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On the design of national wellbeing measures and policies

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Abstract

The pursuit of happiness is perhaps as old as culture itself. In the modern world, it is clear that the hopes and aspirations of humanity extend well beyond GDP and other economic measures of social progress and wellbeing. In this chapter, we examine the modern social progress movement and consider what is needed to facilitate its further evolution. Specifically, we examine the emerging values that are influencing the way governments in different countries are thinking about wellbeing measurement and policy. While many governments now agree that it is important to consult with citizens in the design of wellbeing measures and policies, there is no consensus on how to best do so. We highlight the value of citizen consultations and consider how best to optimize codesigning by experts, citizens and politicians by using applied systems science tools that facilitate collective intelligence and collective action. We describe a recent application of our applied system science methodology to the design of a notional national wellbeing index for Ireland. The chapter closes by highlighting the importance of adopting a wider social science toolkit to the challenge of facilitating social progress.

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... One applied systems science approach-Collective Intelligence (CI)-has been widely used to facilitate groupbased problem solving, specifically, to both understand a complex issue and map options and actions relevant to the problem [28] (see [29][30][31][32] for recent social science applications; and see [33][34][35] for further details on methodology and application). The benefits of applying this approach to understand the complexity of FMS interventions has recently been outlined in an exploratory study [36]. ...
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Background To have population-level impact, physical activity (PA) interventions must be effectively implemented and sustained under real-world conditions. Adequate Fundamental Movement Skills (FMS) is integral to children being able to actively participate in play, games, and sports. Yet, few FMS interventions have been implemented at scale, nor sustained in routine practice, and thus it is important to understand the influences on sustained implementation. The study’s aim was to use Collective Intelligence (CI)—an applied systems science approach—with stakeholder groups to understand barriers to the implementation of FMS interventions, interdependencies between these barriers, and options to overcome the system of barriers identified. Methods Three CI sessions were conducted with three separate groups of experienced FMS intervention researchers/practitioners ( N = 22) in the United Kingdom and Ireland. Participants generated and ranked barriers they perceive most critical in implementing FMS interventions. Each group developed a structural model describing how highly ranked barriers are interrelated in a system. Participants then conducted action mapping to solve the problem based on the logical relations between barriers reflected in the model. Results The top ranked barriers (of 76) are those related to policy, physical education curriculum, and stakeholders’ knowledge and appreciation. As reflected in the structural model, these barriers have influences over stakeholders’ efficacy in delivering and evaluating interventions. According to this logical structure, 38 solutions were created as a roadmap to inform policy, practice, and research. Collectively, solutions suggest that efforts in implementation and sustainability need to be coordinated (i.e., building interrelationship with multiple stakeholders), and a policy or local infrastructure that supports these efforts is needed. Conclusions The current study is the first to describe the complexity of barriers to implementing and sustaining FMS interventions and provide a roadmap of actions that help navigate through the complexity. By directing attention to the ecological context of FMS intervention research and participation, the study provides researchers, policy makers, and practitioners with a framework of critical components and players that need to be considered when designing and operationalising future projects in more systemic and relational terms.
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In the absence of meaningful strategies to promote critical thinking, systems thinking, and social intelligence, it has been argued that algorithm-driven web technology will not only serve to damage human creativity, technology may ultimately reduce our collective intelligence. At the same time, the history of group decision-making in education, business, and public administration highlights that working groups often fail to solve complex problems because their method of collaborative problem solving is ineffective. Decades of research in social psychology and the learning sciences highlight the many limitations of group problem solving, including the tendency to focus on a limited set of ideas, select ideas based on biased ‘rules of thumb’, and failure to build trust, consensus and collective vision. A fundamental skill for resolving complex social and scientific problems is the ability to collectively visualise the structure of a shared problem, and use this knowledge to design solutions and strategies for collective action. In this chapter, we describe an approach to knowledge cartography that seeks to overcome three independent human limitations which impede our ability to resolve complex problems: poor critical thinking skills, no clear methodology to facilitate group coherence, consensus design and collective action, and limited computational capacities. Building on Warfield’s vision for applied systems sciences, we outline a new systems science tool which currently combines two thought structuring methodologies: Argument Mapping for critical thinking, and Interactive Management for system design. We further describe how teaching and learning a form of knowledge cartography grounded in applied systems science requires a vision around the development of Tools, Talents, and Teams. We also provide examples of how our approach to knowledge cartography and applied systems science has been used in business and educational settings.