resources and overcame bureaucratic resistance. In contrast, cities where their low-carbon city pilots were led by lower-ranking officials demonstrated a weaker commitment, resulting in fewer innovative policies proposed or implemented.

Why Institutionalizing Political Will Matters

A critical insight from my study is that when political will is institutionalized, policy innovation persists despite leadership turnover. In China, this was achieved through LCCLGs, which maintained policy continuity even when key officials changed.

This challenges the conventional wisdom that leadership changes disrupt policy innovation.  Instead, embedding political will within the leadership structure sustains transformative policy efforts over time.

Lessons for Policymakers Worldwide

Although my case study focuses on China, the implications extend beyond authoritarian regimes. In democracies, political will is shaped by electoral incentives, coalition-building, and public advocacy, requiring a different approach to measurement. In authoritarian states, political will aligns closely with leader rank and authority, whereas in democracies, multiple veto points necessitate a broader set of variables.

Yet the core principle remains: bold policy innovation depends on committed leadership willing to take risks and overcome resistance.

For policymakers and scholars, political will should be explicitly considered as a critical driver of policy innovation. Whether tackling climate change, public health, or economic shock, fostering and institutionalizing political will enables governments to implement transformative policies that endure.

You can read the original article in Policy Studies Journal at

Shen, Shiran Victoria. 2025. “ Political Will As a Source of Policy Innovation.” Policy Studies Journal 53(1): 185–200. https://doi.org/10.1111/psj.12571.

About the Author

Shiran Victoria Shen is a senior research scholar and the lead for the China Energy Program at the Stanford Doerr School of Sustainability.  Her research examines how incentives and institutions shape climate and environmental actions.  More broadly, she is interested in key issues in public policy and governance.

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Call for Papers: PSJ Special Issue on Policy Diffusion 

The Policy Studies Journal (PSJ) invites submissions for a special Issue focusing on policy diffusion. Since Walker’s groundbreaking work 65 years ago, policy diffusion research has both burgeoned and stagnated at times (Mooney 2021). It continues to be a key policy process theory that has experienced significant advancements in the last decade in data (Boehmke et al. 2020), methods (e.g., Linder et al. 2020), theory (e.g., Colvin and Jansa 2024), and broadening from the American federal context (e.g., Cao 2010, Zhang and Zhu 2019).

This special issue invites papers that engage on any of the four fronts listed above: data, methods, theory, and context. Importantly, the aim is not to publish studies of a single policy using conventional methods (e.g., Event History Analysis) that confirm existing theory. We are looking for work that continues to push the boundaries of policy diffusion research. Papers should aim to explain diffusion broadly and should only focus on a single policy if it is a unique case that illustrates the boundaries of existing theory. These could include papers that:

  • Provide methodological and/or theoretical advancements on our specification and understanding of the key mechanisms of diffusion.
  • Explore diffusion dynamics in contexts beyond the American federal system and Europe. These could be new within-country contexts or underexplored regions like Africa.
  • Propose new methods for conducting diffusion research.
  • Link the macro-level patterns most commonly observed in diffusion studies (e.g., number and timing of adoptions) with the micro-level behavioral foundations that are assumed to be generating those patterns.
  • Builds bridges between policy diffusion and other major policy process theories.
  • Make greater use of the State Policy Innovation and Diffusion (SPID) database (https://dataverse.harvard.edu/dataverse/spid).

We also invite shorter pieces (3,000 – 5,000 words), including those that wrestle with the translational and practical implications of policy diffusion research for policymaking and governance. These will be published together in Policy Theory & Practice (a rolling special issue associated with PSJ) and will be bound with the PSJ special issue through our editorial introduction. This allows us to leverage all opportunities offered by PSJ to advance our thinking about policy diffusion.

For details on PSJ article types and their requirements, see https://onlinelibrary.wiley.com/page/journal/15410072/homepage/forauthors.html.

**The deadline for submitting a manuscript for the Special Issue is December 1, 2025**

Potential contributors to the Special Issue may participate in a “Peer Paper Exchange” in the spring of 2025, through which authors can obtain informal feedback from peers who also plan to submit a paper to the Special Issue and opt to participate in the Exchange. For the exchange, papers will be paired together so the authors can exchange and provide each other with feedback. It is not a formal workshop. Participation in the exchange is intended to support the development of papers but has no bearing on the peer review process that will be undertaken by PSJ once papers are submitted to the journal. That review process is formal and entirely independent of the Peer Paper Exchange.

To participate in the Peer Paper Exchange, please submit a one-page abstract that explains your research question, the contribution of your research to policy diffusion, and the data and methodological approaches you plan to use to answer your research question, along with the paper title and author information. This is due by April 1st. Notifications of acceptance to participate in the Peer Paper Exchange will be made by May 15th.

Authors participating in the Exchange must share their draft papers with fellow participants by September 1st. Comments from the Exchange review will be returned to the authors by October 1st.

To apply for the Peer Paper Exchange, please visit: https://uark.qualtrics.com/jfe/form/SV_5vwfxRpAF5NKeVM

Special Issue Schedule Summary:

  • April 1, 2025: One-page proposal for peer exchange
  • May 15, 2025: Decisions sent for inclusion in peer exchange
  • September 1, 2025: Paper shared with peer exchange
  • October 1, 2025: Comments returned from peer exchange
  • December 1, 2025: Deadline for submitting to PSJ

If you have any questions, please contact Dr. Dan Mallinson at policystudiesjournal@gmail.com

Unpacking Core Components of Interventions: A Comparison of Synthesis Approaches

by Sebastian Lemire & Allan Porowski

Evidence reviews have become a key tool for evidence-based policy, helping policymakers make informed decisions about which interventions to implement. Traditionally, these reviews have focused on the outcomes of entire interventions. However, the growing interest in the specific elements that drive intervention effect has over the past ten years led to a focus on core components—the key features that contribute to an intervention’s effectiveness. Core components refer to the essential features of an intervention—such as activities, services, or practices—that available evidence shows are effective in driving outcomes. Identifying these core components can help create more effective interventions by highlighting the features that contribute most to desired outcomes. Identifying with greater precision what works, in which contexts, and for which populations can help policymakers assess which existing policies and interventions are (or are not) likely to be effective and better understand why policies or interventions that share similar characteristics may achieve different results.

In our PSJ research note, we describe four evidence synthesis approaches—distillation and matching model, meta-regression, framework synthesis, and qualitative comparative analysis—to identify these core components. Each approach offers unique advantages depending on the available data and intervention context. Understanding the various approaches, along with their respective advantages and limitations, can help researchers select the most appropriate analysis method based on the purpose of their evidence review, the intended audience, and how the findings will be applied.

To further enhance the use of core components analysis, we call for advancements in improving reporting conventions, using multi-phased designs, and expanding applications of core component analysis. Providing more detailed reporting of the intervention characteristics, setting, participants, implementation, and costs in primary studies provides for a stronger foundation for core components analysis. To enhance core components analyses even further, a multi-phase approach can be used. In the first phase, researchers analyze evidence in a specific field, and in the second phase, they collaborate with practitioners to design field trials based on the findings to evaluate the effectiveness of core components Finally, applying core components analysis across a broader range of interventions, practices, and policies, with more diverse populations, and in a variety of settings can help policymakers understand how evidence-based interventions and policies should be designed to ensure that they promote positive outcomes in diverse contexts.

You can read the original article in Policy Studies Journal at

Lemire, Sebastian, Laura R. Peck, Allan Porowski and Allison Dymnicki. 2025. “ Unpacking Core Components For Policy Design: A Comparison of Synthesis Approaches.” Policy Studies Journal 53(1): 171–184. https://doi.org/10.1111/psj.12567.

About the Authors

Sebastian Lemire is a Senior Scientist at Abt Global. His research focuses on systematic evidence reviews, alternative approaches to impact evaluation, and evaluation capacity building. He currently serves on the executive board of the American Evaluation Association and on the editorial advisory boards of Evaluation and the American Journal of Evaluation.

Allan Porowski is a Principal Associate at Abt Global. He is a leading expert in the design, execution and analysis of randomized controlled trials, quasi-experimental studies and national cross-site evaluations of education, health, and other social interventions.


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Intergovernmental Implementation in a Time of Uncooperative Federalism: Immigration Enforcement and Federal Secure Communities Program, 2011–14

by William D. Schreckhise & Daniel E. Chand

On the first day of his second term, Present Trump signed an executive order taking aim at “so-called sanctuary jurisdictions,” marking his latest attempt to step up immigration enforcement in progressive, pro-immigrant communities. While there’s no universal definition as to what constitutes “sanctuary” jurisdictions, the most accepted definition are communities that limit state and local law enforcement participation with Immigration and Customs Enforcement (ICE), enforcement program known as Secure Communities (S-Comm).

S-Comm is, essentially, a nationwide immigration screening program. It has long been commonplace for jails to share an individual’s name and biometric information (e.g., photo, fingerprints, etc.) with federal authorities to see if the person has a criminal record or any outstanding warrants when an individual is arrested and booked. S-Comm further shares this information with ICE, which screens the individual for immigration violations.

If ICE suspects an individual of being in the country without proper authorization, it can issue an ICE detainer, which requests the jail to hold the individual for up to 48 hours so that ICE can take custody of the person and begin deportation proceedings. ICE can, and frequently does, detain individuals under S-Comm regardless of whether the charges for the original arrest are dropped. From the time S-Comm became nationwide operational in 2013 through 2020, roughly 700,00 individuals were removed from the country.

S-Comm was (and still is) controversial. Numerous local governments, mostly counties, have passed various measures in opposition to the program. Other governments went further, explicitly prohibiting their officers from contacting ICE and prohibiting their agencies from spending money in ways that otherwise could help ICE. However, other governments essentially did the opposite with some states requiring their counties to honor ICE detainer requests.

In our PSJ article, we examined the extent to which state and local governments play a role in implementing federal policy, focusing on the patterns of interaction between federal actors and nonfederal actors implementing S-Comm. Specifically, we examine the extent to which localities and states could hinder or help with the program’s implementation.

To determine what role these subnational policies could play, we collected county-level ICE removal data and information about which states and localities adopted policies aimed at either helping ICE by mandating their agencies honor detainer requests or hindering ICE’s efforts prohibiting that they cooperate with ICE’s detainer requests.

We found that states and counties can indeed play a prominent role. Taking these various other factors into account, counties that passed so-called “sanctuary” ordinances saw roughly 30% fewer deportations. Counties in states that had passed their own state-level “sanctuary” laws saw a similar decline. States that passed legislation requiring their localities to cooperate with ICE saw 44% more deportations.

We also wanted to determine to what extent the presence of the cooperative and noncooperative policies was reflected in what ICE itself was doing. It is one thing for counties and states to simply refuse to cooperate; it is entirely another for ICE to modify its own behavior because of these policies. To do this, we redirected the variables to determine whether they could help explain the extent to which ICE was making detainer requests in the first place. Again, we found that ICE was making fewer detainer requests in states and counties where cooperation with ICE was prohibited and making more in states where the counties were directed to cooperate.

Considering the ongoing debate over immigration enforcement policies, our findings underscore the significant impact of state and local policies on the implementation of federal initiatives, like S-Comm. The presence of subnational policies not only shape the outcome of the policy, but also how the federal agencies, like ICE, behave when implementing federal programs.

You can read the original article in Policy Studies Journal at

Schreckhise, W.D. and Chand, D.E. (2021), Intergovernmental Implementation in a Time of Uncooperative Federalism: Immigration Enforcement and Federal Secure Communities Program, 2011–14. Policy Stud J, 49: 1160-1188. https://doi.org/10.1111/psj.12426

About the Authors

William D. Schreckhise is professor in the University of Arkansas’ Department of Political Science. He earned his Ph.D. from Washington State University’s Department of Political Science. His research interests include policy implementation and bureaucratic discretion. His the author of Evaluating American Democracy and Public Policy.


Daniel E. Chand (“Danny”) received his Ph.D. in Public Policy in the Policy Management specialization at the University of Arkansas. His research focuses on the implementation of immigration policy, examining the roles of actors such as immigrant-serving nonprofits, immigration judges, and ICE officers. In addition to PSJ, his work has appeared in journals like Policy Sciences and Voluntas.

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Mixed Messages and Bounded Rationality: The Perverse Consequences of REAL ID for Immigration Policy

by Maureen Stobb, Banks Miller, & Joshua Kennedy

The President and Congress have renewed efforts in the past year to reshape immigration policy. Yet, if history can teach us anything, it is that outcomes in this area tend not to match intent. Our research looks at a clear example of this mismatch, the REAL ID Act, a law aimed at tightening refugee admissions by taking control away from liberal judges on the U.S. Courts of Appeals. Despite its intent, it resulted in more people getting asylum. In our research we ask, what explains this policy gap?

We contend that part of the answer lies in the REAL ID Act’s ambivalent language, a common characteristic of policy concerning undocumented immigrants. The law gave the street-level bureaucrats who decide asylum cases —immigration judges (IJs)— more discretion to deny bogus asylum claims. They no longer had to point to an inconsistency undermining a key aspect of the persecution claim to find the applicant not credible. They could deny based on inconsistencies such as birthdays and wedding dates that have no connection to the asylum claim. At the same time, the law required IJs to consider all the circumstances, potentially reincorporating some of the former rule.

What did IJs do in this situation? They are supposed to follow the precedent in the circuit with jurisdiction over where they sit, but the President controls their hiring and firing, and Congress writes the law and determines their budget. We argue that IJs, behaving in a bounded rationality framework, relied on their professional training as lawyers as a shortcut and were considerably more deferential to the circuit courts who read every opinion they write.

We find just that. As the figure below shows, the adoption of the REAL ID Act’s credibility standard enabled significantly closer ideological control by the courts. Before REAL ID, there was very little relationship between the presumed aggregate preferences of the appellate courts on asylum cases and IJ decision making in that circuit. But after the REAL ID Act is implemented by the circuit through the adoption of its standard in precedent, as the percentage of the circuit that is Democratic increases so too does the likelihood of an IJ granting asylum. The impact went from 3 to 52 percentage points.

Image Description

Figure 1: REAL ID & the Circuit Courts

We saw an increase in influence for Congress and the President, but it was not nearly as large. We also show this is not just a result of the uniqueness of the first Trump administration.

The findings suggest that any attempts to restrict asylum access through immigration courts during Trump’s second term would require precisely written policies. If the administration and a Republican-controlled Congress pursue such restrictions, vague or ambiguous language could backfire. In cases of unclear policy, IJs will turn to federal courts for guidance—potentially leading to interpretations that run counter to the administration’s goals.

You can read the original article in Policy Studies Journal at

Stobb, Maureen, Banks Miller, and Joshua Kennedy. 2023. Mixed messages & bounded rationality: The perverse consequences of real ID for immigration policy. Policy Studies Journal 51: 667–684. https://doi-org.echo.louisville.edu/10.1111/psj.12486

About the Authors

Maureen Stobb is an Associate Professor of Political Science at Georgia Southern University. Her research focuses on the expansion of judicial power relative to the legislature and the executive, particularly in the policy areas of immigration and citizenship. Her research has been published in various outlets including The Journal of Law & Courts, and Justice System Journal.

Banks Miller is an Associate Professor of Political Science at the University of Texas at Dallas. His research focuses on judicial decision making, intellectual property policy, and immigration policy. Recent work has been published in the Journal of Law & Courts and American Politics Research.


Joshua B. Kennedy is an Associate Professor of Political Science at Georgia Southern University. His research of late focuses on political control of the administrative state, and he has also published in the area of unilateral presidential power. His research has appeared in American Politics Research, Research & Politics, and Presidential Studies Quarterly, among other outlets.

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