Author Archives: antlerboy - Benjamin P Taylor
“RECURSIVE FRAME ANALYSIS: A Qualitative Research Method for Mapping Change-Oriented Discourse” by Hillary Keeney, Bradford Keeney et al.
Another free whole book
Description
Recursive Frame Analysis (RFA) is a qualitative research method for mapping and analyzing change-oriented conversation. Cybernetician and therapist Bradford Keeney invented RFA over twenty years ago as a means of discerning and indicating the bare bones organization of real-time therapeutic performance. This book revisits some of Keeney’s original ideas while providing a more exhaustive theoretical foundation for RFA, a thorough exploration of its practical application as a research tool, and several detailed analyses of therapy sessions.
Rooted to Gregory Bateson’s notion of contextual frame and the way that a distinction can recursively operate on itself as formulated by G. Spencer-Brown’s Laws of Form, RFA offers both researchers and practitioners of all kinds a formal way of tracking the dramatological construction and movement of a conversation through its beginning, middle, and end episodes. By limiting the analysis to the actual performance of the conversation being studied – including spoken discourse and description of non-verbal action – RFA lays bare the primary distinctions, re-indications, and contextual frames embodied by the communication being studied, as well as those of the researcher. Commentary later generated by the researcher must be demarcated as a separate order of discourse, providing opportunity for multiple layers of analysis by researchers while keeping the primary data intact.
Though this book primarily exemplifies the application of Recursive Frame Analysis to the study of therapeutic sessions, RFA as a research tool is not limited to this domain but can be applied to the analysis of any change-oriented conversation, interaction, or even textual discourse to track the primary distinctions, recursively generated re-indications, and emergent contextual frames being constructed. It is intended that this book serve as a resource for the future application of RFA across multiple fields.
Publication Date
2015
Publisher
The Qualitative Report
City
Fort Lauderdale
Keywords
Recursive Frame Analysis, RFA
Disciplines
Community-Based Learning | Community-Based Research | Quantitative, Qualitative, Comparative, and Historical Methodologies | Social and Behavioral Sciences | Sociology
NSUWorks Citation
Keeney, Hillary; Keeney, Bradford; and Chenail, Ronald, “RECURSIVE FRAME ANALYSIS: A Qualitative Research Method for Mapping Change-Oriented Discourse” (2015). TQR Books. 1.
https://nsuworks.nova.edu/tqr_books/1
Strategic Assumption Surfacing and Testing (SAST)
Mitroff’s ‘operationalization’ of Churchman’s systems approach, part 1
In table 12-3 (p. 301 of Mason’s and Mitroff’s ‘Challenging strategic planning assumptions’) major approaches to business problem solving are compared, including the systems approach and SAST (strategic assumption surfacing and testing), but also analytic modelling (typical of operations research), the case method (widely used, but lacking in objectivity), structured approaches (e.g. PIMS and its many derivatives, often failing to look at key non-quantifiables). The problem with the systems approach is that it is difficult to operationalize (although it could be argued that Wicked Solutions solved that problem). The problem of SAST may be the unwillingness of participants to lay bare their assumptions. This is a general problem in all approaches where we want to leave no stone unturned (as assumptions, e.g. about people’s motivations, lurk beneath them). In this post I will argue that SAST can be combined with…
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Introduction to the Modeling and Analysis of Complex Systems – Open SUNY Textbooks
full, free textbook!
Source: Introduction to the Modeling and Analysis of Complex Systems – Open SUNY Textbooks
Introduction to the Modeling and Analysis of Complex Systems
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PDF DOWNLOAD 19 MB
- Publication Date: August 13, 2015
- ISBN: 9781942341062
- OCLC: 918567125
- Affiliation: SUNY Binghamton
Author(s): Hiroki Sayama
Keep up to date on Introduction to Modeling and Analysis of Complex Systemsat http://bingweb.binghamton.edu/~sayama/textbook/!
Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs. Python sample codes are provided for each modeling example.
This textbook is available for purchase in both grayscale and color via Amazon.com and CreateSpace.com.
REVIEWS:
Hiroki Sayama’s book “Introduction to the Modeling and Simulation of Complex Systems” is … a unique and welcome addition to any instructor’s collection. What makes it valuable is that it not only presents a state-of-the-art review of the domain but also serves as a gentle guide to learning the sophisticated art of modeling complex systems. –Muaz A. Niazi, Complex Adaptive Systems Modeling 2016 4:3
… Sayamaʼs book is a very good instrument for students who want to read an introductory text on modeling and analysis of complex systems, and for instructors who need such a text in simple language for their complex systems courses and projects. The book offers a good introduction to the complex systems terminology and plenty of readily available examples with technical implementation details. … Overall, Introduction to the Modeling and Analysis of Complex Systems offers a novel pedagogical approach to the teaching of complex systems, based on examples and library code that engage students in a tutorial-style learning adventure. It is a solid tool that may become one of the primary instruments for teaching complex systems science and help the discipline to become more established in the academic world, triggering the necessary transition from a top-down tradition to a bottom-up complex systems approach.
-Stefano Nichele, Artificial Life 22(3): 424-427, 2016. www.mitpressjournals.org/doi/abs/10.1162/ARTL_r_00209
Table of Contents
I Preliminaries
1 Introduction
1.1 Complex Systems in a Nutshell
1.2 Topical Clusters
2 Fundamentals of Modeling
2.1 Models in Science and Engineering
2.2 How to Create a Model
2.3 Modeling Complex Systems
2.4 What Are Good Models?
2.5 A Historical Perspective
II Systems with a Small Number of Variables
3 Basics of Dynamical Systems
3.1 What Are Dynamical Systems?
3.2 Phase Space
3.3 What Can We Learn?
4 Discrete-Time Models I: Modeling
4.1 Discrete-Time Models with Difference Equations
4.2 Classifications of Model Equations
4.3 Simulating Discrete-Time Models with One Variable
4.4 Simulating Discrete-Time Models with Multiple Variables
4.5 Building Your Own Model Equation
4.6 Building Your Own Model Equations with Multiple Variables
5 Discrete-Time Models II: Analysis
5.1 Finding Equilibrium Points
5.2 Phase Space Visualization of Continuous-State Discrete-Time Models
5.3 Cobweb Plots for One-Dimensional Iterative Maps
5.4 Graph-Based Phase Space Visualization of Discrete-State Discrete-Time Models
5.5 Variable Rescaling
5.6 Asymptotic Behavior of Discrete-Time Linear Dynamical Systems
5.7 Linear Stability Analysis of Discrete-Time Nonlinear Dynamical Systems .
6 Continuous-Time Models I: Modeling
6.1 Continuous-Time Models with Differential Equations
6.2 Classifications of Model Equations
6.3 Connecting Continuous-Time Models with Discrete-Time Models
6.4 Simulating Continuous-Time Models
6.5 Building Your Own Model Equation
7 Continuous-Time Models II: Analysis
7.1 Finding Equilibrium Points
7.2 Phase Space Visualization
7.3 Variable Rescaling
7.4 Asymptotic Behavior of Continuous-Time Linear Dynamical Systems
7.5 Linear Stability Analysis of Nonlinear Dynamical Systems
8 Bifurcations
8.1 What Are Bifurcations?
8.2 Bifurcations in 1-D Continuous-Time Models
8.3 Hopf Bifurcations in 2-D Continuous-Time Models
8.4 Bifurcations in Discrete-Time Models
9 Chaos
9.1 Chaos in Discrete-Time Models
9.2 Characteristics of Chaos
9.3 Lyapunov Exponent
9.4 Chaos in Continuous-Time Models
II Systems with a Large Number of Variables
10 Interactive Simulation of Complex Systems
10.1 Simulation of Systems with a Large Number of Variables
10.2 Interactive Simulation with PyCX
10.3 Interactive Parameter Control in PyCX
10.4 Simulation without PyCX
11 Cellular Automata I: Modeling
11.1 Definition of Cellular Automata
11.2 Examples of Simple Binary Cellular Automata Rules
11.3 Simulating Cellular Automata
11.4 Extensions of Cellular Automata
11.5 Examples of Biological Cellular Automata Models
12 Cellular Automata II: Analysis
12.1 Sizes of Rule Space and Phase Space
12.2 Phase Space Visualization
12.3 Mean-Field Approximation
12.4 Renormalization Group Analysis to Predict Percolation Thresholds
13 Continuous Field Models I: Modeling
13.1 Continuous Field Models with Partial Differential Equations
13.2 Fundamentals of Vector Calculus
13.3 Visualizing Two-Dimensional Scalar and Vector Fields
13.4 Modeling Spatial Movement
13.5 Simulation of Continuous Field Models
13.6 Reaction-Diffusion Systems
14 Continuous Field Models II: Analysis
14.1 Finding Equilibrium States
14.2 Variable Rescaling
14.3 Linear Stability Analysis of Continuous Field Models
14.4 Linear Stability Analysis of Reaction-Diffusion Systems
15 Basics of Networks
15.1 Network Models
15.2 Terminologies of Graph Theory
15.3 Constructing Network Models with NetworkX
15.4 Visualizing Networks with NetworkX
15.5 Importing/Exporting Network Data
15.6 Generating Random Graphs
16 Dynamical Networks I: Modeling
16.1 Dynamical Network Models
16.2 Simulating Dynamics on Networks
16.3 Simulating Dynamics of Networks
16.4 Simulating Adaptive Networks
17 Dynamical Networks II: Analysis of Network Topologies
17.1 Network Size, Density, and Percolation
17.2 Shortest Path Length
17.3 Centralities and Coreness
17.4 Clustering
17.5 Degree Distribution
17.6 Assortativity
17.7 Community Structure and Modularity
18 Dynamical Networks III: Analysis of Network Dynamics
18.1 Dynamics of Continuous-State Networks
18.2 Diffusion on Networks
18.3 Synchronizability
18.4 Mean-Field Approximation of Discrete-State Networks
18.5 Mean-Field Approximation on Random Networks
18.6 Mean-Field Approximation on Scale-Free Networks
19 Agent-Based Models
19.1 What Are Agent-Based Models?
19.2 Building an Agent-Based Model
19.3 Agent-Environment Interaction
19.4 Ecological and Evolutionary Models
Bibliography
Index
are there any developed methods specific to #complexitytheory other than Agent Based Modelling?
I asked this question on social media and in the systems thinking facebook groups (#lazyweb – all those I could address with a single click through buffer.com).
I think my emergent point is that any real distinction is purely tactical/motivated/arbitrary – at the very least that the overlaps between ‘cybernetics’, ‘systems thinking’, and ‘complexity science’ are so massive – and have such shared routes – that, in order to carve any of them out as individual territories, you have to artificially apportion stuff that rightfully belongs to one or both to the other… if you see what I mean! Remember that I am trying to think specifically about *methods*.
Each has some elements which are of course distinct – agent-based modelling seems like the best candidate in ‘complexity’ – and certainly specific *applications* of mathematical techniques – and maybe some stuff around network modelling?
Here are the threads:
https://www.facebook.com/groups/774241602654986/2083395748406225/?comment_id=2083432968402503¬if_id=1549119341857033¬if_t=group_comment&ref=notif
https://www.facebook.com/groups/2391509563/10156785597314564/?comment_id=10156785650364564¬if_id=1549119885345223¬if_t=group_comment&ref=notif
https://www.facebook.com/groups/1698754760335916/2275321949345858/?comment_id=2275328329345220¬if_id=1549119105597714¬if_t=group_comment&ref=notif
There will now follow a lot of posts of interesting approaches unearthed!
seeking amazing speakers in London and Manchester for Systems and Complexity in Organisation
I’m a non-exec Director of www.scio.org.uk – systems and complexity in organisation – and we run four open days a year, with four systems-related speakers at each one.
We would love to have more speakers (and attendees) related to systems change, regenerative agriculture, sustainability, philanthropy, international development etc. We’d also love to have more contributors from sectors we hear less from – health, education at all levels, social care, arts, charities
Can you recommend any speakers – would you be interested to speak? Reply here or drop me a line at ben.taylor@scio.org.uk
Cheers!
Benjamin
Definitions of systems and systems thinking
There are no simple definitions of systems and systems thinking (Monat & Gannon 2015) that are sufficiently rich to clarify what they are essentially about. So instead, I will offer a circumscriptive definition in three parts and add a small concept map to go with it.
Systems thinking …. is the selection and application of more or less general systems methods or systemic problem solving tools to examine, debate, model, and modify systems structures, which underlie systems behavior. Systems thinking serves to identify and improve or understand the system behavior of a broad range of open systems.
Open systems … consist of sets of at least two parts, elements, components or subsystems that are characterized by at least one interrelationship. The distinction between an open system and its environment is conceptualized by the system boundary. Open systems interact with their environment by receiving…
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Requisiteagility – Requisite Agility UnSymposium, 9-10 Feb 2019, New York City
Well, I am bemused and mystified how I managed not to see this until a week before the event! And I’m intrigued. The combination of Requisite Organisation, Viable Systems Model, and Agile is a powerful one. And of course each of them is very different, though each has been proven to be valuable in practice, when done well.
A few thoughts:
- I have wondered for a while about when and how agile would be absorbed into the deeper theoretical tradition of management and systems thinking (in a meaningful/useful way, I don’t mean McKinsey or HBR), but it has largely remained focused on (a) practice and (b) competing brands and commercial offers to date.
- This is an unconference (plus speakers), but ?every speaker is listed with their own branded ‘offer’, which might rather illustrate the problem.
- I can’t help thinking that Viable Systems Model might have come in there later because someone said ‘oi! there’s a theory which focuses entirely on viability as requisite agility, you know’. I would have said that the use of ‘requisite’ and the entire thrust of the theories are ‘orthogonal’ between RO and VSM – though I explicitly merge them (or at least learning from Elliot Jacques through various routes), and Luc Hoebeke has done it theoretically as well (shame he’s not speaking!)
- These kind of blendings can be the most sterile, or the most fertile, depending on how well the incommensurability of different traditions can be addressed!
Charter: https://requisiteagility.org/wp-content/uploads/2018/10/racharter.pdf
In the about page, it says:
Provenance of RA
The idea of Requisite Agility (RA) was born in 2009, when Amit Arora was in Russia for a software development project based on the Requisite Organization (RO) theory. This was the first time he was introduced to RO and its concepts, denoting the start of a journey of contextualizing the Requisite Organization concepts with the concepts of agile/agility.
**
From 2014 onwards, in collaboration with Steve Clement and many other contributors (see the list below), the idea of Requisite Agility has gradually evolved into a coherent conceptual foundation that recasts many RO concepts into today’s complex and agile context, provides a well-founded scaffolding to design and implement business agility, and is agnostic to any best practice method or framework.
As of the end of 2018, the RA concept is ready for a major leap: collaborative elaboration of the theory, tenets and terminology. To this end, an UnSymposium will be held in early 2019 to get together the harbingers, proponents and future practitioners of RA. The results of the RA community will be released as creative commons open content for anyone to apply.
Main page, source: Requisiteagility – Requisite Agility UnSymposium
About RA
Requisite Agility™ (RA) refers to the organization design principles, patterns and practices that enable the organization to effectively adapt, responsively or preemptively, to changes in its environment. It provides a constructive scaffolding that helps the organization sense these changes, make sense of them, and act accordingly, while learning from the experience.
RA is agnostic to any specific agile methodology, best practice, or framework. Drawing on the systems and complexity theories, it entails theoretically informed and organization-specific diagnosis, analysis, design and implementation of organizational structures, processes and practices that are adaptive in their context.
RA operationalizes key Agile Properties

Driving Questions
Systems Design: Because everything* is systems – Alëna Louguina
Source: Systems Design: Because everything* is systems – Shopify UX
Systems Design: Because everything* is systems

The Warning of the Doorknob
All good product and service design begins with systems analysis. We are tasked with understanding not just one system that the product will be composed of (e.g. electrical, information, mechanical, hydraulic, etc.) or is designed for (transportation, manufacturing, social, natural, etc.) but many. Systems are fascinating but also a great source of anxiety, because they are uncertain, full of complex interpersonal relationships, indefinite, and difficult.
This anxiety is rooted in the hierarchical nature of systems and moves in two directions, infinite escalation and regression.

John P. Eberhard, a neuroscientist who studies brain and how it experiences built environments, named this dichotomy of complexities “the warning of the doorknob”, described by Ed Yourdon in his book ‘Just Enough Structured Analysis’:
This has been my experience in Washington when I had money to give away. If I gave a contract to a designer and said, “The doorknob to my office doesn’t have much imagination, much design content. Will you design me a new doorknob?” He would say “Yes,” and after we establish a price he goes away. A week later he comes back and says, “Mr. Eberhard, I’ve been thinking about that doorknob. First, we ought to ask ourselves whether a doorknob is the best way of opening and closing a door.” I say, “Fine, I believe in imagination, go to it.” He comes back later and says, “You know, I’ve been thinking about your problem, and the only reason you want a doorknob is you presume you want a door to your office. Are you sure that a door is the best way of controlling egress, exit, and privacy?”
“No, I’m not sure at all.” “Well I want to worry about that problem.” He comes back a week later and says, “The only reason we have to worry about the aperture problem is that you insist on having four walls around your office. Are you sure that is the best way of organizing this space for the kind of work you do as a bureaucrat?” I say, “No, I’m not sure at all.” Well, this escalates until (and this has literally happened in two contracts, although not through this exact process) our physical designer comes back with a very serious face. “Mr. Eberhard, we have to decide whether capitalistic democracy is the best way to organize our country before I can possibly attack your problem.”
On the other hand is the problem of infinite regression. If this man faced with the design of the doorknob had say, “Wait. Before I worry about the doorknob, I want to study the shape of man’s hand and what man is capable of doing with it,” I would say, “Fine.” He would come back and say, “The more I thought about it, there’s a fit problem. What I want to study first is how metal is formed, what the technologies are for making things with metal in order that I can know what the real parameters are for fitting the hand.” “Fine.” But then he says, “You know I’ve been looking at metal-forming and it all depends on metallurgical properties. I really want to spend three or four months looking at metallurgy so that I can understand the problem better.” “Fine.” After three months, he’ll come back and say, “Mr. Eberhard, the more I look at metallurgy, the more I realize that it is atomic structure that’s really at the heart of this problem.” And so, our physical designer is in atomic physics from the doorknob.
That is one of our anxieties, the hierarchical nature of complexity.

Now we must not forget that Dr. Eberhard had his own complexity to deal with. From the perspective of escalation, he moves from being an H. sapiens in an urban habitat to a temperate climate zone of New York to our planet’s biosphere. And in another direction, Dr. Eberhard is composed of …

All these systems talk to each other. While Dr. Eberhard is dealing with his door handle, environmental agencies are trying to figure out how to revert the harmful effects of out-of-control manufacturing systems on Earth’s biosphere. And atoms of a door handle are peacefully swerving in the void along with the atoms of Dr. Eberhard’s hand.
Bridging the Distance Between Fundamental Rules and Final Phenomena
Years ago, still a design student, I peeked into John Buschek’s cozy office on the grounds of a project I was working on and ended up in one of his remarkably comfortable chairs, being questioned about the entire purpose of my project. He concluded:
“Designers often jump to a solution before ever asking a question of why the solution is needed in the first place. Don’t worry, scientists do it too.”
And he isn’t talking about a product or service, but more about the fundamental question of systems surrounding it. As a chemist, John engaged in many well funded endeavours of “creating chemistry for the sake of creating chemistry”. He called it ‘mundane science’. There is an excellent paper by Daniel Kammen and Michael Dove titled The Virtues of Mundane Science:
The prejudice against research on mundane topics has created a conceptual “cordon sanitaire” within many disciplines. In energy and development research, it appears as a disproportionate focus on advanced combustion systems, commercial fuels, and large centralized power facilities, even though more than 3 billion people rely on wood, charcoal, and other biomass fuels for the bulk of their energy needs.
Major obstacles to developing sound environmental practices are not principally technological. Instead, the primary stumbling block is the lack of integrative approaches to complex systems and problems. A mundane example — efforts to improve wood and charcoal burning cookstoves — illustrates the important advances that are possible from integrating scientific, engineering, and social science research with very practical implementation programs.
Here it is: lack of integrative approaches to complex systems and problems. There is a great video narrated by Richard Feynman, titled Curiosity:
My favourite phrase from the video:
“So much distance between fundamental rules and final phenomena.”
We all know about emergent behaviour, spontaneous organization, and collective decisions. But what do we really know about the rich web of interactions within all these phenomena?
John Holland once elegantly compared economic system to a natural one:
There is no master neuron in the brain nor is there a master cell within a developing embryo. If there is to be any coherent behaviour in the system, it has to arise from competition and cooperation among the agents themselves.
This is quite true in the economy as well: regardless of how much CEOs of companies are trying to cope with a stubborn recession, the overall behaviour of the economy is still the result of myriad economic decisions made every day by millions of individual people.
More importantly, it’s all about never-ending reshuffling and rearrangement of the said neurons and cells to ensure the resiliency of the system. Thus, an integrative approach and continuous questioning might open a designer’s mind to the world of heavy, complex problems that need solving; beyond safe, easily-accessible, peddled, and ubiquitous challenges that are so tempting to quickly tackle.
And the best part, the more you dive into a complex problem the more you start connecting the dots, branching out, and converging again. This brings about a whole array of inspirations and allows a designer to truly understand the space they are designing for, instead of generalizing and assuming its purpose and function. And, of course, the more we learn, the more humble we become. And isn’t that what designer should strive to be? As Richard Dawkins put it:
The world and the universe is an extremely beautiful place, and the more we understand about it the more beautiful does it appear. It is an immensely exciting experience to be born in the world, born in the universe, and look around you and realize that before you die you have the opportunity of understanding an immense amount about that world and about that universe and about life and about why we’re here.
We have the opportunity of understanding far, far more than any of our predecessors ever. That is such an exciting possibility, it would be such a shame to blow it and end your life not having understood what there is to understand.
After publishing this article, Timi Olotu wrote a thoughtful comment that turned out to be an eloquent summary to my often serpentine thoughts. So, I’m adding it here:
Your discussion of the anxiety attached with the concepts of infinite regression and escalation is basically a physical exploration of the metaphysical concept of an “existential crisis”.
An existential crisis, in other words, is a self-aware “system” attempting to identify which part of the existential spectrum it uniquely occupies… but failing and getting lost in either infinite regression or escalation.We identify systems as occupying a unique part of the existential spectrum based on where one system (or series of systems) ends and where another begins — i.e. part of knowing that a rock is a rock comes from knowing that it is not the same as sand (or some other thing).
This logic (in small doses) is also essential when solving complex problems of any kind […]. It’s a reminder for designers to neither live in blissful ignorance nor suffer a “design existential crisis” — to be aware of the complexity of systems but not get lost in them.
Finally, the art of murmuration to illustrate the difference between non-system and a system!
The best part about systems is, despite their complexity, they can be understood. Stay tuned for the follow-up article that will introduce methods of systems analysis and design.
Logical Levels
Source: Logical Levels
Logical Levels model
The concept of logical levels of learning and change was initially formulated as a mechanism in the behavioural sciences by anthropologist Gregory Bateson, based on the work of Bertrand Russell in logic and mathematics. Robert Dilts first became acquainted with the notion of different logical types and levels of learning, change and communication whilst attending Gregory Bateson’s ecology of mind class at the University of California at Santa Cruz in 1976. Reflecting back, Robert says of attending Bateson’s classes, “These were one of the most transformative experiences of my life. I was sitting in his class, listening to his deep voice and distinctive Cambridge accent, which sounded to me like the voice of wisdom.”
The term logical levels, was adapted by Dilts from Bateson’s work and refers to a hierarchy of levels of processes within an individual or group. The function in each level is to synthesise, organise and direct the interactions on the levels below it. Something on an upper level could “radiate” downward, facilitating change on the lower levels.Something on a low-level could, but would not necessarily, effect the upper levels.
The life of people in any system, and indeed the life of the system itself, can be described and understood on a number of different levels: environment, behaviour, capabilities, values and beliefs, identity and purpose.
Environment
At the most basic level, managing the process of change must address the environment in which a system and its members act and interact. The environment refers to everything outside yourself: the place in which you work, the economy, people around you: your business, your friends and family, your customers. It’s about finding the right time and the right place. Environmental factors determine the context and constraints under which people operate. An organisation’s environment, for instance, is made up of such things as the geographical locations of its operations, the building and facilities which define the ‘workplace’, office and factory design, etc. In addition to the influence these environmental factors may have on people within the organisation, one can also examine the influence and impact the people within an organisation have upon their environment, and what products or creations they bring to their environment.
Behaviour
At another level, we can examine the specific behaviours and actions of a group or individual i.e. what the person or organisation does within the environment. Behaviour is all about what you actually say and do, what you consciously get up to. It is part of what can be seen and heard by other people. What are the particular patterns of work, interaction and communication? On an organisational level, behaviours may be defined in terms of general procedures. On the individual level, behaviours take the form of specific work routines, working habits or job related activities.
Capabilities
Another level of process involves the strategies, skills and capabilities by which the organisation or individual selects and directs actions within their environment i.e. how they generate and guide their behaviours within a particular context. Capabilities are your talents and skills and are increasingly becoming known as competencies. They are the resources that you have available to you. These range from behaviours that you do without any seemingly conscious effort e.g. walking and talking, to skills that you’ve learned more consciously, e.g. riding a bike or working a computer. Capabilities include cognitive strategies and skills such as learning, memory, decision-making and creativity, which facilitate the performance of a particular behaviour or task. At an organisational level, capabilities relate to the infrastructure that is available to support communication, innovation, planning and decision-making between members of the organisation.
Beliefs and values
Our beliefs and values provide the reinforcement that support or inhibit particular capabilities and behaviour. Beliefs determine how events are given meaning and are at the core of judgement and culture. These are the fundamental principles that shape our actions. This level contains statements about yourself, other people and situations that you hold to be true. They are emotionally held views not based on facts. We all hold numerous beliefs and values, some of which are known to us and others which sit outside of our consciousness. Sometimes our beliefs reveal themselves to us when we talk to someone who holds a different belief and we find ourselves drawn to defend our beliefs.
Values are the criteria against which you make decisions. These are qualities that you hold to be important to you in the way you live your life. They are also the rules that keep us on the socially acceptable road.
Beliefs and values are unique to each individual. We may also place a different priority on a belief or a value to our friends, family or work colleagues. Organisations also have beliefs and values, and seek to win over employees to share these beliefs and values.
Identity
Values and beliefs support the individual’s or organisation’s sense of identity i.e. the who behind the why, how, what, where and when. Identity describes your sense of who you are and contains statements that describe how you think of yourself as a person. Our identity is like the trunk of the tree – it is the core of our being. Internally our identities are supported by personal values, beliefs and capabilities as well as our physical being and our environment. Externally, our identity is expressed through our participation in the larger systems in which we participate: our family, professional relationships, community and a global system of which we are a member. A person’s identity is separate from their behaviour, you are more than what you do. For a company the mission statement seeks to define the identity of the organisation.
Purpose
This is the final level that is sometimes referred to as a spiritual level. This term can have a religious connotation but this is not the only meaning here. This level has to do with people’s perceptions of the larger systems to which they belong and within which they participate. These perceptions relate to a person’s sense of, for whom and for what, their actions are directed, providing a sense of meaning and purpose for their actions, capabilities, beliefs and identity.
This level leads organisations to define their vision and ambition; their raison d’être.
In summary, the process of managing change must address several levels or factors:
- Environmental factors determine the external opportunities or constraints that individuals and organisations must recognise and react to. They involve considering where and when the change is occurring.
- Behavioural factors are the specific action steps taken in order to meet the desired state. They involve what, specifically, must be done or accomplished in order to appropriately manage change.
- Capabilities relates to the mental maps, plans or strategies necessary for managing change. They direct how actions are selected and monitored.
- Beliefs and values provide the reinforcement that supports or inhibits particular capabilities and actions. They relate to why a particular path is taken and the deeper motivations that drive people to act or persevere.
- Identity factors relate to people’s sense of their role or mission. These factors are a function of who a person or group perceives themselves to be.
- Purpose relates to people’s view of the larger system of which they are part. These factors involve for whom and for what a particular action step or path has been taken.
It is often easier to make change at the lower levels on the diagram than at higher levels. The value of the model is that it provides a structured approach to help understand what is happening to an individual, a team or an organisation. A key aspect of the model is it looks at the level of congruence an individual, team or organisation have across all the logical levels. When an individual is aligned, they are more likely to be described as comfortable in their own skin, charismatic, powerful and are true to themselves. Organisations are more likely to be described as authentic, cohesive and consistent. Knowing which levels are out of alignment provides an individual or an organisation with the best way forward for change.
In Studio – Helsinki Design Lab – recipes for systemic change (free 336-page book)
Helsinki Design Lab helps government see the ‘architecture of problems.’ We assist decision-makers to view challenges from a big-picture perspective, and provide guidance toward more complete solutions that consider all aspects of a problem. Our mission is to advance this way of working. We call it strategic design.
Source: In Studio – Helsinki Design Lab
pdf [Creative Commons Attribution-NonCommercial-ShareAlike 2.0 licence.]
Click to access In_Studio-Recipes_for_Systemic_Change.pdf
In Studio: Recipes for Systemic change
This book explores the HDL Studio Model, a unique way of bringing together the right people, a carefully framed problem, a supportive place, and an open-ended process to craft an integrated vision and sketch the pathway towards strategic improvement. It’s particularly geared towards problems that have no single owner.
It includes an introduction to Strategic Design, a “how-to” manual for organizing Studios, and three practical examples of what an HDL Studio looks like in action. Geoff Mulgan, CEO of NESTA, has written the foreword and Mikko Kosonen, President of Sitra, contributed the afterword.
Release | Media effects | Special Issue of Cybernetics and Human Knowing
Heidingsfelder, M. and Roth, S. (2018) Media effects. Special Issue of Cybernetics and Human Knowing, Vol. 25 No. 4.
Contents
Foreword: Media Effects (M. Heidingsfelder)
Contingency Alert: Editorial Note on Necessary and Impossible Media (S. Roth)
Articles
The Mediality of Looseness (U. Stäheli)
Listening to Media in Cultural Theory, Sociology, and Management (D. Baecker)
Digitality with a Medium of Communication: With a Focus on Organizations as Systems of Decision-Making (A. Brosziewski)
New Media and Socio-Cultural Formations (J. Fuhse)
Regular Features
Column: Virtual Logic-The Erdos Machine (L. Kauffman)
Photo credit: Stefan M. Seydel, dfdu.org.
Productive Organisational Paradoxes – Ivo Velitchkov
This was Ivo’s presentation at the SCiO open event in London last week (www.scio.org.uk/events for more) – one of those real brain workouts which he’s so good at. I’m not sure how well others can follow from the slides, but depending on how the edit comes out, SCiO members and/or those following his blog – I think http://www.strategicstructures.com/ but maybe https://eavoices.com/author/ivo/
Also well worth a look from the Strategic Structures website is
What can Social Systems Theory bring to the VSM?
In 2015, when the Metaphorum was in Hull, I tried to kick off a discussion about potential contributions from cognitive science, and particularly from the Enactive school. I shared some insights and hinted at other possibilities. This year the Metaphorum conference was in Germany for the first time. It was organised by Mark Lambertz and hosted by Sipgate in Düsseldorf. I saw in the fact that the Metaphorum was in Germany a good opportunity to suggest another combination, this time with the Social Systems Theory of Niklas Luhmann.
These are the slides from my talk and here you can also watch them with all animations.
Related posts:
Power of Community Summit Feb 1-10, 2019
Interesting speakers
Source: Power of Community Summit Feb 1-10, 2019

Power of Community Summit
Climate Change and Consciousness
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When You Meet the Monster, Anoint Its Feet by Bayo Akomolafe — Emergence Magazine
I thought this was very interesting
Source: When You Meet the Monster, Anoint Its Feet — Emergence Magazine

ESSAY
When You Meet the Monster, Anoint Its Feet
In the age of the Anthropocene and entrenched politics of whiteness, Bayo Akomolafe brings us face-to-face with our own unresolved ancestry, as it becomes more and more apparent that we are completely entwined with each other and the natural world.
A stunning invitation is in the air, urging us to rethink ourselves, our bodies, our hopes for justice, and how we respond to the politics of whiteness. In these times of painful displacements, unavertable crises, and unexpected entanglements (the Anthropocene), the logic of race and identity collides with genetic technologies and splinters into new emergent insights into how bodies come to be enfleshed—granting us hope for becoming otherwise.
The story I write here might have a neat beginning and an ending, but this story is really about the middle-ing spacethat gives birth to beginnings and endings. To be sure, it is about a good number of things—about race and racism, about black bodies, about the exterminations perpetrated in the name of superiority, about healing and decolonization, and about technology. And yet, it is at heart a letter about middles—not mathematical middles or the morality of balance in the way we often strive to find the golden mean between two extremes, but about how things interpenetrate each other, and how that leads us to interesting places. The middle I speak of is not halfway between two poles; it is a porousness that mocks the very idea of separation.
This is a tale about the brilliant betweenness that defeats everything, corrodes every boundary, spills through marked territory, and crosses out every confident line. The Yolngu people of Arnhem Land in northeastern Australia have a name for this “brilliance”: bir’yun (meaning “brilliance” or “shimmer”). It refers to a Yolngu aesthetic that is effected in paintings by crosshatching patterns and lines, which leave an optical impression of a shimmer. Bir’yun, more than just an artistic technique, speaks of ancestry cutting into the present, identities queered, tongues rendered unintelligible, and im/possibilities opening up. Bir’yun speaks of middles. And everything dies and begins in the middle.
When I was a child, I heard a story of beginnings from our Yoruba traditions about how the world came to be: they say there were once primal seas and raging waters below—and no land mass to counter their fury. Up above, the sky churned with the politics of a restless pantheon of Òrìshàs, non-human mythical beings who lived before humans. Olókun ruled the waters, and Olodumare—supreme above all—ruled the heavens. Between them, there was nothing. But, you see, “nothing” is never really as empty as some might think.
Obatálá, son of Olodumare—curious, restless, and uneasy with endless bliss—was inspired to create a people and the land they would rest on. With Olodumare’s blessings, he took leave of heavenly places and made his way down to the waters to begin his task. Just before he made his way, Obatálá consulted with Orunmila, Òrìshà of prophecy, who told him that he must prepare a chain of gold; gather palm nuts, with which he might hold the sand to be thrown over the waters; and obtain a sacred egg which contained a bird that would come in handy along the way. Obatálá did as instructed and secured these items. At the moment of departure, he fastened the golden chain to the sky and climbed down.
Can you take an instant to visualize this event? Imagine it for a moment: sky and swirling blue traversed by a shimmering chain that irrevocably and rudely links the heavens to the terrestrial, the divine to the mundane, the transcendent to the immanent, the infinite to the finite, nature to culture, masculine to feminine, beginnings to endings, unsettling both, re-configuring both just as well. In a sense, Obatálá’s epic adventure recreated everything.
On Obatálá’s golden chain, poised in the grand between, hangs not just a riveting account of beginnings-that-are-not-originary (or “middles”), but a figure of shocking intersections or transversal happenings—a figure that is particularly alive and much needed right now. This chain—like Obatálá’s golden chain—disturbs everything, remakes everything … rethinks everything. Its helixes weave together new practices that open up new considerations about how to ask questions related to identity and racial justice. I speak of deoxyribonucleic acid, or DNA.
Continues in source: When You Meet the Monster, Anoint Its Feet — Emergence Magazine
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Hillary Keeney and Bradford Keeney would like to express their gratitude and appreciation to our colleagues in Mexico for their support of this work. In particular Pedro Vargas Avalos and Clara Haydee Solis Ponce, who with their colleagues have sponsored our teaching at the Department of Clinical Psychology, National University of Mexico (UNAM), Zaragoza, and Juan Carlos García and Sylvia Arce, who have sponsored our teaching at Etfasis: Institute of Systemic Family Therapy. It was during our seminars there that many of the ideas in this book were developed.
Ronald Chenail would like to thank President George L. Hanbury II and Nova Southeastern University for supporting The Qualitative Report; Hillary and Brad Keeney for their continuing guidance and encouragement; Lydia Acosta, Michele Gibney, and Cheryl Ann Peltier-Davis for launching NSU Works and helping with our first book development and release; Melissa Rosen for her copyediting and graphics skills; Adam Rosenthal for his leadership in making TQR Books a reality; and Jan Chenail, my late wife, for making me a better writer, husband, father, and friend.
Copyright 2014: Hillary Keeney, Bradford Keeney, Ronald Chenail and Nova Southeastern University