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Michael Howlett and Stuti Rawat

Behavioral science consists of the systematic analysis of processes underlying human behavior through experimentation and observation, drawing on knowledge, research, and methods from a variety of fields such as economics, psychology, and sociology. Because policymaking involves efforts to modify or alter the behavior of policy-takers and centers on the processes of decision-making in government, it has always been concerned with behavioral psychology. Classic studies of decision-making in the field derived their frameworks and concepts from psychology, and the founder of policy sciences, Harold Lasswell, was himself trained as a behavioral political scientist. Hence, it should not be surprising that the use of behavioral science is a feature of many policy areas, including climate change policy. This is given extra emphasis, however, because climate change policymaking and the rise of climate change as a policy issue coincides with a resurgence in behaviorally inspired policy analysis and design brought about by the development of behavioral economics. Thus efforts to deal with climate change have come into being at a time when behavioral governance has been gaining traction worldwide under the influence of works by, among others, Kahneman and Tversky, Thaler, and Sunstein. Such behavioral governance studies have focused on the psychological and cognitive behavioral processes in individuals and collectives, in order to inform, design, and implement different modes of governing. They have been promoted by policy scholars, including many economists working in the area who prefer its insights to those put forward by classical or neoclassical economics. In the context of climate change policy, behavioral science plays two key roles—through its use of behaviorally premised policy instruments as new modes of public policy being used or proposed to be used, in conjunction with traditional climate change policy tools; and as a way of understanding some of the barriers to compliance and policy design encountered by governments in combating the “super wicked problem” of climate change. Five kinds of behavioral tools have been found to be most commonly used in relation to climate change policy: provision of information, use of social norms, goal setting, default rules, and framing. A large proportion of behavioral tools has been used in the energy sector, because of its importance in the context of climate change action and the fact that energy consumption is easy to monitor, thereby facilitating impact assessment.


Japan is one of the world’s leading marine fishing nations in globalized industrial fisheries, yet the mainstay of the national fishing industry continues to be small-scale fisheries with their own set of cultural and environmental heritage. The cultural tradition of the Japanese fishing communities still preserves the various ways of understanding local weather, which are mainly based on landscape perception and forecasting knowledge. The prediction of weather conditions for a given location and time is part of a long-established historical tradition related to the need for an “easy” understanding of the climatic and maritime environment. It encompasses a variety of practical experiences, skillful reasoning strategies, and cultural values concerning indigenous environmental knowledge, decision-making strategies, and habitual applications of knowledge in everyday life. Japanese traditional forecasting culture interfaces with modern meteorological forecasting technologies to generate a hybrid knowledge, and offers an example of the complex dialogue between global science and local science. Specifically, interpretations and meteorological observations of local weather are modes of everyday engagement with the weather that exhibit a highly nuanced ecological sophistication and continue to offer a critical discourse on the cultural, environmental, and social context of Japanese small-scale fisheries. Indigenous weather understanding is bound up with community-based cultural heritage—religious traditions, meteorological classifications, proverbs, traditional forecasting models, and selective incorporation or rejection of scientific forecasting data—that offers a general overview of the interaction between community know-how, sensory experience, skills, and cultural practices.