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Learning is a cognitive and social dynamic through which diverse types of actors involved in policy processes acquire, translate and disseminate new information and knowledge about public problems and solutions. In turn, they maintain, strengthen or revise their policy beliefs and preferences. Despite the conceptual and theoretical developments over the last years, concerns about the measurement of policy learning remain persistent. Based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) approach, this article reports the results of a systematic review of the existing practices for measuring policy learning in the public administration and policy research. In addition to operationalizations, data sources, methods of analysis and levels of analysis, we examine how the reviewed articles deal with the processual nature of policy learning. We show that the existing measurement practices transcend the research streams on policy learning for the most part, which extends the argument developed by Dunlop and Radaelli (2018) that policy learning is an analytical framework of the policy process. Based on these results, we argue for more transparent operationalizations, discuss the strengths and weaknesses of direct and indirect measurement approaches, and call for more creativity in designing measurement methods that recognize the multilevel nature of policy learning.

This study identifies network management as a facilitator of effective policy transfer. We reconstruct the unconventional collaboration between Dutch private-sector experts and national governments of Vietnam and Bangladesh to develop multi-sectoral, long-term strategies (‘delta plans'). We identify the network management strategies used by the Dutch actors and use these to explain how problem perceptions of state and non-state actors were aligned in order to define solution pathways. Based on these cases, we argue that network analysis is a tool for policy transfer studies. This paper further concludes that the ‘soft' nature of the transferred policy (in the form of principles, norms and ideas) increased its transferability, as being ambiguous and abstract left room for interpretation and translation to the local context.

This paper comparatively examines two highly decentralized federations, namely Brazil and the United States (U.S.) The study uses a combination of methods to determine which mechanisms explain the spread of metropolitan regions (Brazil) and the growth of the statewide smoking ban (U.S.) among state governments over the 1990s and 2000s. It uses Weibull distribution and Cox regression to measure the time until events occur and to estimate the influence of a variety of factors on the likelihood of two policies being adopted. I find evidence of electoral-year drive policy diffusion in both countries. In Brazil, a key structural variable associated with internal determinants stimulated metropolitan policy adoptions. In the U.S., structural factors – linked with citizen ideology – enhance the probability of enacting smoke-free laws.