Source: Gordon Pask’s Adaptive Teaching Machines

Continues in source…

Source: Teaching Machines: An American Story (And the Case for Gordon Pask)

Source: Dancing with systems, uncertainty & positive emergence

Dancing with systems & designing for positive emergence

Daniel Christian Wahl

Apr 16

This webinar was hosted by Deeanna Burleson, Ph.D. in the ‘Topics in the field of systems science’ series intended as a contribution to the International Society for Systems Science (here is a link to the original announcement of the webinar).

The webinar (video link below) starts with a 45 minute presentation offering reflections on nearly 20 years of experience in trying to apply whole systems thinking to the field of design for sustainability and more recently regenerative development practice.

I explore the limitations of a quantity focussed science and the need for a new ‘science of qualities’. I explore how the work and thinking of Donella Meadows evolved from ‘leverage points 1.0’ to ‘leverage points 2.0’ and on to ‘Dancing with systems. Nora Bateson’s ‘warm data’ approach is mentioned as a related example of this relationships and qualities focussed work with systems from the inside. Katia Laszlo’s framing from ‘systems thinking to systems being’ is also briefly addressed.

I go on to explore some of the most common mistakes made in intervening in complex adaptive systems and highlight the need for embracing the fundamental unpredictability of such systems as we move from being detached observers to being engaged participants of such systems. In this context I also speak to the power that lies in asking the right questions and asking questions rather than offering a list of principles to follow.

To ground these theoretical considerations and paradigmatic shifts in a practical example, I offer a brief summary of my work for Gaia Education on the ‘SDG Flashcards’, the ‘SDG Project Canvas’, the ‘SDG Training of Multipliers’ and the ‘Multipliers Handbook’ as an example of ‘designing for positive emergence’ and taking Bucky Fuller’s advice that “to change the way people think, don’t tell them what to think, give them a tool the use of which will change the way they think”. The flashcards by Gaia Education and UNESCO have been used successfully on 5 continents and translated into 6 languages.

… after the presentation there is another 45 minuter conversation or Q&A session that addresses a wide range of topics related to ‘Designing Regenerative Culture’ … enjoy and share!

You can watch the slides with animations here: http://www.strategicstructures.com/?p=1511

Ivo Velitchkov

Independent Management Consultant

Source: CECAN Webinar: The Human, Learning, Systems approach to managing in complexity | CECAN

 

CECAN Webinar: The Human, Learning, Systems approach to managing in complexity

 

Tuesday 1st October 2019, 13:00 – 14:00 BST

Presenter: Dr Toby Lowe, Senior Lecturer in Public Leadership and Management, Newcastle Business School 

 

You are warmly invited to join us for the following CECAN Webinar…

 

Webinar Overview: 

The webinar views the challenge of creating complexity-informed evaluation by seeing it as a public management challenge. How can public management adopt a more complexity-informed approach? The session will outline an emerging complexity-informed approach to public management: the Human, Learning, Systems (HLS) approach. The HLS approach involves public services responding to the variety of human need through bespoke service provision, using learning as the engine for performance improvement and stewarding the health of the systems which produce social outcomes.

 

Human

One of the three key tasks of managing work in an HLS way (including funding and commissioning of work) means creating the conditions in which people can build effective human relationships.

This means understanding human variety, using empathy to understand the lives of others, recognising people’s strengths, and trusting those who do the work. Variety, Empathy, Strengths and Trust (VEST).

 

Learning

In complex environments people are required to learn continuously in order to adapt to the dynamic, ever-changing nature of the work. In complex environments, there is no simple interventions which “works” to tackle a problem. “What works” is an on-going process of learning and adaptation.

It is the job of managers to enable staff to learn continuously as the tool for performance improvement. This means using measures to learn, not for reward/punishment. It means creating the conditions where people can be honest about their mistakes and uncertainties. It means creating reflective practice environments between and across peer groups.

This requires funders/commissioners to fund for learning and adaptation, not for “results”.

 

Systems

The outcomes we care about are not delivered by organisations. They are produced by whole systems – by hundreds of different factors working together. The final job of managers is therefore to act as Systems Stewards – to enable actors in the system to co-ordinate and collaborate effectively  – because that it was will enable positive outcomes to emerge.

 

The HLS approach has recently been outlined in this report.

 

Presenter Biography (Dr Toby Lowe, Senior Lecturer in Public Leadership and Management, Newcastle Business School):  

My purpose as an academic is to help improve the funding, commissioning and performance management of social interventions (across the public, private and voluntary sectors). My research team has used complexity theory to create a critique of New Public Management approaches, particularly highlighting the problems created by attempts to use Outcome-Based Performance Management (e.g. Payment by Results) in complex environments.

We have also developed a new complexity-informed paradigm for the funding, commissioning and performance management of social interventions, and are undertaking action research programmes with public and voluntary sector funders and delivery organisations to explore how this paradigm is implemented in practice, and to support the development of a Community of Practice around this new paradigm.

My team is also conducting working as a Learning Partner for the Lankelly Chase Foundation’s inquiry into place-based system change. In this context we are exploring how learning functions as a mechanism for system change.

I began my academic life as a political philosopher (my PhD is in the concept of community in political theory). After completing my PhD I worked in both the public and voluntary sectors for 15 years. My previous job before returning to academia was as Chief Executive of Helix Arts, a North East charity specialising in participatory arts practice with marginalised groups.

From 2015-2018 I worked at Newcastle University Business School, and Open Lab. In this context I also worked with PhD students at Open Lab exploring the role of digital technology in enabling people and organisations to reflect on their performance, and to contribute to learning in complex systems.

 

How to Join: 

This talk will take place via a Zoom Webinar – please click here to register for a place.

After registering, you will receive a confirmation email containing information about joining the webinar. In case you are unable to attend, a recording of the webinar will be uploaded to our website following the event.

 

 

More information:

This event is currently open to all

Contact: cecan@surrey.ac.uk

Start date

Tue, 01/10/2019 – 13:00

End date

Tue, 01/10/2019 – 14:00

Systems theory-based construct for identifying metasystem pathologies for complex system governance

PhD Thesis

August 2015

Polinpapilinho F. Katina

Source: Systems theory-based construct for identifying metasystem pathologies for complex system governance

pdf direct link https://www.researchgate.net/profile/Polinpapilinho_Katina/publication/323202439_Systems_theory-based_construct_for_identifying_metasystem_pathologies_for_complex_system_governance/links/5b365aa0aca2720785f69eff/Systems-theory-based-construct-for-identifying-metasystem-pathologies-for-complex-system-governance.pdf

Shorter article

Click to access fd7820cc84838274dd93233fbea1cd1310cd.pdf

Can’t believe I haven’t linked this before?

Source: Encyclopaedia Autopoietica: Autopoiesis & Enaction Compendium

e.g.

autopoiesis

1.

The theoretical construct definitive of the manner of operation of that class of systems that includes living systems. This term, combined from the Greek auto- (self) and poiesis(creation/production), was coined by Maturana in (approximately) 1972 (Cf. Maturana & Varela, 1980, p. xvii). Often loosely translated as ‘self-creation’ or ‘self-production’, the term connotes the process or dynamic by which an autopoietic machine / system maintains its autopoietic organization (via intrinsic processes of production of components realizing this particular organization). More specifically, autopoiesis is attributed to a machine (delineated as a a network of processes) which through that network of processes produces the components that:

“(1) through their interactions and transformations continuously regenerate and realize the network of processes (relations) that produced them; and(2) constitute it (the machine) as a concrete unity in the space in which they [the components] exist by specifying the topological domain of its realization as such a network.”

(Varela, 1979, p. 13)

In the primary literature, autopoiesis is not directly defined as a process. Instead it is defined indirectly, on the basis of how an ‘autopoietic machine’ operates. There are, in fact, very few instances in the primary literature where ‘autopoiesis’ is substantively treated in and of itself, and then only as a process characteristic of ‘self-production’ or ‘homeostatic organization’ — constructs themselves framed mechanicistically with respect to the subject system’s architectonics. For example, Varela (1979, pp. 24-26) comes closest to addressing ‘autopoiesis’ directly in the course of discussing productions of relations in a given system:

“What makes this system a unity with identity and individuality is that all the relations of production are coordinated in a system describable as having an invariant organization. In such a system any deformation at any place is compensated for …by keeping its organization constant as defined by the relation of the productions that constitute autopoiesis. The only thing that defines the cell as a unity (as an individual) is its autopoiesis, and thus, the only restriction put on the existence of the cell is the maintenance of autopoiesis.”(Varela, 1979, p. 26, emphasis in the original)

“…[A]utopoiesis may arise in a molecular system if the relations of production are concatenated in such a way that they produce components specifying the system as a unity that exists only while it is actively produced by such concatenation of processes. This is to say that autopoiesis arises in a molecular system only when the relation that concatenates these relations is produced and maintained constant through the production of the molecular components that constitute the system through this concatenation.”

(Varela, 1979, pp. 26-27)

NOTE: Given the above distinctions and qualifications about the nature and origin of the construct ‘autopoiesis’, the details on what makes a composite unity (system) ‘autopoietic’ are therefore to be found under the entries for autopoietic machine and autopoietic organization.

The strict, though indirect, definition of autopoiesis proposed in the early papers was intended to provide a basis for overcoming vague or problematical characterizations of living systems — particularly those which represented vitalistic explanation of biological phenomena. As Maturana (1980a, p. 45) put it, the construct of autopoiesis:

“…resulted from the direct attempt … to provide a complete characterization of the organization that makes living systems self-contained autonomous unities, and that makes explicit the relations among their components which must remain invariant under a continuous structural transformation and material turnover.”

This passage reinforces the viewpoint that it is the constitutive organization of an autopoietic system which is primary in delineating autopoiesis. This is reflected even in the less formal popular account given in The Tree of Knowledge (Maturana & Varela, 1987, 1992):

“When we speak of living beings, we presuppose something in common between them; otherwise we wouldn’t put them in the same class we designate with the name ‘living.’ What has not been said, however, is: what is the organization that defines them as a class? Our proposition is that living beings are characterized in that, literally, they are continually self-producing. We indicate this process when we call the organization that defined them an autopoietic organization.“(Maturana & Varela, 1992, p. 43, emphasis added)

Having said that, Maturana and Varela proceed (as they have consistently done in the more formal literature) to delineate the autopoietic organization as the basis for ‘indicating’ the process of ‘autopoiesis.’

These last quotations illustrate a point which has proven somewhat problematical over the years. As mentioned at the outset, ‘autopoiesis’ has in fact been delineated and formally defined in terms of the constitution and operational character of an autopoietic machine or system. This definitional approach was entirely consistent with the mechanicistic perspective from which Maturana and Varela initially proceeded. To have invoked an ephemeral ‘autopoiesis’ (e.g., as a processual or qualitative referent) would have arguably entailed sliding into the sort of vitalistic explanation which they explicitly opposed and stringently avoided.

In other words, ‘autopoiesis’ is an abstract construct known solely in relation to a machine / system of a particular constitution which maintains its key constitutive character over time. Strictly speaking, autopoiesis has not been positively defined as a type of process in and of itself, even though it is clear in the context of its primary literature (e.g., Maturana & Varela, 1980) that it is the dynamic or process evidenced by, and reciprocally preservative of, the autopoietic organization / autopoietic machine. Nonetheless, it became common practice (even on occasion by Maturana and Varela themselves) to allude to ‘autopoiesis’ as a rhetorical shorthand connoting (in terms of process) the constitutive and operational details of a particular system. This is most evident when addressing the dynamics of an autopoietic system — i.e., when the processes manifest in the autopoietic network comprise the referential foreground, and the mechanics of the network itself are relegated to the background.

Given the above-cited conditions, it is possibly understandable, though definitely somewhat ironic, that this indirectly- or allusively-defined shorthand term should become the de facto label for the essence of Maturana and Varela’s work, as well as a common label for that work itself (Cf. 2. below). So long as such invocations retain (or at least can be linked to) the sort of mechanicistic context in which the process ‘autopoiesis’ is definitively framed, this is not problematical. What is problematical is explanatory invocation (and reliance upon) the process or dynamic of ‘autopoiesis’ absent this context. To invoke ‘autopoiesis’ (e.g., as ‘self-production’) without concomitantly explaining the constitutive elements of the system(s) for which such invocation is made, is to deny any basis for evaluating the applicability of the construct (as it was defined originally). The most well-known example of such an invocation would be that of German sociologist Niklas Luhmann, who adopted ‘autopoiesis’ as a processual construct in analyzing social systems, yet never (to date) bothered to explain what in his view are the key constitutive elements (e.g., ‘organization’, ‘structure’) by which such an application might be assessed in terms of Maturana and Varela’s clear-cut definitional criteria.

The explanatory risk in invoking ‘autopoiesis’ absent attention to the machine / system manifesting it has two distinguishable (but admittedly intertwined) components. The first is that an observer may simplistically project the feature ‘autopoiesis’ onto a unity with which she has insufficient or imperfect observational engagement upon which to base its ascription. Phrased another way, stripping the processual construct away from the machine manifesting it opens the possibility of its mistaken attribution to something only partially or indirectly observed. Varela (1979) provides some illustration for this type of risk in writing of recognizing an autopoietic system (as distinct from autonomous systems in general):

“In general, the actual recognition of an autopoietic system poses a cognitive problem that has to do both with the capacity of the observer to recognize the relations that define the system as a unity, and with his capacity to distinguish the boundaries that delimit this unity in the space in which it is realized (his criteria of distinction). Since it is a defining feature of an autopoietic system that it should specify its own boundaries, a proper recognition of an autopoietic system as a unity requires that the observer perform an operation of distinction that defines the limits of the system in the same domain in which it specifies them through its autopoiesis. If this is not the case, he does not observe the autopoietic system as a unity, even though he may conceive it.”(Varela, 1979, p. 54)

The second, but related, explanatory risk has to do with ascribing autopoiesis to systems with which the observer / explainer may have ‘proper’ observational engagement, but for which the observer ignores addressing the key features of the autopoietic organization by which the process of autopoiesis is defined. Varela (1979) also addresses this issue in passing, during his discussion of ascribing autopoiesis to other (autonomous) systems (i.e., systems of similar apparent constitution or apparent mode of operation, but not ‘living systems’). Varela notes that other systems, being autonomous, entail:

“…assertion of the system’s identity through its functioning in such a way that observation proceeds through the coupling between the observer and the unit in the domain in which the unity’s operation occurs.What is unsatisfactory about autopoiesis for the characterization of other unities … is also apparent from this very description. The relations that characterize autopoiesis are relations of productions of components. … Given this notion of production of components, it follows that the cases of autopoiesis we can actually exhibit, such as living systems or model cases …, have as a criterion of distinction a topological boundary, and the processes that define them occur in a physical-like space…

Thus, the idea of autopoiesis is, by definition, restricted to relations of productions of some kind, and refers to topological boundaries. These two conditions are clearly unsatisfactory for other systems exhibiting autonomy.” […of which Varela specifically mentions animal societies and human social institutions — Ed.]

(Varela, 1979, p. 54, emphasis in the original)

The difference between autonomy and autopoiesis is that autopoietic systems must produce their own components in addition to conserving their organization . Autonomous machines need only exhibit organizational closure, and they are not required to produce their own components as part of their operation.

---

Cf. : allopoiesis, allopoietic machine, autopoietic machine, machine.

---

2.

A label sometimes used to denote the body of Maturana and Varela’s theoretical work.

---

Cf. : autopoiesis theory, autopoietic theory, theory of autopoiesis.

autopoiesis theory

A label for the body of Maturana and Varela’s theoretical work, occurring rarely in the writings of other authors alluding to their theories.

Cf. : autopoiesis (2.), autopoietic theory, theory of autopoiesis.

autopoietic closure

A term invoked by Maturana (1978) in summarily characterizing autopoietic systems. He states autopoietic closure “… is the condition for autonomy in autopoietic systems in general, and that it “… is realized through a continuous structural change under conditions of continuous material interchange with the medium.” With regard to the thermodynamic constraints relevant to the physical space, “… autopoietic closure in living systems does not imply the violation of these constraints, but constitutes a particular mode of realization of autopoiesis in a space in which thermodynamic constraints are valid.”

This term is used only within one paragraph in this paper, and as such it’s somewhat difficult to discern whether it is being used as (a) a summary term for the ‘mode of closure’ evidenced in autonomous / autopoietic systems generally, or (b) a specific analogue to more clearly delineated constructs such as operational closure or organizational closure. Because the term is invoked specifically to discuss autonomy , one might make a case that it connotes organizational closure. However, there is no evidence beyond this to suggest such a linkage between the two constructs.

Cf. : closure, operational closure, organizational closure

autopoietic machine (system)

A machine / system which is a member of the class of autonomous systems and which meets the requirement of being organized (defined as a unity ) as a network of processes of production, transformation and destruction of components that produces the components which:

(i) through their interactions and transformations regenerate and realize the network of processes (relations) that produced them; and (ii) constitute it as a concrete unity in the space in which they exist by specifying the topological domain of its realization as such a network. (Maturana & Varela, 1980, p. 135, Cf. : Varela, 1979, p. 13)

Any unity meeting these specifications is an autopoietic machine / system, and any such autopoietic system realized in the physical space is a living system. The particular substantiation of a given unity — its structure — is not a sufficient factor for making the system “living”. The key feature of a living system is maintenance of its organization, i.e, preservation of the relational network which defines it as a systemic unity. Phrased another way, ‘…autopoietic systems operate as homeostatic systems that have their own organization as the critical fundamental variable that they actively maintain constant.’ (Maturana, 1975, p. 318)

Varela, Maturana & Uribe (1974) provide a concise set of criteria for autopoietic machine, arranged as a 6-point key by which one may proceed step-by-step in evaluating autopoiesis for a given unity. This key is illustrated in Table AutoKey below.

Autopoietic machines are the opposite of allopoietic machines, which are defined in terms of a purpose other than maintenance of their own organization. However, an observer can ascribe allopoietic ( allo-referred) status to an autopoietic machine within a subsuming context. Autopoietic machines may be described or manipulated as components of “…a larger system that defines the independent events which perturb them … [and] can in fact be integrated into a larger system as a component allopoietic machine, without any alteration in its autopoietic organization.” (Varela, 1979, p. 16) (See Also: higher-order, second-order, third-order) Conversely, an observer may analytically decompose an autopoietic machine, treating each of its “…partial homeostatic and regulatory mechanisms as allopoietic machines (submachines) by defining their input and output surfaces.” (Varela, 1979, p. 17) Such a decomposition does not sum up (as a collection of allopoietic submachines) to an appropriate description of autopoietic machines, because it “…does not reveal the nature of the domain of interactions that … [autopoietic machines] … define as concrete entities operating in the physical universe.” (Varela, 1979, p. 17)

Cf. : autonomy , autopoiesis , autonomous machine (system), machine

autopoietic network

A term used by Varela (1979, p. 13) to denote that “…particular network of processes (relations) of production of components …” which characterizes an autopoietic machine / system.

autopoietic organization

The generic term denoting the organization characterizing autopoietic machines / systems. The term “…simply means processes interlaced in the specific form of a network of productions of components which realizing the network that produced them constitute it as a unity.” (Maturana & Varela, 1980, p. 80)

Cf. : living organization, organization , organization of the living

autopoietic space

“An autopoietic organization constitutes a closed domain of relations specified only with respect to the autopoietic organization that these relations constitute, and thus it defines a space in which it can be realized as a concrete system, a space whose dimensions are the relations of production of the components that realize it.”(Maturana & Varela, 1980, p. 135)

Note that this “autopoietic space” is not isomorphic with the general physical space which is the context for realization of the composite unity . Perhaps the best interpretation is to consider an autopoietic space to be analogous to a state space (a depictive construct for a system’s attributes). Maturana and Varela (1980, pp. 90 ff.) ascribe three dimensions to the autopoietic space, corresponding to the three classes of relations of production.

Cf. : domain, relations of production, space

Source: Some Streams of Systemic Thought

(alt links:

and

Click to access MapOfSystemsAnnotated.pdf

THURSDAY, 28 JULY 2016 06:48 WRITTEN BY BENJAMIN HADORN

PUBLISHED IN SYSTEMICS & CYBERNETICS

Some Streams of Systemic Thought

In terms of systems thinking, an extensive map of related work and their influences is presented by the International Institute for General Systems Studies (IIGSS, 2001). This map was originated by E. Schwarz in 1996. It includes the influences of researchers in the domains of mathematics, physics, computer science, engineering, cybernetics, systemics, biology, ecology, sociology and philosophy fromancient times to the present.

With the permission of Jeffrey Yi-Lin Forrest (director of IIGSS), we update the map and add recent work in the field of cybernetics, systemics and coordination. Because the latest source files of that map are missing, we completely redraw it. We choose graphml, an open source format for graph design.

Legend of Map

The map encompasses different nodes and edges. The nodes denote topics, such as scientific work or research areas. Major influences between the topics are illustrated by directed edges. The map uses a color-code to show the major scientific realm of nodes and edges:

• white: general system
• red: cybernetics
• black: physical sciences
• blue: mathematics
• dark red: computers & informatics
• green: biology & medicine
• yellow: symbolic systems
• orange: social systems
• light green: ecology
• gray: philosophy
• cyan: systems analysis
• purple: engineering

History

Following list illustrates the origin and updates from the map.

• Originated in 1996 by Dr. Eric Schwarz, Neuchâtel, Switzerland.
• Extended in 1998, including items from the “The Story of Philosophy” by Will Durant (1933).
• Elaborated in 2000-2001 from many sources for the International Institute for General Systems Studies.
• Extended in 2016 by Benjamin Hadorn, Fribourg, Switzerland.

Your contribution: Feel free to extend and correct the graph. Please send an updated version to us in order to keep a current version online.
Thanks.

Download attachments:

• systemic_evolution.graphml (1318 Downloads)
• systemic_evolution.pdf (1965 Downloads)

Benjamin Hadorn

Source: visualcomplexity.com | A visual exploration on mapping complex networks

	Search the VC database:

Latest Projects:

Indexing 1000 projects

Most Visited Projects: 1. Yeast Protein Interaction Network 2. Afghanistan Stability / COIN (Counterinsurgency) Dynamics 3. Brain drain 4. Dead Kennedys 5. College of Design and Social Context  6. Guardian’s Facebook Page 7. Listen to Wikipedia 8. Musical Nodes 9. The Contractor Food Web 10. Top 10 Twitter Languages in London Most Commented Projects: 1. NYC Subway Map Redesign 2. Windows vs Linux Server 3. I Wish… 4. Data visualisation of a social network 5. Oil Money 6. Hospital System – From client to Patient 7. Web Trend Map v3.0 8. Musicovery 9. Human Trafficking 10. 1hr in front of the TV Popular Searches: 1. map 2. facebook 3. timeline 4. architecture 5. music  6. time 7. twitter 8. network 9. tree 10. internet

The concept of the regulation of the internal environment was described by French physiologist Claude Bernard in 1865, and the word homeostasis was coined by Walter Bradford Cannon in 1926.^[5][6] In 1932, Joseph Barcroft a British physiologist, was the first to say that higher brain function required the most stable internal environment. Thus, to Barcroft homeostasis was not only organized by the brain—homeostasis served the brain.^[7] Homeostasis is an almost exclusively biological term, referring to the concepts described by Bernard and Cannon, concerning the constancy of the internal environment in which the cells of the body live and survive.^[5][6][8] The term cybernetics is applied to technological control systems such as thermostats, which function as homeostatic mechanisms, but is often defined much more broadly than the biological term of homeostasis.^{[4][9][10][11]}

Source: Homeostasis – Wikipedia

Cannon https://en.wikipedia.org/wiki/Walter_Bradford_Cannon

Bernard https://en.wikipedia.org/wiki/Claude_Bernard

Barcroft https://en.wikipedia.org/wiki/Joseph_Barcroft

(Extracts from) self-regulation of the body (Cannon, 1939) http://www.cybsoc.org/cannon.pdf

Walter Cannon and Self-Regulation in Animals (Hagen) http://shipseducation.net/db/cannon.pdf

Good core references: https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/homeostasis

https://en.wikibooks.org/wiki/Human_Physiology/Homeostasis

Some alternative points:

Research review
From Claude Bernard to Walter Cannon. Emergence of the concept of homeostasis
Steven J. Cooper

Roots of current conceptions of the regulation of states of the body through negative feedback mechanisms are traced back to Bernard’s ideas on active stabilisation of bodily states against disturbances from the outside, revived by Henderson and Haldane, and crystallised in Cannon’s concept of homeostasis.
2008

Click to access cooper2008.pdf

A. Querido and J. van Gijn
‘The Wisdom of the Body’: the Usefulness of Systems Thinking for Medicine

Abstract
An attempt is made to evaluate the application of system thinking to medical
problems. Two examples clarify the difference between the atomistic
approach and considering the organism as a whoIe. After elucidation of the
roots of system thinking – especially in connection with natural systems –
some consequences of the integrative approach for both the theory and the
practice of medicine are discussed, as weIl as its significance for medical
education.

Click to access PU00011604.pdf

Reference in cybernetics: a new management tool (Clemson, 1984)

https://books.google.co.uk/books?id=VqQpICD5IXgC&pg=PA215&lpg=PA215&dq=Canon:+%27A+system+survives+only+so+long+as+all+essential+variables+are+maintained+within+their+physiological+limits.

Adaptive Homeostasis

Adv Physiol Educ. 2015 Dec; 39(4): 259–266.

doi: 10.1152/advan.00107.2015

PMCID: PMC4669363

PMID: 26628646

A physiologist’s view of homeostasis

Harold Modell,¹ William Cliff,² Joel Michael,³ Jenny McFarland,⁴ Mary Pat Wenderoth,⁵ and Ann Wright⁶

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4669363/

Always worth sharing this classic – can’t believe it wasn’t on here – must have been on model.report 🙂

A first lesson in meta-rationality, or stage 5 cognition, using Bongard problems as a laboratory.

Source: A first lesson in meta-rationality | Meaningness

My comment and David’s response:

Click to access REI_2011_Snakes.pdf

(pdf)

https://onlinelibrary.wiley.com/doi/abs/10.1002/sres.1105

Research Paper

Snakes all the Way Down: Varela’s Calculus for Self-Reference and the
Praxis of Paradise

André Reichel*
European Center for Sustainability Research, Zeppelin University, Friedrichshafen, Germany

This contribution seeks to commemorate Francisco Varela’s formal conceptions of self-reference, providing an overview of his writings while shedding some light in the praxis of self-reference, from where a future research agenda can be derived. The architecture of Varela’s thinking, determined by the interrelated notions of autopoiesis, autonomy, closure and self-reference, was examined. The emphasis was on the development and expansions of his calculus for self-reference from George Spencer Brown’s Laws of Form. After dealing with some of the criticism launched at both works, an appraisal of the praxis of self-reference of Varela’s thinking in action was given. The outlook rounds up this contribution, shedding some light on a possible future research agenda for the formalization of theory and praxis of self-reference.

Keywords Francisco Varela; self-reference; Laws of Form; closure; autonomy

“If everybody would agree that their current
reality is a reality, and that what we essentially
share is our capacity for constructing a reality,
then perhaps we could agree on a metaagreement for computing a reality that would
mean survival and dignity for everybody on
the planet, rather than each group being sold
on a particular way of doing things. Thus,
self-reference is, for me, the nerve of this logic
of paradise . . .”

(Varela, 1976: 31)