Social systems thinking – wrt systems in general
Copyright 2016 Graham Berrisford. One of about 100 papers on the
System Theory page at http://avancier.website. Last updated 13/09/2019 15:47
Some systems thinkers regard a system as no more than "some parts related in an organised whole".
Some social systems thinkers regard a system as no more than “some people with some shared aims”.
For sure, discussion of how people best cooperate in groups to achieve aims, and improve the way they work, is very valuable.
What does the system concept add to that?
It seems timely to revisit the basic principles of general system theory.
To explain that a real-world entity (hardware, software, organism, society or business) is not a system.
It is, rather, as many systems as we envisage, describe and observe it as conforming to, well enough.
And to explain how the term "system” and several related terms are used differently in different branches of system thinking.
Contents
Mapping
concrete networks to abstract systems.
Mapping
concrete actors to abstract roles
On mutations in “self-organising systems”
On
goals/aims, decisions/choices, freedom and constraints
Some
define a system as "parts related in an organised whole", which may
be true but is too vacuous to be of much use.
That definition includes passive structures and taxonomies,
like the Linnaean system for classifying organisms.
Here,
the term “system” has the more interesting and useful meaning that emerged in
the 20th century.
In most modern systems thinking, the “parts” of a system
are actors or components that interact in activities.
Generally, a system can be described
as actors interacting in activities to advance the system’s state
and/or transform inputs into outputs.
·
The actors are structures (in space) that
perform activities - in roles and processes that are describable and testable.
·
The activities are behaviors (over time) that
change the state of the system or something in its environment - governed by rules
that are describable and testable.
·
The state is describable as a set of state
variables - each with a range of values.
·
An open system is connected to its wider environment
- by inputs and outputs that are describable and testable.
These
concepts can be seen in writings of Ashby, Forrester and Checkland.
In
Ashby’s cybernetics, a system is modelled as processes that maintain a set of
state variables.
In
Forrester’s system’s dynamics, a system is modelled as inter-stock flows that maintain
a set of stocks (variable populations).
In
Checkland’s soft systems method, a system is modelled as actors who perform
processes that transform inputs into outputs for customers.
Ashby, Ackoff, Checkland and others emphasised that a system is a perspective of a reality.
|
The basis of system theory |
|
Abstract systems (descriptions) <create and use> <represent> System thinkers <observe and envisage > Concrete systems (realities) |
These
papers take this triangular, scientific, view of system theory as axiomatic.
An abstract system is a description or model of how some part of the word behaves, or should behave.
A concrete system is a realisation (by a real-world entity) that conforms well enough to an abstract system.
For further discussion of the abstract/concrete distinction, read about Ashby’s “Cybernetics”.
It is important to distinguish two very different ways a system can change.
System state change
System state change (within a system generation) is a change to the values of a system’s state variables (e.g. body temperature).
To change Ashby’s system state is to update its variable values in response to an event or condition.
To change Forrester’s system state is to change the quantity of a stock in response to an inter-stock flow.
System mutation
System mutation (between system generations) is a change to the nature of a system.
To change Ashby’s system is to change its variable types or processes.
To change Forrester’s system is to add/remove stocks or change inter-stock flows.
The two kinds of change are often confused in
systems thinking discussion.
And many social systems thinkers apply the
terminology of system state changes to system mutations.
For further discussion of system change and change control, read “System change”.
Millions of years ago, animals evolved to conceptualise things they perceived in the world.
Later, animals in the same species evolved to communicate concepts to each other.
To communicate is to
send a message that conveys information, such as a description, direction or
decision.
This table
distinguishes some concepts related to communication.
|
WKID |
meaning |
|
Wisdom |
is
the ability to respond effectively to knowledge in new
situations |
|
Knowledge |
is information
that is accurate enough to be useful |
|
Information |
is
any meaning created or found in a structure or behavior by an actor |
|
Data |
is a structure
of matter/energy in which meaning has been created or found |
For an act of communication to succeed in conveying
information, two roles must be played.
· One actor must encode some information or meaning
in a data structure or message.
· Another actor must decode the same
information or meaning from that data structure or message.
In systems, in business, in all science, it is necessary for communicating actors to use the same code or language.
Messages must be expressed using the symbols and grammar of a language shared by senders and receivers.
Scripts for regular behaviors must be expressed using a language known to the actors.
A system must be described using a domain-specific language, else the system description cannot be agreed or tested.
For further discussion of data, information and communication, read here about “Second order cybernetics”.
Some systems thinkers regard a system as no more than "some parts related in an organised whole".
Some social systems thinkers regard a system as no more than “some people with some shared aims”.
For sure, discussion of how people best cooperate in groups to achieve aims, and improve the way they work, is very valuable.
What does the system concept add to that?
A system was described above as actors
interacting in orderly activities to maintain the system’s state
and/or transform inputs into outputs.
A social system is further characterised by the communication of information between actors, using of some kind of language (not necessarily verbal).
Some systems thinkers have discussed communication in non-human systems.
E.g. the mating ritual of sticklebacks, the pollen locating system of honey bees, a chimpanzee hunting party.
In all these cases, system actors perform regular activities in response to information given to them by other actors.
Unsurprisingly, most social systems thinkers are more interested in human social systems.
In the 19th century, some viewed a social system as a homeostatic system.
Yet many a social group is arguably better characterized as unstable and continually shifting its direction.
It is a social network in which actors act in ad hoc, novel, ways, in response to whatever events come across the horizon.
Many since then have drawn analogies between social organisations and biological organisms.
Some look at the workings of a social organization as an extrapolation from the workings of a biological organism.
Other system thinkers, such as Russell Ackoff, have deprecated this approach.
Why? Because the distinguishing feature of human social groups is the ability of actors to make choices.
Any actor can obey, disobey or act contrary to any goals, roles or rules anybody might conceive.
To put it another way, the social network that realises a social system is not itself a system.
When general system theory (as in Ashby’s cybernetics) emerged in the 1950s, sociologists tried to embrace its ideas.
Many have written wisely about human institutions and the human condition.
However, their use of the term “system” often differs from its meaning in more general system theory.
There has been confusion of:
· abstract systems with concrete systems
· system state changes with system mutations
· continuous mutations with incremental mutations
· actors in social networks with roles in social systems.
A system theorist ought to carefully distinguish these things.
In his “System of System Concepts” (1971), Ackoff distinguished these concepts.
· An abstract system: a system in which the elements are concepts.
· A concrete system: a system in which physical objects realise an abstract system.
· System state: the values of a system’s properties at a particular time.
|
A basis for social systems thinking |
|
Abstract social
systems <create and use> <represent> Sociologists <observe and envisage > Concrete social systems |
However, Ackoff was inconsistent;
he started off distinguishing abstract systems from concrete systems.
Later, he spoke of a human
organisation as being a system
regardless of any abstract system description.
This confusion of a human social
network with a system runs through much systems thinking discussion.
This table is an attempt to
separate three concepts that have become entangled.
|
Abstract
social system |
A set of roles and rules (the logic or laws actors follow) |
|
Concrete
social system |
Actors playing the roles and acting according to the rules |
|
Social
network |
Actors who inter-communicate and act as they choose |
Given that the systems of interest to us involve both actors and activities, there is a choice to be made.
“The first decision [a theoretician has to make] is what to treat as the basic elements of the social system.
The sociological tradition suggests two alternatives: either persons or actions." Seidl 2001.
Choose persons, then your system is a bounded group of interrelated actors (who perform activities).
In what we call a “social network”, a group of actors communicate with each other, and may act as they wish.
A social network is defined by the actors who belong to it, regardless of what actions they perform.
It is an ever-unfolding process, its dynamics evolve as actors determine what they do - including joining and leaving the network.
Choose actions, then your system is a bounded pattern (or choreography) of interrelated activities (performed by actors).
In what we call a “social system”, a group of actors play given roles in which they act according to given rules.
A social system is defined by the activities performed in it, regardless of which actors perform them.
Since its dynamics are fixed – at least for a generation – they can be described and tested.
A human social network is both
less and more than any system it realises.
Less, in that it may not implement
the given system completely or perfectly.
More, in that it does much more
than is described by that system, and may realise other systems.
The actors in a social network may cooperate, compete or conflict with each other.
One actor may undermine the actions of another.
Actors may behave in disorderly, unsystematic and unsystemic ways.
On the other hand, the actors in a social network may agree, or be directed, to realise one or more social systems.
Some of those systems may be complex, others simple.
Some may be adaptable, others inflexible.
Some may purely social, others socio-technical.
Some may cooperate with each other, others be in conflict.
Systems as
games
Anatol Rapport is perhaps best known as a founding father of game theory
A common
concern in “management science” is how the actors in a system best
cooperate to meet aims.
Rapport studied games as systems in which communicating
actors may compete or have conflicting aims.
In discussion of a human society, we often blur the distinction between networks and systems.
But it helps to recognise they are different views, and in a many-to-many relationship.
One social network can realise several distinct social systems. E.g. one group of people may play roles in a church and in a game of poker.
And one social system can be realised by several social networks. E.g. the roles and rules of poker are realised by many groups of people.
In this 2003 book, Michael Jackson proposed as follows.
"Social systems are not just ‘complex adaptive systems’ bound by the fixed rules of interaction of their parts.
Rather, they are ‘complex evolving systems’ that can change the rules of their development as they evolve over time."
He could more clearly have written:
“Social networks are not systems, in which actors are bound by roles and rules
Rather, they are “complex evolving entities” that can change the roles or rules of any system(s) they realise.”
Feudalism was a combination of legal and military customs in medieval Europe.
It structured a society around roles related to the holding of land and the provision of services or labour to land holders.
You may see a feudal society as the realisation by a social
network of the roles and rules of an abstract system.
Each geographically distributed feudal society developed and
maintained its own roles and rules.
Changes to roles and rules had to be agreed (or a least
accepted) by actors playing roles in the system.
Social cells
A social cell is a social network in which actors find that realising the roles and rules of an abstract system is attractive.
Actors playing roles in the system find it so attractive
that they resist any change to the
system.
The Japanese tea ceremony has been given as an example; a community choir might be another.
In discussion of human societies, we often blur the distinction between abstract roles and concrete actors.
But it helps to recognise one role can be played by many actors (at the same time, or at different times).
And one actor can play many roles, in the same system, or in different systems (even competing systems).
Bear in mind that most of one human actor's time, energy, attention likely lies outside a system they play a role in.
They live, breath, speak and otherwise act outside of any
system that could ever be described.
The say and do things that cannot possibly be regarded as systematic, and sometimes defy any given rules.
One actor may undermine the aims or actions of another.
Suppose an actor in a feudal society or a game of poker stops playing a role he/she was assigned to.
The actor changes how they respond to events - without the prior agreement or understanding of other actors.
Then what had been a describable and testable system will disappear.
And what remains may be describable only as a chaotic social network.
Systems thinkers often use the term “emergence”.
Some uses are questionable: “The concept has been used to justify all sorts of nonsense.” Gerald Marsh.
You might say that when a system changes from one state to the next, the new state emerges from the performance of its regular behaviors.
You might say that when a system mutates, the new generation of the system emerges from a change made to the variables, roles of the system.
Arguably, the latter is an abuse of the term.
Emergence of observable behaviors or state changes
Emergence occurs
when an entity is observed to do what its component parts or subsystems cannot
do on their own.
This category includes the following cases.
The emergence of a system's properties from the
interactions of its components.
“that a whole machine should be built of parts of given behavior is not sufficient to determine its behavior as a whole:
only when the details of coupling are added does the whole's behavior become determinate. ” Ashby 1956
E.g. Neither a rider nor a bicycle to can do alone what they can do together – move smoothly forwards.
The V shape of a flight of geese cannot emerge until three geese fly together.
The waving of the Tahoma Narrows bridge emerged from the interaction between its cables and the wind.
The emergence of higher-level phenomena from lower-level
phenomena
This can be seen in a hierarchy of subsystems related by client-server interactions.
E.g. consider the multi-layer operation of a messaging system like Facebook.
At the top level, people are using words to share ideas and pictures.
Messages pass down and back up the multiple layers of a communication stack
At the bottom level, electrons or radio waves are in motion.
Emergence of observable mutations (novel variables, roles
or rules)
This is a very different kind of emergence
If it happens continually in an ad hoc, uncontrolled or unpredictable way then there is no system - only an ever-unfolding process.
To be describable and testable as a system, an entity’s behavior must be sufficiently "regular, repeatable or determinate" (Ashby 1956).
Suppose the actors in a social network continually invent and copy new activities in an uncontrolled or unpredictable way.
Then there is no recognisable, describable or testable system.
It is impossible to know what an actor will do next, or even which actors are playing roles in which systems.
We can observe people communicating and doing things, in a social network. but to call that a “system” is useless if not meaningless.
For more on emergence, read “Emergence”.
You may look at a chess game as the realisation by a social
network (a pair of actors) of the roles and rules of an abstract system.
The first pair of people to play something like a game of
chess must have agreed the rules that choreograph their roles in the
game.
The rules of chess varied somewhat from place to place, and
were extended during the Middle Ages.
The rules continued to be modified until the early 19th
century, when they reached essentially their current form.
Changing the rules is not part of
the game itself.
An actor cannot simultaneously move a chess piece and change the rules by which that piece is moved.
To change the rules, the actor must
1. stop playing their role in the game.
2. step up into the higher or meta system in which their role is to suggest, discuss and agree rule changes.
3. ensure the rule change is agreed with their opponent
4. step back down into their role as game player.
As Ashby and Maturana agreed, the notion of a "self-organising system” undermines the concept of a system.
The notion requires division of a system into higher and lower parts – as in the example above.
For further discussion, including the need for change control, read “System change” and about “Second order cybernetics”.
Authors use these terms glibly, without being clear what they mean.
What is a complex adaptive system? How are complexity and adaptivity defined and measured?
What kinds of adaptation or change are
possible? How is a change measured? How is the ease of change measured?
As in so much systems thinking discussion, there are ambiguities
Complex?
In cybernetics, a system is complex if the system description is complex; the roles and rules are complex
To social systems thinkers, a system is complex if the reality is complex, the actors are complex (their roles and rules may be lightly prescribed, if at all.)
Adaptive?
In cybernetics, a system adapts to feedback from its environment by changing state – which may be called self-regulating.
To social systems thinkers, a system mutates as actors change its roles, rules or aims - which may be called self-defining.
System?
In cybernetics and system dynamics, a system is a collection of repeated or repeatable activities.
In social systems thinking, a system is a collection of actors, who interact as they choose (a social network).
In his 2003 book, Michael Jackson proposed as follows.
"Social systems are not just ‘complex adaptive systems’ bound by the fixed rules of interaction of their parts.
Rather, they are ‘complex evolving systems’ that can change the rules of their development as they evolve over time."
He could more clearly have written:
“Social networks are not systems, in which actors are bound by roles and rules
Rather, they are “complex evolving entities” that can change the roles or rules of any system(s) they realise.”
A
complex evolving entity (or ever unfolding process) - in which no behavior is regular,
or determinate, or reproducible – is not a system in the ordinary sense of the
term.
This table distills some ambiguities.
|
Term |
School |
Meaning |
|
Complex |
Classical cybernetics |
The measurable complication of an abstract system description |
|
Sociological thinking |
The un-measurable disorder or unpredictability of a real-world situation |
|
|
Adaptive |
Classical cybernetics |
System state change – updating the values of system variables |
|
Sociological thinking |
System mutation - changing the roles and rules of the system (evolving) |
|
|
System |
Classical cybernetics |
Actors playing roles and acting
according to rules |
|
Sociological thinking |
A group of self-aware actors who inter-communicate and act as they choose, or a problematic situation (an entity) |
|
|
Emergence |
Classical cybernetics |
A property arising from coupling
subsystems into a larger system |
|
Sociological thinking |
Not seen before, new, or surprising. |
For more on this topic, including definitions from the Sante Fe Institute and MIT, read “Complex adaptive systems”.
Remember the definition of “system” as "parts related in an organised whole".
Every material entity in the universe is a whole made of interrelated parts.
The idea does not significantly advance our understanding of systems.
As an actor who plays a role in a system, you are a part of
that reality.
But the term part is misleading, since you are much more than
a part of any system.
You give only a fraction of your time, ability and energy to each of the many roles you play in different systems.
E.g. Imagine you are an actor who plays a role as a Clerk in the Criminal Justice System.
To speak of you as a “part” of that system is rather misleading – since you are so much more than that.
The role requires only a fraction of your time, ability and energy.
The study of whole-part composition is called mereology.
However, it turns out that the concept of composition is very loose.
It seems clearer to distinguish membership from containment.
Whereas members play a logical role in a whole, parts are physically contained in a whole.
To illustrate the difference, contrast cells and people.
|
A cell as a part of a biological organism |
A
person as a member of social groups |
|
The organism occupies a three-dimensional space. |
A social group is distributed in space. |
|
A cell belongs to one and only one organism – which physically contains it. |
One person can belong to many social groups. |
|
The containment is persistent. |
Membership is transient; people can join and leave groups. |
|
A cell contains an identifier (DNA) that shows which organism a cell belongs to. |
A person does not contain the identifier of a group. |
You play a role in a social network whenever you communicate with others in it.
Likewise, you play a role in a social system whenever you act according to the rules of that system.
You are hugely more than any part you play, which consumes only some of your time and energy.
You exist independently – and might leave a social group with little or no effect on it.
Your aims and principles are distinct from those of the groups you are member of.
Moreover, the various groups you are a member of may have conflicting aims or principles.
A system can be simpler than its parts or members
Some (starting with Boulding, 1956) assume that an aggregate or composite is more complex than its “parts”.
But the reverse is often true.
A coarse-grained system (or process) can be simple, despite the fact that its atomic actors or actions are internally complex.
E.g. A game of poker is a simple social system, much simpler than the people who play parts in that system.
E.g. A groupware system with message boards is a simple social system in which people post and reply to messages.
Their message content is not "regular or repeated"; its meaning is not designed or tested by the system designers.
So, the groupware system is simpler than the discussions it enables and the actors who play parts in that system.
Unfortunately, the equation system = organization is embedded in the history of systems thinking.
Biologists (like Bertalanffy) use "organisation" with reference to orderly interaction between the organs of a biological organism.
Sociologists (like Ackoff) use "organisation" to mean a managed human institution, such as a church or a business.
So, “organisation” can mean either a set or roles and rules (a system) or a human institution or business (a social network).
In writing that "every organisation is a system", Ackoff seemed to contradicted his own basic system ideas.
He had earlier written than different observers can perceive one entity as instantiating different systems.
The system of interest depends on the perspective you bring to the reality, and which of infinite possible descriptive variables you are interested in.
Indeed, two decades before Ackoff, Ashby had pointed out that every substantial entity can realise countless different systems.
So, although some speak of a business as a “system of systems”, a system theorist sees it differently.
They see a business as an entity or social network that can realise countless describable and testable systems.
And it is possible, even likely, that some of those systems will have conflicting goals and/or compete for resources.
Moreover, a business is more than the sum of the systems it employs.
Since much of what business directors and employees say and do is not at all systematic.
Certainly, the ad hoc interactions of people in social networks are very important to business success.
Not least, when they discuss how to change the roles and rules of systems they are employed to realise or to manage.
Different observers of and actors in a business may see that business as having different goals.
IBM is an entity or social network. Seen as a system, what is its goal?
· a system for making its directors happy?
· a system for making a profit for shareholders?
· a system for making and selling products to customers?
· a system for providing consulting services to customers?
· a system for providing income to suppliers?
· a system for employing and paying people?
· a system to pay corporation tax to the government?
· a system to minimize climate change?
Each goal may be served by different systems that operate within IBM.
Not only can IBM employ many systems, some discrete, others more or less tightly integrated.
But some of those systems may have conflicting goals, or compete for resources.
Must the actors in a system share its aims?
Some presume the goals of individual actors should be shared, or match the goals of any organisation those actors play roles in.
What matters in general is the compatibility of goals with
the continuance of the system - rather than their commonality.
Naturally evolved systems have no goals. E.g. neither the solar system nor its planets have goals.
In game theory (an interesting branch of general system theory), the players often have opposing goals.
In a business, the goal of employees to make more money from their employment may be in opposition to the goal of employer to make more profit.
In the performance of play, the objectives of the actors differ from the objectives of the audience.
So, actors playing roles in a system may have different goals from each other, and from the system as a whole.
Also, actors may play a role reluctantly, or manipulate a system to their own ends, in opposition to the goals of the system as a whole.
On freedom of choice
In many natural social systems (e.g. the
stickleback mating ritual) actions and responses are instinctive.
Some social animals (e.g. chimpanzees) do
invent new behaviors and copy each other.
However, humans are uniquely, extraordinarily,
inventive and able to follow instructions.
We can and do design systems in
which activities and responses are scripted or otherwise pre-ordained.
Two kinds of decision
In a social network, actors can make ad hoc decisions to act in ad hoc ways that lead them down novel paths.
In a social system, actors make pre-ordained decisions that select between pre-ordained actions.
In both, a decision is a constraint in the sense that choosing one path denies another.
Two kinds of freedom
In a social network, freedom means individual actors set their own aims and define their own activities.
It means actors in one social network can have different aims and do different things, and change them without any overarching change control.
Increasing this kind freedom leads the network to behave chaotically - which is not a system at all.
In a social system, actors must accept the concept of change control, not change their role on a whim
Within a system, freedom means actors are able to choose between many pre-ordained actions.
Increasing this kind freedom tends increase the complexity of the system.
The hard/soft distinction means different things
to different people.
There is a
spectrum from entities that realise an abstract system closely, as an orchestra
realises the score of a symphony.
To entities that
realise an abstract system loosely, as a software development team may realise
an agile development method.
But the hard/soft
distinction is usually more to do with approach taken to system
definition.
One of the first soft system thinkers, Churchman, said "a thing is what it does".
He outlined these considerations for designing a system:
· “The total system objectives and performance measures;
· the system’s environment: the fixed constraints;
· the resources of the system;
· the components of the system, their activities, goals and measures of performance; and,
· the management of the system.”
Today, soft
systems thinking approaches typically involve:
·
Considering the bigger picture
·
Studying the vision/problems/objectives
·
Identifying owners, customers, suppliers and
other stakeholders
·
Identifying stakeholder concerns and assumptions
· Unfolding multiple views, promoting mutual understanding
· Analysis, visual modelling, experimentation or prototyping
· Considering the cultural attitude to change and risk
· Prioritizing requirements.
For more on soft systems methodologies read “Checkland’s ideas”.
Even mechanical engineers use ideas attributed to “soft systems thinking”.
Still, there is a schism between much social systems thinking
and more general system theory.
Sociologist use words drawn from cybernetics and system
dynamics (such as emergence, requisite variety, attractors, chaos, etc.) but
with different meanings.
Much social system thinking discussion is far from general
system theory, cybernetics and system dynamics.
Some is even removed from the soft systems methods of
Churchman and Checkland, which are centered on the definition of a new SIPOC
transformation system.
It might better be called human situation/problem thinking.
There is a substantial overlap between social systems thinking and management science.
In both, the science is often unclear or thin.
A tradition is to discuss a managed human institution or business as though it is a "system".
For sure, a business can be as a social network, a group of human actors who are employed to work toward some agreed purpose(s).
Discussion of how people best cooperate in groups to achieve aims, and improve the way they work, is very valuable.
Management scientists and authors like Ackoff, Senge and Jackson offer good advice to managers.
However, the use of term “system” in this context is questionable.
Peter Senge's idea of "The learning
organisation"
Organisation can refer to a particular set or roles and rules (a system).
Senge’s concern is, rather, a human institution or business (a social network).
Learning can mean learning of a fact, rule, event or condition; or learning to perform a specified process.
Senge’s concern is, rather, learning from the outcome of past experience, from responses to past events.
This cooperation may lead to changes of various kinds.
Including but not only, changes to the roles and rules of systems employed by that business.
Michael Jackson’s review of
system thinking approaches
In his 2003 book, Jackson questionably:
· refers to a real-world human organisation/institution as a "system"
· conflates what may better be distinguished as social networks and social systems.
· suggests "hard systems thinking" is reductionist rather than holistic - contrary to goal and service-oriented approaches.
· suggests "hard systems thinking" can produce only one view of a real-world organisation – rather than multiple stakeholder views.
· differentiates hard systems thinking, soft system thinking and system dynamics - though all three model a system as a set of roles and rules
· relates complexity to disorder – which may confuse system activity with system state change trajectory.
· refers to "complex adaptive system" - without saying how to measure complexity or adaptivity.
Some systems thinkers regard a system as no more than "some parts related in an organised whole".
Some social systems thinkers regard a system as no more than “some people with some shared aims”.
For sure, discussion of how people best cooperate in groups to achieve aims, and improve the way they work, is very valuable.
What does the system concept add to that?
It seems timely to revisit the basic principles of general system theory.
To explain that a real-world entity (hardware, software, organism, society or business) is not a system.
It is, rather, as many systems as we envisage, describe and observe it as conforming to, well enough.
And to explain how the term "system” and several related terms are used differently in different branches of system thinking.
The analysis above points to a schism in systems thinking.
Later papers go on to explain how von Foerster's "second order cybernetics" undermines Ashby's “classical cybernetics”.
And how, as Ashby and Maturana agreed, the concept of a “self-organising social system” undermines the concept of a system.
Such a thing is better seen as a social network – an ever-unfolding process - which may realise successive generations of a social system, or several of them.