Feedback loops

Using archetypes as a systemic lens to understand the complexity of sustainable development

By Hossein Hosseini, Enayat A. Moallemi, Sibel Eker, Edoardo Bertone and Katrina Szetey

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1. Hossein Hosseini; 2. Enayat A. Moallemi; 3. Sibel Ekern; 4. Edoardo Bertone; 5. Katrina Szetey (biographies)

What are systems archetypes and how can they be used to bring a deeper understanding of causal drivers, potential dynamic behaviour in the future, and policy resistance when tackling complex problems, including those in sustainable development?

Systems archetypes are recurring generic systems structures found in many kinds of organisations, under many circumstances, and at many levels and scales. They are distinctive combinations of reinforcing and balancing processes theoretically rooted in systems thinking and modelling.

There are eight common archetypes, each with specific underlying causal drivers (eg., feedback loops, delay), expected dynamic behaviour (eg., acceleration, disruption, tipping point), and policy implications (eg., how to respond, where to intervene). Archetypes can help shift an analytical focus from simple behavioural correlations or a limited understanding of interactions between certain goals to a generalised knowledge of recurring patterns, causes, and consequences.

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Seven methods for mapping systems

By Pete Barbrook-Johnson and Alexandra S. Penn

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1. Pete Barbrook-Johnson (biography)
2. Alexandra S. Penn (biography)

What are some effective approaches for developing causal maps of systems in participatory ways? How do different approaches relate to each other and what are the ways in which systems maps can be useful?

Here we focus on seven system mapping methods, described briefly in alphabetical order.

1. Bayesian Belief Networks: a network of variables representing their conditional dependencies (ie., the likelihood of the variable taking different states depending on the states of the variables that influence them). The networks follow a strict acyclic structure (ie., no feedbacks), and nodes tend to be restricted to maximum two incoming arrows. These maps are analysed using the conditional probabilities to compute the potential impact of changes to certain variables, or the influence of certain variables given an observed outcome.

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Fifteen characteristics of complex social systems

By Hamilton Carvalho

Author - Hamilton Carvalho
Hamilton Carvalho (biography)

What is it about complex social systems that keeps reproducing old problems, as well as adding new ones? How can public policy move away from what I call the Mencken Syndrome (in reference to a quotation from American journalist Henry Mencken) – that is, continually proposing clear and simple solutions to complex social problems – that are also wrong!

With this goal in mind, I have compiled a list of fifteen major characteristics of complex social systems based on the system dynamics and complexity sciences literatures, as well as my own research.

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Four patterns of thought for effective group decisions

By George P. Richardson and David F. Andersen

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1. George P. Richardson (biography)
2. David F. Andersen (biography)

What can you do if you are in a group that is trying to deal with problems that are developing over time, where:

  • root causes of the dynamics aren’t clear;
  • different stakeholders have different perceptions;
  • past solutions haven’t worked;
  • solutions must take into account how the system will respond; and,
  • implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?

The fields of systems thinking and system dynamics modelling bring four important patterns of thought to such a group decision and negotiation:

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Scaling up amidst complexity

By Ann Larson

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Ann Larson (biography)

How can new or under-utilized healthcare practices be expanded and institutionalized to achieve audacious and diverse global health outcomes, ranging from eliminating polio to reversing the rise in non-communicable diseases? How can complex adaptive systems with diverse components and actors interacting in multiple ways with each other and the external environment best be dealt with? What makes for an effective scale-up effort?

Four in-depth case studies of scale-up efforts were used to explore if there were different pathways to positively change a complex adaptive system.

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