ABSTRACTA core literature in the field of public policy seeks to understand whether decentralized collective action institutions will emerge to provide public goods. While some studies examine how they perform relative to public institutions, they fail to account for the possibility of public institutions self‐selecting into the most challenging contexts. If they do, finding that public institutions perform worse could reflect the greater challenge rather than differences in knowledge, skill, or motivation. We examine measures of performance in remediating polluted water discharges from abandoned mines, a task sometimes done by the state government and sometimes by nonprofit watershed associations. Accounting for self‐selection, we find that watershed associations are at least as effective as the state across a variety of outcomes measuring effectiveness and cost‐effectiveness. Moreover, associations better maintain their effectiveness over time. The findings suggest a role for sustained public investment in collective action institutions when providing public goods and services in complex and dynamic policy settings.

ABSTRACTSyringe littering in public places is a public health problem in many big cities nationwide amid the ongoing opioid crisis. Besides needle exchanges and/or safe disposal efforts, cash incentives have come into play as a policy tool to address the issue. In December 2020, the City of Boston launched the Community Syringe Redemption Program (CSRP), which offers a nominal cash “buy back” incentive for used syringes at designated centers. This study examines the impact of Boston's CSRP on reducing syringe litter. It employs a distance band‐based, near‐far identification strategy and uses the difference‐in‐differences (DID) to analyze Boston's 311 service requests related to needle pickup and the number of discarded needles discovered in response to the pickup requests before and after CSRP's implementation. Results show that both 311 requests and publicly discarded syringes have reduced significantly in neighborhoods located within a 0.5‐mile radius of the CSRP redemption center. There are no statistically significant reductions observed in 0.5–1‐mile or 1–1.5‐mile donut bands around the center. In effect, although CSRP could be effective in reducing syringe littering, its impact is geographically bounded and sensitive to the redemption centers' locations. Results from alternative models, robustness tests, and placebo tests are consistent with main findings.

Abstract Devil and Angel Shifts are commonly applied concepts in policy research. Using the two concepts in related but different theoretical frameworks – the Advocacy Coalition Framework (ACF) and the Narrative Policy Framework (NPF) – provokes potential challenges of cross‐theoretical dialogue, the establishment of methodological best practices, and mutual research advancement. How do these frameworks conceptualize Devil and Angel Shifts theoretically and how do they empirically study this concept? To what extent do similarities and differences exist that influence comparability and research progress? This paper starts from the foundational roots of the two concepts that were developed to advance the understanding of collective action and inter‐coalition conflict. It then provides a systematic literature review of existing applications that sheds light on conceptualization, measurement, hypotheses, and findings. Drawing from these insights and complementing them with psychological research, it makes an integrated argument that ACF and NPF are developing the same sub‐theory of the Devil and Angel Shifts and offers recommendations for improvements.

Abstract Punctuated equilibrium theory (PET) suggests that policy processes experience periods of stability interrupted by dramatic change. Most previous studies have used kurtosis, distribution tests, or change categorization to assess punctuation, but these methods provide limited information. We propose a novel approach that statistically determines the cutoff between small and large changes, assuming small changes follow a normal distribution and large changes follow an exponential distribution. This approach also estimates other parameters describing these distributions. We then compare budgetary decision‐making in bureaucratized and non‐bureaucratized school districts in New York and Texas. Both types in New York conform to PET, but bureaucratized districts exhibit a higher percentage of punctuations. In Texas, non‐bureaucratized districts follow PET, whereas PET is rejected in bureaucratized districts. The wealth of information obtained through the application of our new method enables us to suggest that bureaucratization likely impedes information flows and that poor information flows can manifest in more ways than previously believed, including underreaction followed by overreaction, as well as consistent overreaction.

Abstract This article contributes to the evolving discourse on the role of technology in public policy formulation by proposing an integration of algorithmic meta‐capital (AMC) into the Narrative Policy Framework (NPF). Recognizing the profound impact of algorithms on shaping public narratives and policy discussions, this research attempts to unravel the complex ways in which the symbolic social power embedded in modern algorithmic systems influences the initiation and reception of public policies. Through examinations at the micro (individual), meso (group), and macro (cultural and institutional) levels, the study reveals how AMC impacts the dissemination and resonance of policy narratives, alters the dynamics within advocacy coalitions and interest groups, and contributes to the stability and evolution of algorithmic institutionalization. In presenting our arguments, we also provide real cases and ideas aimed at future empirical investigations.

Abstract How did a pension movement construct its narrative around pension age, shaping its structure and content to influence policy change in an electoral autocracy? This article delves into the campaign of the Turkish pension movement, a single‐issue movement self‐identifying as “people stuck in the pension age barrier” [emeklilikte yaşa takılanlar (EYT) in Turkish], to analyze policy narratives in an electoral autocratic context. Employing the Narrative Policy Framework (NPF), this exploratory study dissects the Turkish pension movement's policy narrative through an examination of nearly 2100 tweets, selected from a total of 64,980 tweets posted between 2020 and 2023. It shows how, in 280 characters, the movement challenged the long‐established pension age. The article reveals that the EYT movement positions itself as the hero, using a victim‐centered injustice narrative with the villain often left vague, likely to preserve dialogue with the government. The movement emphasizes the diffused benefits of the moral of the story, portraying its constituency as larger than it is and its base of allies as wide as possible, reflecting the movement's strategic engagement with electoral politics. This study enhances the NPF literature by demonstrating how non‐governmental actors construct influential narratives in electoral autocracies.

Abstract The growing popularity of basic income has led to extensive trials of the policy in numerous settings across the world. However, analysis of the politics of basic income, and in particular the political dynamics preceding and resulting from trial programs, lags. In response, we propose a research agenda that uses political scale to investigate where basic income trials emerge, how individual trials' design and implementation parameters vary, and how those trials influence subsequent policy development. By focusing on the previously omitted variable of political scale, our approach addresses a number of key challenges in evaluating basic income trials. First, we provide a means of identifying negative and partial cases to remedy the small‐N problem at the national and regional scales. Second, focusing on a given scale helps to identify specific incumbent programs and policy possibilities influenced by basic income trials. Third, our framework draws attention to the importance of distinct, scale‐based political dynamics in both securing basic income trials and converting trial programs into future policy changes.

Abstract Policy diffusion based on learning mechanisms has fascinated political science and public administration scholars for a long time. A robust and growing body of studies have identified the existence and importance of learning mechanisms in policy diffusion. However, there are still some gaps that need to be further improved. First, scholars identify the learning mechanism mainly based on indirect evidence, such as geographical proximity and successful innovation policies adopted by other jurisdictions, which lacking direct and systematic evidence. Second, little is known about how the hierarchical power structure affects the leap from learning behavior to policy adoption. This study provides direct evidence for the promoting effect of intergovernmental learning on policy diffusion by analyzing case of Chinese local financial subsidy policies for new energy vehicles. The empirical results reveal that policy learning in the form of site visits among local governments significantly promotes the policy diffusion, but superior government policy strategy attenuates the influence of interlocal learning on policy diffusion. Also, the initiators and themes of policy learning affect the learning–diffusion linkage, portraying the conditional effects and nuanced dynamics of interlocal policy learning in eliciting policy diffusion.

Abstract A growing body of public policy literature examines how welfare retrenchment reform produces attitudinal and behavioral feedback effects. This study adds to the literature on welfare reforms by exploring how different policy designs, combined with individual proximity to reform, produce heterogeneous feedback effects. Bridging the theories of policy feedback and policy design, we theorize how different policy designs shape individuals' self‐interest or sociotropic considerations when they form opinions on welfare reform. The feedback effects of these different policy designs are channeled by individual proximity to the reform, resulting in heterogeneous responses to proposed policy change. Seizing an opportune time window when the Chinese government undertook a public consultation program in 2020 regarding the proposed reform reallocating financial resources in individuals' medical savings accounts, we conducted a survey experiment to examine if two different policy designs led to varying feedback effects. We find that the moderate de facto retrenchment reform indeed triggered public opposition. Unlike previous research that emphasizes partisanship as a major source of heterogeneous feedback effects, our study reveals different sources of heterogeneity—public opposition to the proposed reform varies by the specific policy designs and individuals' past experiences with the existing health insurance policy.