Policy Sciences最新文献

Addressing current socio-economic crises strains public budgets and may threaten fiscal sustainability. Particularly in the welfare sector, where high expenditures meet poor controllability, efficient resource usage is essential to ensure future governments’ capability to act while alleviating current problems. Consequently, this paper asks: why are some countries more efficient in translating social expenditure into welfare outcomes? To answer this question, it is argued that efficiency is a matter of institutional structures and their vertical policy-process integration (VPI): efficiency depends on institutional structures’ capability to (1) ensure policymakers’ responsibility and to (2) provide coordinated feedback, thus pushing for considerate and informed resource use. Analysing the effect of VPI on the relationship between welfare efforts and social outcomes in 21 OECD countries over three decades, the results show that VPI can not only turn ‘less’ into ‘more’, but it also compensates for performance losses in the face of spending cuts.

The United States faces multiple political challenges to achieving the rapid cuts in carbon emissions called for by the Intergovernmental Panel on Climate Change. Among these are the long-standing issue of partisan polarization and the newly emerging problem of climate doom and defeatism. These challenges are not only barriers to agenda-setting and enactment, but can also threaten the durability of policies over time. This study uses a survey experiment from a nationally representative sample (n = 1760) to examine the impact of partisan cues and fatalistic rhetoric on support for the climate provisions of the Inflation Reduction Act. We find that Republicans and Independents exposed to Democratic Party cues expressed less support for the IRA. We also find that Independents respondents exposed to a fatalistic message had reduced support for the IRA. These findings underscore the importance of framing in the post-enactment period and suggest that the IRA may be vulnerable to retrenchment or reversal.

The deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.

Catastrophic wildfire is an increasingly familiar phenomenon on multiple continents. In the United States, concerns about uncontrolled, destructive wildfire have prompted some major insurance carriers to cease writing new policies or to non-renew existing policies. These trends affect not only policyholders, but also, vulnerable communities that already face multiple obstacles to securing property or renters insurance. This study reviews the social and behavioral sciences literatures on wildfire risk in the United States and insurance protection by homeowners. Three categories of research emerge from the review, namely, homeowner as rational actor, wildfire governance and risk management, and wildfire and social equity. There is abundant scholarship on determinants of homeowner decisions to manage wildfire risk by self-protecting or by purchasing insurance, but comparatively little research on the policy implications of shrinking markets for insurance. Policy research on the needs of underinsured and uninsured populations is also relatively undeveloped. Overlaying Lasswell’s social process framework on the three dominant research themes, we find not only divergent research questions, models, and methods, but also, important differences in which stakeholders and stakeholder values are considered. There are opportunities for the different literatures to learn from one another, but also, to sharpen their focus on insurance as a scarce and uncertain resource amid climate change and as property development continues to expand in wildfire-prone areas.

Scholars may be diversely engaged in boundary-crossing work, either staying more confined in academic settings, or reaching out to the policy world. Despite growing theoretical attention, there is little empirical knowledge on the extent to which scholars indeed engage in boundary-crossing activities, and the conditions that foster or jeopardize this. We use original survey data from European political scientists to investigate how frequently they ‘travel’ to the policy world, what patterns of engagement are visible, and how these are determined. The article introduces a typology capturing different boundary-crossing profiles and shows that political scientists are rather frequent travelers across the border between academia and the policy world. Yet, individual characteristics matter. Having (had) a position outside of academia has an especially strong effect on the likelihood of boundary-crossing. Our results also reveal that not every scholar has the same chance to be involved, depending on gender or seniority.

Studies of evidence-based policy have found that research often fails to influence policy-making and identify a number of barriers to research utilization. Less is known about what public administrations do to overcome such barriers. The article draws on a content analysis of 1,159 documents and 13 qualitative interviews to compare how and why evidence standards affect research utilization in two Danish ministries with available evidence, policy analytical capacity, and broad political agreement on key policy goals. The article finds support for the proposition that more exclusive evidence standards in ministries will lead to higher levels of research utilization by showing that average levels of research utilization are higher in the Ministry of Employment than in the Ministry of Children and Education in the period 2016?2021. In active employment policy the adoption an evidence hierarchy and the accumulating evidence in a knowledge bank has interacted with stakeholder support and a continued coordination with the Ministry of Finance to provide economic incentives for policy-makers to adopt evidence-based policies thus stimulating research utilization. Evidence for public education policy, by contrast, has been more contested and the Ministry of Children of Education retains inclusive evidence standards in an attempt to integrate evidencebased and practical knowledge from stakeholders, which has led to lower average levels of utilization in the period.

In 1951, Harold Lasswell defined the ability to clarify value goals as integral to a policy analyst’s job. But graduate education in public policy analysis has paid insufficient attention to the skills needed to investigate and clarify value disputes. In turn, practicing policy analysts don’t have ready access to a set of methods for normative analysis that serves Lasswell’s vision of a contextualized, holistic, and interdisciplinary policy science. I start by describing calls for more emphasis on social equity in policy analysis and explore the complementary relationship of empirical, fact-based analysis and normative, value-driven analysis. I then propose seven competencies that policy analysts should be expected to master. They need to understand how normative issues arise in and adjacent to the classical model of policy analysis. They need to master a vocabulary for normative analysis and understand how humans make moral judgments, recognizing the distinction between moral rationalism and moral intuitionism. To engage in moral rationalism, practitioners need to be able to use the tools of analytic political philosophy. When it comes to moral intuitionism, they need to recognize the emotion-driven foundations of moral judgement and personal values. Finally, policy analysts also need to know where to find the values that are relevant to their analysis. Mastery of these competencies will allow analysts to better serve what Laswell describes as the intelligence needs of policymakers.

Evidence-based policy making (EBPM) has been a key pillar of the better regulation agenda of the European Union. However, the extent to which it has genuinely impacted domestic policy making practices has remained largely unexplored. This study sets out to address this gap by focusing on EBPM adoption in settings with historically weak culture of technocratic rationality. To this end, the article proposes a novel analytical framework combining the concept of Europeanisation with insights from the scholarship on knowledge and evidence utilisation. The framework is then applied to the “least likely” case of Bulgaria and its National Climate and Energy Plan for 2021–2030. The article draws on 26 semi-structured interviews to analyse the use of different types of evidence in the Plan’s formulation. The study finds that genuine adoption of EBPM practices remains relatively low with evidence serving predominantly a perfunctory role. In contrast, instrumental and conceptual uses of evidence remain rare. Still, the findings point at the possibility, albeit limited, for gradual Europeanisation and uptake of evidence-based practices even in highly unfavourable conditions. This can be facilitated by a prolonged exposure to evidence-based practices, targeted EU pressure, the establishment of forums facilitating evidence exchange and the presence of “evidence-friendly” individuals within the civil service.

This article investigates how certainty and timing of evidence introduction impact the uptake of evidence by policy-makers in collective deliberations. Little is known about how experts or researchers should time the introduction of uncertain evidence for policy-makers. With a computational model based on the Hegselmann–Krause opinion dynamics model, we simulate how policy-makers update their opinions in light of new evidence. We illustrate the use of our model with two examples in which timing and certainty matter for policy-making: intelligence analysts scouting potential terrorist activity and food safety inspections of chicken meat. Our computations indicate that evidence should come early to convince policy-makers, regardless of how certain it is. Even if the evidence is quite certain, it will not convince all policy-makers. Next to its substantive contribution, the article also showcases the methodological innovation that agent-based models can bring for a better understanding of the science–policy nexus. The model can be endlessly adapted to generate hypotheses and simulate interactions that cannot be empirically tested.

Policy design approaches currently pay insufficient attention to feedback that occurs during the design process. Addressing this endogenous policy design feedback gap is pressing as policymakers can adopt ‘low-fidelity’ design approaches featuring compressed and iterative feedback-rich design cycles. We argue that within-design feedback can be oriented to the components of policy designs (instruments and objectives) and serve to reinforce or undermine them during the design process. We develop four types of low-fidelity design contingent upon the quality of feedback available to designers and their ability to integrate it into policy design processes: confident iteration and stress testing, advocacy and hacking, tinkering and shots in the dark, or coping. We illustrate the utility of the approach and variation in the types, use, and impacts of within-design feedback and low-fidelity policy design through an examination of the UK’s Universal Credit policy.