3 Section activities
Activity 6A: Modelling your shared understanding for a sustainable future
In this activity the aim is to integrate the various explorations you have engaged in so far (such as cause-and-effect models of emerging social/economic and environmental crises, your personal ecology, quality of life, ecological footprint index, system dynamics models) and create, using a range of communication and modelling approaches, the beginnings of a shared understanding of how various hierarchically-nested systems determine the flows of energy, matter and information in the Earth system. These flows and their feedbacks may be either maximising homeostasis or dragging us down towards collapse.
Developing a shared understanding does not imply achieving a singular mindset. This block has tried to demonstrate that we all have unique characteristics and that there are a multitude of paths to achieve the same objective – Costanza’s Star Trek, Big Government and Ecotopia scenarios are all potentially ‘sustainable’. Thus we need to strive to accept different perspectives and allow the emergence of creative ways to work through problems. However, the latter half of the block has focused on engaging with ‘reality checks’ to see whether any single approach is as sustainable as its associated rhetoric. I therefore hope that you can now see why I think the ‘one size fits all’ mechanistic, reductionist and no-limits economics model to resolving the major challenges we are faced with might not provide all the answers.
I would therefore like to propose that you begin this final activity by considering, together with your fellow course participants, the following question: ‘Is it possible for humanity to define, arrive at and sustain an ecological footprint that is within the Earth’s carrying capacity and simultaneously improves people’s quality of life in a way which is fair?’ There is clearly no ready-made answer, but engaging with this activity will certainly contribute towards an ongoing process of addressing this question.
The platform which we will be using for this activity is a wiki and associated discussion board. You can go tohere and instructions on how to use it can be found within the wiki itself. This wiki was started by the cohort of students on the 2008 T214 presentation and developed further by subsequent students. Now it’s your turn to contribute according to the pointers that I provide (which arise from the learning outcomes for this course).
For the purposes of this activity I actually want you to limit your engagement to a maximum of eleven hours: one hour to initially explore the wiki in order to develop a ‘big picture’ view of it, how it works and where you could intervene (including discussions with co-participants); a couple of hours to research your initial contribution; and another couple of hours to put this into practice. This will be followed by a period of observation and evaluation, and, hopefully, one final iteration to take you up to the eleventh hour.
The limited amount of engagement time means that you have to be realistic in what you want to and can achieve. With such momentous activities, I always have the metaphor of the giant termite hills one observes in the tropics – microscopic living organisms individually adding even smaller pieces of earth to create highly sophisticated and gigantic structures. With hundreds of individual contributions you will be surprised to see how rapidly the process will develop. What you do need to keep in mind is that at the end of your process of engagement things need to be left in a state where others can pick up the process.
But for now please limit your engagement to the indicated timeframe – time management is also a useful skill to pick up. I am providing this warning here because this relatively open-ended activity could easily turn into a temporal black hole.
In the spirit of the ‘star configuration’ outlined in Reading 6.4, I would like you to contribute your own interventions and views on the collective process in a way that does not offend and upset others – something which can be so easily done in an online situation.
You should not be surprised if I now go on to recommend that you structure this process according to the four phases of the action learning process:
- Planning – what is the aim of your intervention? What activities do you think you will need to undertake in order to achieve it? How are you going to measure your progress? What assumptions are you relying on for your plan to be executed smoothly? What are your weaknesses and strengths? Who are you going to collaborate with and how are you going to manage this collaboration?
- Acting – each of the above questions will require certain actions to take place, either in creating the conditions for more information to be revealed about the situation and/or yourself, or in experimenting with certain interventions.
- Observing – this involves the simple task of recording the process and outcomes of the various actions.
- Evaluating – this should allow you to compare the models established in your planning phase with the resulting observations emerging from our actions. Have you got any closer to your aim? Were the actions, measurements, assumptions and collaborations appropriate? Was the original aim you set appropriate? Do you have the time to undertake another iteration in order to progress further?
To kick start your ideas, here are some different types of intervention you may wish to consider. You may want to:
- Engage in the process of analysis (exploring the detail) and synthesis (summarising the detail into the ‘bigger picture’ view) – in other words, illustrate the situation at a range of scales, from the local to the global, from the here-and-now to the long-term, from the personal to the transnational organisational scale. You could, for example, summarise some entries to a higher level, or, expand a particular entry into one or more subcomponents.
- Explore issues in both intuitive/emotive and rational/logical ways: solutions often emerge from a bit of creative thinking and are then validated by logic and facts – so don’t be afraid to introduce some pretty wild ideas while being aware that these will need to be justified eventually. In particular, you may want to include both qualitative and subjective indicators (such as those determining one’s quality of life), and quantitative and objective indicators (such as those characterising the biophysical status of our environment). You could, for example, develop a range of quantitative and qualitative indicators which can be used to assess progress towards the activity’s goal or one or more subcomponents of this goal.
- Promote an integrated verbal, visual and mathematical modelling approach, i.e. I would encourage you to look out for ‘gaps’ within the various wiki entries not only in terms of ‘scale, knowledge gaps and missing links’, but also in terms of model types, hopefully encouraging the full use of your multiple intelligences. NB you are not restricted to the verbal, visual and mathematical models introduced in this block, but I would recommend that you at least practice one diagramming technique.
- Explore the relationship between components, ideas, systems, etc, rather than only concentrating on describing these as isolated and independent entities. This implies clarifying the cause and effect relationship between components, and ultimately identifying positive and negative feedback loops. I acknowledge that this task may be limited by the functionality of the wiki. However, a lot can be achieved by simple restructuring of wiki pages and by the creation of webs of hyperlinks between pages.
- Distinguish between ‘states’ (i.e. temporary stores of energy, matter and information) and ‘rates’ (i.e. the processes which transform these states from one form into another).
- Propose how one could build dynamic models in order to develop a feeling for the behaviour of complex systems over time (NB this is optional in that there are no requirements for prior mathematical/programming knowledge and skills in this course – although it is possible to ‘mentally simulate’ dynamic behaviour by sketching a graph). At its simplest, tables showing change over time for particular ‘states’ could form the backbone of future dynamic modelling.
- Use the action learning framework to take ideas from the Earth wiki, actively experiment in the real world, and feed back to the wiki the results of these actions. We are not passive spectators helplessly glued to our television screens as the world collapses around us. As Mahatma Gandhi stated: ‘Be the change you want to see in the world’ (as quoted in Potts, 2003).
During the initial development of the Earth wiki, some participants struggled with the exercise and showed little evidence of constructive and cooperative working. Part of the problem was most certainly a result of the rather ambitious goals I had provided, the fact that people were starting from scratch, and the limited functionality of the wiki. Yet, I suspect that those individuals that struggled with the activity were those that had difficulties in taking the initiative to try to address some of the problems that emerged during its execution. Notwithstanding all that was said in this course about top-down hierarchical control by those in positions of power not providing the ideal conditions for solving complex problems, some still had the automatic expectation of needing to be told what to do, rather than implementing a ‘learning by doing’ approach to the activity.
I suspect that problems will still be encountered in this iteration. Systems thinking reveals one major insight: that blame cannot be attributed to a singular cause, whether this is an individual or an event. However, this does not mean that we can blame ‘the system’ as a whole for the difficulties either. Each participant within any system has a role to play, and we should take responsibility for the effects of our particular actions, including our inaction. We must certainly not be afraid to act and make mistakes, indeed, this is the only way in which we can learn.
You have now come to the end of this learning experience. Well done for getting this far!
If you have enjoyed any aspect of this course, it is most probably thanks to the constructive feedback from students, tutors and fellow course team members. Any difficulties that you may have had are my responsibility to address, so your feedback on any issues would be very much appreciated.
So, one final request. There is nothing better than receiving detailed feedback on particular aspects of your learning experience straight from participants. Now would be an ideal opportunity for you to summarise your experiences and feed them back to me, Andrea Berardi (a.berardi[at]open.ac.uk).