A Simulation Model to explore Community Dynamics based on Inner Peace, Perceived Kindness, Actions of Kindness, Resources and Quality of Space
Jeffery Jonathan Joshua (ישוע) Davis & Florian Schübeler
The Embassy of Peace, Whitianga, New Zealand
joshua_888@yahoo.com, florian@theembassyofpeace.com
In previous papers we have explored the dynamics of small communities' spiritual growth via the development and use of system dynamics simulation models. So far we have produced simulation models for two (2) sub-systems of a larger model, which describes some of the complexities associated in understanding the dynamics of an economy based on actions of kindness. In this paper we model the integration of these two (2) sub-systems via links which connect the soft variables Actions of Kindness, Quality of Space and Perceived Kindness (Schübeler et al., 2018), (Davis & Schübeler, 2019),(Davis et al., 2019). We then run a series of simulations to explore different scenarios in a horizon of three (3) years with an initial community size of ten (10) people. Finally, we create graphs to compare all the simulations with respect to number of people, perceived kindness and quality of space. Once again we derive from our simulation and scenario analysis that soft variables like Inner Peace and Quality of Space for example, play a fundamental part in community health, development and growth, even more so than physical or hard variables, like resources for example.
INTRODUCTION
The purpose of this work is to create a robust system dynamics simulation model which, in our estimation and from our experience, represents reasonably well the main considerations of living in small communities and what factors are most impactful on both the quality of life or space and the longevity of the community, in terms of stability, metastability and growth for their members. Through this work our aim is to provide practical tools which can be used by any group of people living or partaking in a learning community or organization, which is interested in exploring consciousness evolution and social harmony dynamics, with a solid foundation grounded in an economy based on actions of kindness. We conjecture that this seminal work will support those communities who are genuinely seeking ways of making this world a better place to live in, in order to develop smoothly, dynamically, systematically and systemically, step-by-step towards the fulfilment of their vision.
To this end, we started with an exploration of the dynamics of an economy based on actions of kindness in which we developed a system dynamics model (Schübeler et al., 2018). Due to the size and complexity of this model, we decided to first explore two (2) sub-systems (the "left" and "right" side) (Davis & Schübeler, 2019), (Davis et al., 2019). We can now create a combined model (left & right), thus enabling us to simulate the effect of the synthesis and hence explore the big picture.
The first sub-system ("left" side of the larger model) (Davis & Schübeler, 2019) explored the dynamics of the community based on number of people, resources and quality of space and how these elements impact on the growth or decline of the community. We concluded that in order to evolve harmoniously, for a small pilot community such as the one described in (Davis & Schübeler, 2019), it is more relevant to pay attention to the quality of space, which is a more significant factor to manage, than the availability and efficient use of resources. The quality of space can be maintained via different strategies. In previous studies it has been proposed that by meditating and focusing on and embodying Spiritual Values like Compassion and Love, for example, human beings are able to harness inner peace and psychophysiological coherence, thereby creating resilience at an individual level and within the community (Zhuang et al., 2016), (Schübeler et al., 2018), (Davis et al., 2019a), (Childre & Cryer, 2008), (McCraty, 2005). Once established, this solid foundation enables the members of such a community to direct and commit their energy towards the fulfilment of their shared vision in an atmosphere where actions of kindness are the norm.
The second sub-system ("right" side of the larger model) explored the relationship between inner peace and actions of kindness and their influence on perceived kindness (Davis et al., 2019). The main conclusion we derived from the simulations of this sub-system is that Inner Peace, the main variable of the model, is also the most significant variable in achieving a sustainable and healthy growth.
The integrated simulation model features four (4) levels or state variables, namely: Resource, People, QOS (quality of space) and Perceived Kindness with associated carrying capacities. Altogether we simulated six (6) different scenarios, all starting with a set of initial conditions as follows: the variable People with a value of ten (10), Quality of Space with a value of 0.5 and Perceived Kindness with a value of fifty (50). By changing the initial settings of various parameters we can alter the dynamics between all the levels and rates influencing the behaviour of the model. In the first scenario we set Resource, Resource Efficiency Factor, Synergy Quality Rate and Inner Peace at relatively small values. Then we studied the sensitivity of the system by specifying different conditions for different scenarios.
Scenario 1 was designed as a baseline to which most of the other scenarios were compared. This baseline was conceived to lead to relatively low values for Perceived Kindness and Quality of Space, together with conservative values for the evolution of the community in terms of People. It is important to note that the values of Inner Peace were set to relatively low values.
In Scenario 2 we observe the effect of increasing the initial value of Resource, Resource Efficiency Factor and Synergy Quality Rate to relatively high values compared to Scenario 1. This allowed us to test the effect of an increment and better management of resources with a greater synergy in the community.
In Scenario 3 we tested the effect of a significant increment in the initial value of Inner Peace when compared to Scenario 1.
In Scenario 4 we raised the values of Inner Peace slightly while raising the value of Synergy Quality Rate significantly when compared to Scenario 1. This allowed us to quantify the effect of having a greater community synergy with a relatively high standard of inner peace.
In Scenario 5 we raised the initial value of Resource and Resource Efficiency Factor to relatively high values, while slightly raising Inner Peace, all with respect to Scenario 1. This allowed us to understand the effect of adding resources to the community when inner peace is set at a relatively high standard.
In Scenario 6 we tested the combined effects of Scenario 4 and 5 when compared to Scenario 1. This constitutes a very favourable community setting for both spiritual and physical growth and community wellbeing.
Finally, we conducted a set of comparative analyses as follows: (1) Comparative Analysis of People across scenarios, (2) Comparative Analysis of Perceived Kindness across scenarios and (3) Comparative Analysis for Quality of Space across scenarios.
As in the previous studies mentioned above, we concluded that individual inner peace and the community quality of space are the main elements that modulate sustainable growth and community wellbeing. Community synergy and quality of space remain two (2) of the main contributing elements, particularly with regard to how kindness is perceived, although the amount of resources and their management also play a role.
DESCRIPTION OF THE MODEL
Based on our previous work that described community dynamics in terms of: (a) people, resources and quality of community space, in one (1) of the models (Davis & Schübeler, 2019) and (b) perceived kindness, actions of kindness and inner peace in another model (Davis et al., 2019), here we present an integrated model based on the previous two (2). In Figure 1 we present a system dynamics diagram that allows for the reader to get the foundational understanding of this integrated model. There are several positive (
) and negative (
) feedback loops present in the description of the system that presumably capture the most significant elements that may describe the different regimes and behaviours that the system may display. Some of these behaviours are growth, oscillations or decay. The causal relationships describing the dynamics that comprise all the elements and variables of the system are marked either with a plus (
) or minus (
) sign. These signs describe the type of causal relationships which basically means in which direction they influence one another. For example, Inner Peace affects Actions of Kindness in the same direction (), meaning that as Inner Peace grows or decays, so will Actions of Kindness grow or decay respectively. Similarly, Inner Peace affects Kindness Dissipation in the opposite direction (), which means that when Inner Peace grows, Kindness Dissipation will decay and if Inner Peace decays, Kindness Dissipation will grow. For a deeper understanding of system dynamics we direct the reader to the work of (Roberts et al., 1996), (Senge, 1990), (Meadows, 2008).
The integration of the two (2) previously developed models resulted in one (1) new feedback loop that we introduce here to the reader. In Figure 1 we can appreciate how People affects Actions of Kindness in the same direction, while Actions of Kindness in turn affects Perceived Kindness also in the same direction, beginning to form a reinforcing loop. Further, Perceived Kindness is a part of this reinforcing loop, which has an effect on Quality of Space, which in turn affects Net Quality Factor. The effect of Net Quality Factor on People is also part of this positive or reinforcing feedback loop. The reader must note that we started following the loop from People via Actions of Kindness, Perceived Kindness, Quality of Space and Net Quality Factor and closed it arriving back to People. For a more detailed description of this system dynamics model we refer the reader to our previous work (Schübeler et al., 2018), (Davis & Schübeler, 2019), (Davis et al., 2019).
This system dynamics model is the foundation for our simulation model and we used Insight Maker, a free, open source, web-browser based, modelling and simulation tool (Insight Maker, 2017) in order to create a simulation model of this system. The 4th Order Runge-Kutte Method was chosen for our simulations with a dt=0.02 to guarantee for accuracy in the solution of the equations (Roberts et al., 1996).
Our simulation model features four (4) levels, namely Resource, People, QOS and Perceived Kindness, marked as blue rectangles in Figure 2. These levels all have associated to them an inflow and an outflow, which are rates by which each particular level changes. The level grows per unit of time t (specified in months in our model) by the influence of the inflow and similarly, it diminishes because of the outflow. The three (3) levels, People, Resource and Perceived Kindness, are modelled via the logistic function and therefore are limited by a particular carrying capacity for each as follows: Carrying Capacity, R Carrying Capacity and Carrying Capacity Threshold for AoK, respectively (von Bertalanffy, 2013). The flow AoK (actions of kindness) is mainly influenced by the Net AoK Growth Factor variable, which is derived from Inner Peace and People AoK Factor. While Inner Peace is described by an oscillatory process, People AoK Factor is a transfer function (see Figure 3a) that is modulated by the level People. The rate QIn is, amongst other variables, influenced by Quality Kindness Rate, which is described by another transfer function (see Figure 3b) and is modulated by the level Perceived Kindness.
Since this simulation model is an integrated model from previous work, we have described those variables and relationships that have been added to this integrated model. For a complete description of all the variables and relationships of this model we refer the reader to (Schübeler et al., 2018), (Davis & Schübeler, 2019), (Davis et al., 2019). However, we must emphasize that in this model we include Inner Peace as an exogenous variable in the form of a function of time or time series, which affects other variables in the system, while the rest of the variables exercise no feedback effect on the variable Inner Peace.
Finally, it is important to note that in the simulation model diagram in Figure 2, four (4) of the variables are displayed in yellow, namely Resource Efficiency Factor, Synergy Quality Rate, Inner Peace and Inner Peace Projection. It is mainly by changing the initial settings of the first three (3) of these variables that the system behaviour is significantly changed as shown in the different scenarios modelled. Inner Peace Projection is a variable that is a fixed constant for all our simulations, however we have kept it in the model since it plays a role in modelling more complex Inner Peace scenarios when required. In the following section we will introduce the reader to several scenarios and present an analysis for each of them.
SIMULATION SCENARIOS AND RESULTS
For our analysis we have simulated six (6) different scenarios, which illustrate various behaviours of the levels and other variables analysed depending on the initial conditions. All our scenarios have been simulated for a time horizon of 36 months. We look at the four (4) levels of the system and the variable Inner Peace and provide some possible explanations for the dynamics we observe in the simulation results. It is important to note that the level Perceived Kindness is treated as one (1) of the main indicators for determining a successful scenario, since our main interest is in building communities that are of high quality in regards to peace, harmony and wellbeing and provide an environment conducive to the spiritual growth of its members.
As can be seen in Table I for all our simulations, the levels People, QOS and Perceived Kindness (PK) are set to the same initial values of 10, 0.5 and 50 respectively. The initial value for the level Resource varies from scenario to scenario as do the initial values of the variables Inner Peace (IP), Resource Efficiency Factor (REF) and Synergy Quality Rate (SQR). IPA is an amplitude factor that defines IP oscillations and is governed by the equation: IP(t) = (1+1*cos(0.25*2*3.14*t)/2)*IPA+0.1 where t is in the unit of months. For a detailed description of these levels and variables we refer the reader to (Davis & Schübeler, 2019), (Davis et al., 2019).
In Scenario 1, a baseline scenario, we start the simulation with relatively low amounts of resources, inner peace and synergy between people. While these initial conditions lead to a stable community in numbers of people, the members experience low quality of space and a continuous oscillatory tendency of diminishing perceived kindness. We observe QOS oscillating at first and eventually stabilizing at a relatively low value of ~ 0.68. Resource increases slightly but remains low and People stabilises at ~ 20. Inner Peace oscillates as expected and takes rather small values between 0.45 and 1.15. Generally speaking, here we observe that the community stabilise at ~ 20 people, even in the face of a relatively low amount of resources, as well as a relatively low quality of space. The small levels of inner peace that each individual embodies is a direct cause for the decrease of the kindness perceived within the community. Such a community may be able to survive in order to meet its physical requirements, however, falling short to provide its members with an ideal environment favourable for spiritual growth.
In Scenario 2 the initial values for Resource, REF and SQR are increased significantly. We can observe that PK oscillates and grows to high values and reaches a metastable state with relatively small oscillations. This indicates that with more resources and a more efficient management of them, together with a greater community synergy, the system will be able to achieve significantly higher values in the collective perception of kindness, even with the same relatively low level of inner peace as in Scenario 1. We also observe that the quality of space improves significantly causing the number of people to increase almost to carrying capacity.
We can conjecture that a community living in such conditions, with a good quality of space would provide an environment where people could, over time, work on their personal mastery and improve on inner peace. This would then feed back into the system and presumably allow perceived kindness to further increase. However, this remains an exploration for future research with new and further integrated simulation models.
In the simulation for Scenario 3 we set Resource, REF and SQR to the same values as in Scenario 1, yet this time combined with very high values for IP. Here PK grows very quickly towards carrying capacity (100) and oscillates slightly around values of 95. The other variables behave in a similar fashion to Scenario 1. From this observation, we can presume that even though Resource and QOS have an effect on PK, IP appears to be the predominant variable modulating the behaviour of PK. Here it is important to note that even though the community members manifest high values of inner peace and are able to perceive relatively high values of kindness, the community still remains with twenty (20) members. This can be interpreted as a consequence of the low amount of resources available and the inefficient management of them, together with a low level of the quality of space in the community, which appears to be the most determinant factor. This result coincides with the findings in our previous work (Davis & Schübeler, 2019) and becomes evident when we look at Scenario 4.
For Scenario 4, we increase the value of SQR significantly and reduce the value of IP, while Resource and REF remain the same as in the previous scenario. As expected we observe that QOS increases to a much higher value (~ 1.16), which allows the community to grow in numbers near its carrying capacity, even though resource availability and efficiency of their use remains low. The fact that the number of community members grows to near carrying capacity is something we would expect and is also observed in (Davis & Schübeler, 2019). Interestingly, however, we still observe high values for PK even with much smaller values of IP than in Scenario 3.
This scenario illustrates that a high quality of space combined with low levels of resources and relatively high levels of inner peace allows for high levels of perceived kindness.
In Scenario 5 we set Resource and REF to higher values and SQR to a lower value than in Scenario 4, while IP remains the same. In Figure 8 we observe similar values for PK though marginally smaller than in Scenario 4.
In Scenario 5 the greater amount of resources appears to compensate for less quality of space, in terms of the level of perceived kindness that is reached, however, this amount of resources fails to support the growth of the community to the same numbers as in Scenario 4. The exact effect of IP, QOS and Resource on PK requires a deeper sensitivity analysis and is outside the scope of this paper.
We can deduce that both resources and quality of space can improve perceived kindness, however, when combined with low levels of inner peace, people will more likely become dependent on resources and other factors, such as excessive emotional feedback for example, in order to raise perceived kindness. On the other hand, the practice of personal mastery leading to inner peace lessens the dependence on external factors, without lessening and sometimes even enhancing the perception of kindness. Such an approach to inner peace will be less energy demanding and require fewer actions of kindness to keep the community thriving.
In our final scenario, Scenario 6, we have raised the value of SQR and can observe the effect that an increase in this variable has on both QOS and People, where the number of people approaches carrying capacity. When comparing this scenario with Scenario 2, we observe very similar results for both scenarios with overall slightly higher values for Scenario 6, however, in Scenario 2 we can clearly observe that it takes much longer to reach those values. This means that the system spends more time in less desirable conditions.
The fact that the system reaches its carrying capacity for the level People indicates a good nurturing environment that supports growth in numbers. These conditions combined with relatively high levels of inner peace provide an ideal environment for people to perceive kindness and work on personal mastery and spiritual growth. This scenario simulates a community that is close to the ideal that we have outlined in detail in (Davis & Schübeler, 2019), (Davis et al., 2019) where room for improvement in the area of inner peace always remains.
At this stage, we can appreciate some important differences between scenarios. These differences are better appreciated in Figures 10 to 12 where we display comparative graphs for the levels People, PK and QOS. It is important to note that Simulation Results 23 to 28 correspond to Scenario 1 to 6 respectively, for all graphs presented in these figures.
It is important to note that Scenario 6 shows a population growth pattern that reaches a maximum due to an abundant availability of resources and a strong synergy in the community that can be observed in the values that Resource and QOS display. Scenario 2 and 4 display a similar population growth pattern even though in Scenario 4 there are significantly less resources available and in Scenario 2 the level of inner peace is lower. In contrast, Scenario 1, 3 and 5 show a population growth pattern that is significantly lower, reaching a certain equilibrium with very mild oscillations due to a lack of resources and synergy in the community, which can be observed in the values that QOS displays and additionally with a lack of resources for Scenario 1 and 3. The reader must note that Scenario 1, 3 and 5 display low, very high and high levels of inner peace respectively.
In the comparison displayed in Figure 11 we can identify the different behaviours of PK for the different scenarios where in Scenario 1 we observe the lowest values for PK since all the relevant variables are set initially to small values. In Scenario 2 we observe a significantly oscillatory delayed growth pattern where Resource and SQR have been set to high values while IP is set to small ones. Finally, in the rest of the scenarios PK behaves quite similarly, however it is clear that PK reaches the highest values in Scenario 3 due to a high level of inner peace even in the face of a lack of resources and synergy in the community.
In Figure 12 we can identify the various behaviours of QOS for the different scenarios where once again in Scenario 1 we observe the lowest values for QOS since all the relevant variables are set initially to small values. Scenario 3 and 5 present low values for QOS due to the fact that SQR has been set to a small initial value. From this comparison we can infer that SQR significantly affects the behaviour of QOS as prescribed in our design of the model (Davis & Schübeler, 2019).
CONCLUSION AND FUTURE PERSPECTIVE
This paper has explored the integration of the two parts ("left" and "right" side) of a system dynamics model used to simulate a community based on actions of kindness (Schübeler et al., 2018), (Davis & Schübeler, 2019), (Davis et al., 2019). From analysing the graphs derived from the simulation model we draw the following conclusions:
1. The most crucial elements within the whole system are Inner Peace and QOS in order to support the growth of the community accompanied by high levels of Perceived Kindness.
2. When the level Inner Peace shows low values, then the Synergy Quality Rate, the level Resource and the level QOS are the main elements left in the system to support and maintain the level Perceived Kindness at relatively good or high values.
3. When Synergy Quality Rate, Quality of Space and Inner Peace show higher values, then the level Perceived Kindness is maintained at also high or very high values regardless of the amount of resources available to the community.
4. It is interesting to note that in a community of monks, for example, where most of them spend long periods of time meditating in retreat huts or caves, which could imply a low level of social synergy for a newcomer to this community, the quality of space and the perceived kindness could be interpreted as low which could cause newcomers to leave the community even though the monks embody very high levels of inner peace. This in turn would lead the community to an equilibrium in terms of number of people who share the same monastic life ideals. That could be the case of Scenario 3.
5. Without a doubt, this modelling process will support the exploration of many other scenarios and community configurations that will lead us and others to deepen our understanding and fine tune the design and engineering process of communities like monasteries, ashrams, small spiritually inclined communities and family environments.
Based on the above it seems to us that any community willing to operate according to an economy based on actions of kindness needs to build an environment, which will nurture people to grow spiritually and develop their own self-mastery of inner peace. Improved communication and synergy between community members will also promote an environment where people perceive greater kindness and we conjecture that a healthy management of those elements would support newcomers in finding inner peace as long as this comfort zone would be kept in check to prevent a dependency on social and material attachments that would prevent self-mastery. This would in turn make the system grow faster since inner peace is a critical element in raising the quality of space for the community to function in harmony. The feedback loop between inner peace, quality of space and perceived kindness is left for future development of an even higher level of model integration.
We make the observation that when community inner peace is at a low level, the community (system) spends more energy to keep high levels of perceived kindness. In contrast when the community operates at a high or very high level of inner peace it consumes less energy since the system is minimally reliant on resources, social feedback and attachment co-dependencies and therefore the community becomes more resilient. The moral of the story is that without the development of inner peace and self-mastery, people will more likely become highly dependent on resources, emotional counselling and general maintenance in order for the community to be perceived as a kind and nurturing environment. We could almost conceive a set of theorems though without proof, which of course would make them more conveniently expressed as postulates that state:
POSTULATE 1. If IP, the level of inner peace in the community, is very high, then resources and synergetic social interactions will consume a minimum or optimal amount of energy leading to a maximum or optimal level of perceived kindness.
POSTULATE 2. If IP, the level of inner peace in the community, is low, then resources and synergetic social interactions will consume a maximum amount of energy leading to a minimum level of perceived kindness and decay depletion and eventual disintegration of the community.
These postulates we still think could be thought of as theorems whose proof is work in progress if any could be achieved, however a theory of inner peace may be able to be supported by enough experimental verification in future research, hopefully on the side of POSTULATE 1 !!!
GLOSSARY
Actions of Kindness (AoK):
An action of kindness is an event that entails an interaction between a giver and a recipient or receiver, be it an individual or a group. Such an action stands as an opportunity to do good and have a positive impact primarily for the recipient, however, also with a spiritual or emotional benefit for the giver. The giver enjoys the act of giving or doing good. The reader must note that there are indirect benefits from such actions of kindness, which also have positive consequences in other people's lives and communities at large.
In folk wisdom we could describe it as 'what goes around comes around.' At a deeper level the laws of cause and effect may create social feedback loops of happiness and inner peace based on interactions between people that are intended to manifest kindness towards the other.
Actions of kindness differ from actions based only on good intentions in a way that consider more deeply the real needs of the receiver above only the good intention and the different biases, for example cultural or religious biases, of the giver. Actions of kindness have no strings attached to the recipient and can be regarded as genuine acts of unconditional love. In a sense, for the knower of God, actions of kindness are inspired by The Creator and fuelled by Spiritual Values.
Perceived Kindness:
The perception of the quality of being kind by an observer via his or her cognitive and perceptual capacity according to his or her own learned behaviours, cultural and embodied spiritual values. It can be understood as the perception that an observer experiences regarding another human being and his or her disposition to act kindly towards others.
Carrying Capacity Threshold for AoK:
The maximum value that the level Perceived Kindness can take, which is associated with the maximum amount of actions of kindness that the system or community can generate per unit of time.
Quality of Space (QOS):
A level or state variable that quantifies the subjective experience of the quality of environment and relationships that the community provides.
Soft Variables:
A type of variable in a system dynamics model that includes qualitative factors, such as intangibles like love and peace or social variables like morale for example, that are closely related to spiritual and behavioural values. Because of their qualitative nature, soft variables can be difficult or impossible to measure or estimate, however, they can be quantified by providing an appropriate scale. These variables are in all certainty, just as necessary a part of the system as hard-quantitative variables are in order to model, explain or predict the overall dynamics.
ACKNOWLEDGEMENTS
We are very grateful to Enya, Sarah, Keryn, Matthew, Colin, Carey, Shiloh and Kali for their dedication in support and completion of this work. We also express our gratitude to the team of Insight Maker for providing the free and open source online simulation platform that we used for this work.
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