Mapping wisdom as a complex adaptive system

This is the second of two papers concerning wisdom as an ecosystem appearing in sequential editions of Management & Marketing journal. The notion of wisdom as an ecosystem, or "the wisdom ecology", builds on work by Hays (2007) who first identified wisdom as an organisational construct and proposed a dynamic model of it. The centrepiece of this and its former companion paper is a relationship map of the Wisdom Ecosystem (the Causal Loop Diagram at Figure 1). The first paper, "The Ecology of Wisdom", introduced readers to the topics of wisdom and complex adaptive systems, and presented a dynamic model of the Wisdom Ecosystem. This second paper discusses systems dynamics modelling (mapping systems) and covers the Wisdom Ecosystem model in detail. It describes the four domains, or subsystems, of the Wisdom Ecosystem, Dialogue, Communal Mind, Collective Intelligence, and Wisdom, and walks readers through the model, exploring each of its 25 elements in turn. It examines the relationships amongst system elements and illuminates important aspects of systems function, providing a rare tutorial on developing and using Causal Loop Diagrams.Causal Loop Diagramming, Complexity, Dialogue, Organisational Learning, Systems Dynamics, Wisdom.

Governing science as a complex adaptive system

Research policy is a complex matter. Copying best practices in research policy, as identified by benchmarking studies, is popular amongst policy makers but fails because of ‘knowledge asymmetries’. Research fields exhibit distinct knowledge dynamics that respond differently to governance interventions. Extending the idea of search regimes, this paper aims at providing a policy model for different knowledge dynamics by elaborating the notion of knowledge production as a complex adaptive system. Complex regimes emerge from three interacting sources of variance. In our conceptualisation, researchers are the nodes that carry the science system. Research can be considered as geographically situated practices with site specific skills, equipments and tools. The emergent science level refers to the formal communication activities of the knowledge published in journals and books, and announced in conferences. The contextual dynamics refer to the ways in which knowledge production provides resources for social and economic development. This conceptualization allows us to disaggregate knowledge dynamics both in horizontal (field related) and vertical (level related) dimensions by articulating the three different dynamics and their path dependencies (in research, science and society) in co-evolution with each other to produce distinct search regimes in each field. The implication for research governance is that generic measures can sometimes be helpful but there is clear need for disaggregated measures targeting field specific search regimes. Governing knowledge production through disaggregated measures means targeting in a distinct way not only different fields, but also, and more importantly, the interactions between local research practices, emergent scientific landscapes, and the field’s relationship to its societal context. If all three “levels” are aligned, there is a stable regime.search regime, research and innovation governance, complex adaptive system

Using complex adaptive systems to investigate Aboriginal-tourism relationships in Purnululu National Park: exploring the role of capital

Resource management systems such as national parks are complex and dynamic with strong interdependencies between their human and ecological components. Their management has become more difficult as scale, impacts and consequences have increased and local communities have become increasingly involved. Increasing pressures from tourism have added to this management complexity. Complex adaptive systems thinking, and especially the metaphor of the adaptive cycle (Holling 2001), can potentially enhance our understanding of these resource systems, including national parks. The concept of the adaptive cycle can help understand changes over time in a system such as a national park

Application of Method of System Potential in Analysis of Economic System Evolution (english version).

The mathematical formulation of new System Method based on ideas of “system potential” and “conditions of its realization” is given. Cyclical dynamics of “efficiency of work” of a complex adaptive system follows from this Method. These cycles have the properties like to the properties of typical business cycles. It is proposed to identify these evolution cycles of complex adaptive systems as applied to economic system with business cycles.business cycle, catastrophe jump, economic potential, complex adaptive system

On Selfish Memes: culture as complex adaptive system

We present the formal definition of meme in the sense of the equivalence between memetics and the theory of cultural evolution. From the formal definition we find that culture can be seen analytically and persuade that memetic gives important role in the exploration of sociological theory, especially in the cultural studies. We show that we are not allowed to assume meme as smallest information unit in cultural evolution in general, but it is the smallest information we use on explaining cultural evolution. We construct a computational model and do simulation in advance presenting the selfish meme powerlaw distributed. The simulation result shows that the contagion of meme as well as cultural evolution is a complex adaptive system. Memetics is the system and art of importing genetics to social sciences

Rawlsian Individuals: Justice, Experiments, and Complexity

John Rawls’s A Theory of Justice is examined from the perspective of experimental methods in economics and complex adaptive systems simulations. This paper first discusses the justice principle selection process in Rawls’s representation of it as a hypothetical experiment. This hypothetical experiment fails to satisfy reasonable experimental controls, particularly as reflects the conception of the individual it employs. The second section of the paper discusses the differences between Rawls’s two conceptions of rational persons associated with his distinction between thin and full theories of the good. The third section uses his fuller conception of rational persons, life plans, and psychological laws in the third part of the book to offer an alternative view of the selection process understood as a complex adaptive system. The fourth section turns to a topic raised by this complex system approach, the status of normative reasoning in political-economic systems. The fifth section summarizes

Emergent Form from Structural Optimisation of the Voronoi Polyhedra Structure

In the course of the exploration of computational means in the architectural design process, in order to investigate more complex, adaptive geometries, the Voronoi diagram has recently gained some attention, being a three-dimensional space-filling structure which is modular but not repetitive. The project looks at the Voronoi diagram as a load-bearing structure, and whether it can be useful for structural optimisation. Hereby the edges of the Voronoi polyhedra are regarded as structural members of a statical system, which then is assessed by structural analysis software. Results seem to indicate that the Voronoi approach produces a very specific structural as well as spatial type of order. Through the dislocation of the Voronoi cells, the statical structure becomes more complex through emergent topology changes, and the initially simple spatial system becomes much more complex through emerging adjacencies and interconnections between spaces. The characteristics of the emerging form, however, lie rather in the complexity how shifted spaces and parts are fitted together, than in a radical overall emergent geometry. Spatially as well as a structurally, the form moves from a simple modular repetitive system towards a more complex adaptive one, with interconnected parts which cannot stand alone but rather form an organic whole