Tag: General Systems Theory

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EFGST

Foundational Causality

New paper and course modules: Foundational Causality

Causality is fundamental to systems thinking, explanation, diagnosis and intervention. Yet causal relationships are often represented in highly compressed form: A → B.

My latest General Systems Theory paper, Foundational Causality, asks what lies behind that arrow.

Beginning with processes and physical transfers of matter, energy and embodied information, the paper progressively examines multiple causal contributions, causal chains and networks, PTP and TPT perspectives, recurring causal structures, persistent causal organisation, conditions and constraints, systems and emergence, causal leverage, and the development of causal knowledge.

A central idea is causal decompression: progressively exposing the processes, transfers, conditions and constraints concealed within apparently simple causal relationships.

The paper is accompanied by eleven free course modules (GST 81–91). These take the learner from elementary cause-and-effect reasoning through causal networks and systems to leverage, causal knowledge and the interaction between hypotheses, explanations and theories.

A single flooding example develops throughout the modules so that learners can see a simple causal representation progressively become a systems-level causal analysis.

Recent research in science education has highlighted the importance of mechanistic reasoning, while other recent work has explicitly explored its relationship with systems thinking. The paper approaches that territory from a General Systems Theory perspective.

Alongside the paper I have also published a new set of General Systems Theory course modules featuring plain-English explanations, diagrams, examples, and practical exercises.

Both the paper and the course modules are open access. The paper is available at:

https://www.academia.edu/172403287/Foundational_Causality_Vers4

https://rational-understanding.com/efgst/

The course materials are available in two ways:

🔗 Open access (self-paced): https://rational-understanding.com/gst-course/

🔗 Supported learning: via Google Classroom through the ISSS Student SIG

Those in full-time or part-time education are especially encouraged to join the Student SIG, where they can benefit from guidance by experienced systems scientists, discussion with fellow learners, and access to a wider international community. To join go to: https://isss.org

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EFGST

Ontological Foundations of General Systems Theory

I’m pleased to share the publication of my latest paper:

Ontological Foundations of General Systems Theory

This paper is the second in a series on General Systems Theory. It sets out a clear, physically grounded framework for understanding reality in systems terms. It brings together concepts of space-time, entities, structure, relationships, causality, and change into a single coherent ontology.

The aim is not to introduce new complexity, but to clarify the foundations on which systems theory rests; providing a consistent basis for analysing systems across physical, biological, and social domains.

The paper is available via the following links:

🔗Academia: https://www.academia.edu/165495501/Ontological_Foundations_of_General_Systems_Theory

🔗Website: https://rational-understanding.com/efgst

Alongside the paper, I have also added a new set of course modules to an existing General Systems Theory (GST) course. These modules correspond to the ontological foundations developed in the paper and are designed to make the concepts accessible through plain-English explanations, diagrams, and practical exercises.

The course materials are available in two ways:

🔗Open access (self-paced): via my website https://rational-understanding.com/gst-course/
🔗Supported learning: via Google Classroom through the ISSS Student SIG.

Those in full-time or part-time education are especially encouraged to join the Student SIG, where they can benefit from guidance by experienced systems scientists, discussion with fellow learners, and access to a wider international community. To join go to : https://isss.org

I hope these resources are useful to those interested in systems theory.

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Admin

Free Systems Theory Courses

I’m pleased to announce the launch of a new series of Systems Theory courses, now available both as open-access materials and as supported courses through the International Society for the Systems Sciences (ISSS).
The programme currently includes:
📜 Motivational Reflexivity (full course available)
📜 General Systems Theory (modules being released progressively)
📜 Social Systems Theory (modules being released progressively)
These courses provide a structured pathway from:
💡 understanding individual behaviour and motivation
💡 through core systems theory
💡 to the analysis of complex social systems
All materials are freely available on my website for open, self-paced study.
For those who would prefer a more structured and supported learning experience, the courses are also available via Google Classroom through the ISSS Student SIG, which is currently free to join for students.
Those in full-time or part-time education are especially encouraged to take this route, as it provides access to a supportive learning environment, including guidance from experienced systems scientists, opportunities for discussion with fellow learners, and engagement with a wider international community. ISSS membership also offers access to a range of resources, events, and professional networks that support both academic and personal development in systems theory.
Access the courses:
Open courses (website):
🔗 https://rational-understanding.com/motivational-reflexivity-course/
🔗 https://rational-understanding.com/gst-course/
🔗 https://rational-understanding.com/sst-course/

Supported courses (ISSS Student SIG):
Join ISSS free of charge as a student at:
🔗 https://www.isss.org/home/
If you are interested in developing a deeper understanding of systems theory, you are very welcome to explore the materials or join us through ISSS for supported learning.

Categories
EFGST

01 Philosophical Foundations of General Systems Theory

This paper sets out the philosophical basis for the Extended Framework for General Systems Theory (EFGST), integrating two complementary perspectives:

  • Cognitive Physicalism – everything that exists is physical and located in space–time, including cognition itself
  • Critical Realism – reality exists independently of our knowledge, but our understanding of it is always mediated

Together, these provide a realist yet epistemically modest foundation for systems science.

The paper explores several key implications, including:

  • systems as real, structured physical entities
  • knowledge as model-based and necessarily partial
  • the distinction between observable events and underlying causal structures
  • and the idea that the future is constrained but not predetermined, unfolding through branching possibilities shaped by interaction and agency

One theme that runs throughout is that we never act directly on reality itself, but on representations of it; representations that are sufficient for action, but never complete.

To illustrate this, I’ve included a banner image accompanying the paper.
You might like to take a careful look at it…

The paper can be downloaded in pdf format from https://rational-understanding.com/EFGST#01

Categories
SST

The Enhanced Morphogenetic Cycle

How do societies adapt to change? Why do some institutions reform successfully while others persist in arrangements that no longer work?

These questions sit at the heart of sociology and systems science. Margaret Archer’s Morphogenetic Approach has long provided a powerful way of analysing them by separating structure, culture, and agency and examining how their interaction over time produces stability or transformation.

A new paper introduces the Enhanced Morphogenetic Cycle (EMC), a systems-based refinement of the morphogenetic framework designed to clarify the mechanisms through which social systems reproduce or transform.

The enhanced framework introduces several key ideas:

• Three domains of constraint, material, relational, and cultural, which together define the conditions within which social interaction occurs.
• Needs, satisfiers, and contra-satisfiers, which explain how interactions provide feedback that stabilises or destabilises social processes.
• Defensive filtering and needs-driven beliefs, which help explain why individuals and institutions sometimes ignore signals that change is necessary.
• Recognition that social systems are overlapping, hierarchical, and multi-scalar, with agency operating not only at the level of individuals but also through organisations and institutions.

One of the most interesting implications of the model is that the morphogenetic cycle can also be interpreted as a learning process. Individuals, organisations, and societies all receive feedback from their interactions with the environment. When that feedback is interpreted reflexively, systems can adapt. When it is filtered or ignored, instability may accumulate.

The Enhanced Morphogenetic Cycle therefore provides a systems perspective on social adaptation, linking individual learning, organisational decision-making, and broader societal transformation.

This paper serves as the foundation for a series of studies that will explore these ideas in greater detail, including topics such as organisational learning, institutional capture, political dynamics, and social responses to environmental challenges. You can read the full paper here:

https://rational-understanding.com/sst

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17. Extended Framework for a General Systems Theory

Introducing the Extended Framework for a General Systems Theory (EFGST)

The “Extended Framework for a General Systems Theory” (EFGST) builds upon the original “Framework for a General Systems Theory” that I first released several months ago. The original framework provided a structured, cross-disciplinary approach to understanding systems, their properties, and the causal processes that drive them.

This new Extended Framework expands this foundation with several key advances that connect systems theory more tightly to physical and informational dynamics:

  1. Seeds and Contra-Seeds describe how systems can be triggered to develop or decay through reinforcing or opposing influences.
  2. Mobus’s Concept of Systemness,  Integrated with the notion of state spaces, helps describe how systems maintain coherence, evolve, and approach attractors.
  3. Troncale’s Linkage Propositions are reinterpreted within EFGST as causal-probabilistic connections that can potentially be used to map probabilities across configuration and state spaces, providing a degree of predictability.
  4. Recomposition provides a new explanatory model for how complex systems build upon rather than replace their components, clarifying how emergence arises in distinct levels.

Together, these extensions bring the framework closer to a unified theory of system dynamics, applicable from physics and biology to social and cognitive systems.

You can read the overview paper and explore the detailed set of definitions and propositions here:

Overview Paper (Academia.edu): https://www.academia.edu/144773922/Overview_of_the_Extended_Framework_for_a_General_Systems_Theory

Overview Paper (Rational-Understanding) and Complete Definitions and Propositions List: https://rational-understanding.com/efgst/

These materials form the foundation for ongoing work towards an integrated General Systems Theory; one that connects the causal, energetic, and informational dimensions of system behaviour.

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09. Unifying Universal Disciplines towards a General System Theory

Unifying Universal Disciplines towards a General System Theory

This paper can be downloaded free of charge from:

https://rational-understanding.com/UUDH#paper & https://www.academia.edu/127960952/Unifying_Universal_Disciplines_Towards_a_General_System_Theory

Systems theory, causality, natural language, and logic have traditionally been pursued as separate disciplines. However, underlying each of these domains are fundamental structures that suggest a deeper, unified framework. The way we structure our understanding of these disciplines is not arbitrary. Rather, it is dictated by principles that govern perception and cognition. It may also be dictated by principles that govern reality.

The Unified Universal Disciplines Hypothesis (UUDH) proposed in this paper posits that Fundamental systems theory, causality, natural language, and logic are different manifestations of the same underlying structure in the way that human beings perceive reality and reason. Each of these domains encodes and processes causal interactions in ways that reflect the level of complexity and perspective employed by the observer.

This paper presents the argument and describes the methodology for unifying these disciplines into a cohesive model that enables more precise reasoning across them. Symbolic Reasoning, an enhancement of traditional set theory, provides a formal tool to facilitate this unification.

UUDH has considerable and diverse explanatory power from quantum theory to human society. The unification of systems, causality, natural language, and logic represents a promising approach to developing a more comprehensive understanding of human cognition and external reality. By integrating these traditionally separate fields, we can enhance our ability to reason about complex systems in a coherent and structured manner. Symbolic Reasoning offers a powerful tool for this integration. However, the approach is hypothetical, and empirical testing is needed to verify it.

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11. The Hierarchy of Organising Principles Uncategorized

The Hierarchy of Organising Principles

I haven’t posted for a while because I have been working on this paper. It is quite long and contains many diagrams. So, I have produced it in pdf format and you can download it via the following link https://rational-understanding.com/my-books#hierarchy-of-organising-principles.

The paper presents a comprehensive hypothesis that seeks to explain the nature of reality and how humans understand it, integrating foundational concepts from critical realism, systems theory, and causality. The hypothesis holds that reality can be viewed as a fractal-like structure, generated by underlying organising principles that operate at various ranks in a hierarchy. Starting from acausal foundational principles, the paper explores how systems interact, transfer matter, energy, and information, and contribute to the complexity observed at different levels of organisation. The hypothesis extends to the idea that human understanding is structured by organising principles that differ from reality’s, leading to distinct layers of comprehension reflected in scientific disciplines. The paper suggests that integrating these principles may help bridge gaps between disciplines, such as the disconnect between social sciences and the biological sciences. This unification has the potential to deepen our understanding of both the natural world and human social behaviour, while identifying new pathways for societal change.

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06. Systems Theory from a Cognitive and Physicalist Perspective

Systems Theory from A Cognitive and Physicalist Perspective Updated

This paper, is available for download in pdf form at https://rational-understanding.com/my-books#Systems-Theory-from-a-Cognitive-and-Physicalist-Perspective

It was originally published in January, 2023, has been updated to include observations from:

  • “A Conceptual Framework for General System Theory”, John A. Challoner, March, 2024.
  • “Different Interpretations of Systems Terms” sent to the Research towards a General Systems Theory SIG of the International Society for the Systems Sciences’ in April, 2024.
  • “The Mathematics of Language and Thought”, John A. Challoner, 2021.

The paper discusses systems theory from a cognitive and physicalist perspective. The cognitive perspective holds that we are our minds and cannot escape the constraints imposed by their biology and evolutionary history. Nevertheless, human cognition is a reasonably accurate representation of reality. Physicalism holds that space-time comprises the whole of reality and that everything, including abstract concepts and information, exists within it.

From this perspective, conceptual and theoretical frameworks for systems theory are proposed and described. Concepts include: the importance of structure; the nature of relationships, causality, and physical laws; and the significance of recursion, hierarchy, holism, and emergence. Human cognitive factors are also discussed, including: their limitations; the nature of information and language; and the search for knowledge in a world of complexity and apparent disorder.

The paper includes the implications of this perspective for General System Theory and Social Systems Theory, suggesting further work to advance those disciplines.

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03. Further Principles of General Systems Theory

Further Principles of General Systems Theory

I will describe General Systems Theory in more detail in the next few articles, and then provide a systems based model which can be used to understand human society, how it works, and why it sometimes fails. This model uses the principles described below.

Near Decomposability. Many natural and artificial systems are structured hierarchically, and their components can be seen as occupying levels. At the highest level is the system in its entirety. Its components occupy lower levels. As we move down through the levels we encounter ever more, smaller, and less complex components. The rates of interaction between components at one level tend to be quicker than those at the level above. The most obvious example of this is the speed with which people make decisions. An individual can make decisions relatively quickly, but the rate steadily slows as we move up the hierarchy through small groups, organisations, and nations, to global society.

Sub-optimisation. This principle recognises that a focus on optimising the performance of one component of a system can lead to greater inefficiency in the system as a whole. Rather the whole system must be optimised if it is to perform at maximum efficiency. Its components must sometimes operate sub-optimally.

Darkness. This principle states that no system can be known completely. The best representation of a complex system is the system itself. Any other representation will contain errors. Thus, the components of a system only react to the inputs they receive, and cannot “know” the behaviour of the system as a whole. For the latter to be possible then the complexity of the whole system would need to be present in the component. The expression “black box” is used to describe a system or component whose internal processes are unknown, and “white box” to describe one whose internal processes are known. Most systems are, of course, “grey boxes”.

An interesting question arises from the principles of near composability and darkness. As explained in previous articles, human beings are motivated by needs and contra-needs. The question is, of course, whether groups of individuals, species, and ecosystems also have needs and contra-needs which differ from their individual members. Are reduced birth rates, for example, a natural species response to population pressures? If so, then near decomposability implies that, because groups, species, and ecosystems are more complex systems than single individuals, the processes which satisfy those needs will proceed more slowly. Darkness implies that as individuals we would be unable to “know” the processes involved, although as a society we might.

Equifinality. The processes in a system can, but do not necessarily, have an equilibrium point, i.e., a point at which the system normally operates. If, for any reason, the processes are displaced from it, then they will subsequently alter to approach that point once more. This characteristic is known as homeostasis. Thus, a given end state can be reached from many initial states, a feature known as equifinality. For example, if a child’s swing is displaced from the vertical and released, then, after swinging to and fro for a while, it will eventually return to the vertical.

Multifinality. It is possible for the processes in a system to have more than one stable point. If a process is displaced a little from one of them, it may ultimately return. However, if it is displaced too far, then it may subsequently approach another equilibrium point. This is a feature of natural ecosystems. If they are damaged in some way, they will ultimately return to a stable state. However, this state will often differ from the earlier, damaged, original.

Dynamic Equilibrium. This principle is like that of equifinality but applies to rates of change in systems. Some systems are dynamic and have a stable rate of change. If displaced from that rate of change for any reason, they will ultimately return to it. This is known as homeorhesis, a term derived from the Greek for “similar flow”. Again, a dynamic system may have several stable rates of change.

Relaxation Time. Relaxation means the return of a disturbed system to equilibrium. The time it takes to do so is known as the relaxation time.

Circular Causality or Feedback. Feedback occurs when the outputs of a system are routed back as inputs, either directly or via other systems. Thus, a chain of cause and effect is created in the form of a circuit or loop. The American psychologist Karl Weick explained the operation of systems in terms of positive and negative feedback loops. Systems can change autonomously between stable and unstable states depending on the dominant form of feedback. Feedback is, therefore, the basis of self-maintaining systems which will be discussed in the next article.