What is Structural Memetics? And Why Does it Matter?


Below Kanab Creek, Grand Canyon, 2003

A quick editorial note — lately, I’ve been referring to my work as ‘structural memetics’ — with the intent of expanding a concept of knowledge generation with memes along the same line as genetics — laying out general principles to follow about how humans generate knowledge.  Much of this material has already been created on this blog, but I wanted to consolidate and summarize it in one place.

Bored, and seeking the never-ending references, I Googled up Melvin Conway, whose famous law serves as the backbone for most of my developed insights.  Turns out he’s still alive — and on Twitter.  So.. I tweeted back at him.  And he responded, saying he’d take a look at my work.  

Short version of a longer story — I hurried up with this post so he wouldn’t have to dig.  I think it’s pretty complete.  So, Mel — this one’s for you.  Thanks for the origination thought.  There’s a lot here.  Check out the Topics Grouping/Readers Guide for the full extent of all of this. But these are the bones.


What is Structural Memetics?  And Why Does it Matter?

As a scholar, I’ve spent my life studying things.  Directly or indirectly, my profession (and the need to be a better teacher and designer – I’m a design engineering prof.) has fed my interest in reading all sorts of different types of information, or rather, knowledge.  Internet resources like Wikipedia have made it possible as well for anyone to peruse any subject area.  I love Wikipedia.  Nowhere else on the Internet can you move so quickly between connected subject areas – or areas you might think are connected – with just a click.

But one of the interesting things I’ve noticed as I’ve gone about my escapades on Wikipedia, following philosophers, fighter aircraft, and military campaigns across the Asian steppes, is that there is precious little discussion on knowledge, or rather, the structure of knowledge, in any or all of it.  There are isolated blips of understanding – things like Bloom’s Taxonomy are often used, for example, in educational work.  People will allude to culture, literature, art, math or science.

It all sounds good enough – we’ve been raised to think in those terms, they satisfy, so we move on. But science, or culture, is a pretty big thing.  None of it tells you how or whether you should believe it to be true.  No one would argue that knowledge is created by groups of humans, though usually one gets the credit.  But largely, most knowledge has no origin story that we’re aware of.  We’re told someone is supposed to believe something because of ‘science’.  Let’s stop a moment – I am a scientist, and I support the scientific method (whatever that is) in the face of a backdrop of blind faith. But with replicability crises happening across many different scientific enterprises – I’ve been immersed in the nutrition research lately, since I lost a lot of weight and been attempting to figure out how I got fat in the first place – it’s time to take a pause and realize that we have a very poor understanding of what knowledge is in the first place.  Or what level of truth it actually represents.

People have more recently attempted to think of knowledge in terms of ‘memes’ – small fragments of information, typically with viral characteristics.  There’s a relatively short, unhappy literature associated with the concept.  Richard Dawkins is noted for coining the term, mapping it as an analog to a gene. And then he started using it to condemn religion for infectious, unaware acceptance of a veritable litany of concepts. The book Virus of the Mind, written by Richard Brodie, the inventor of Microsoft Word, and world champion poker player, maps the idea of memetics to ideas as infections.  The idea of thoughts “going viral” has entered the vernacular of everyone with access to the Internet.

Not a very prosocial, nor hopeful understanding of how we think.  Big thoughts get sidelined as anti-memetic and outside any understandable brain coding. Instead, the focus is on the pernicious exploitation of our lack of awareness.  And if you ask most people what a meme is, they’ll likely tell you it’s a picture of Kermit the Frog, or a velociraptor, dressed up as a Philosoraptor, puzzling over life’s larger questions in some pithy text written on top of their face.  Even one of the founders of meme-ology (for lack of a better term) Susan Blackmore, settled on defining a meme in the smallest unit of replicable information.  If you were really mapping understanding to genes, why wouldn’t you want to understand the deeper patterns present in human, or generalized sentience?  It’s more than a metaphor — information is information is information.  There has to be larger patterns.

There have been exceptions to the ‘meme as a smallest unit of information’ club.  Don Beck, of Spiral Dynamics fame, created the term ‘v-Meme’ to characterize value sets associated with different levels of societal development, which in turn map to social structures.  But outside of this, work on memetics has essentially vanished. We’re left with Kermit the Frog, longing for a beer in the rain.

Why would such a promising idea – the idea that knowledge has replicable structure, with affinities vanish so quickly?  The real problem is that we have no generalizable notion of how knowledge is created in the first place. The deeper reason below that level is what I’d characterize as a patently false belief — that we implicitly believe that knowledge is created by experts, and enshrined by culture – two things that we have little or no ability to challenge.  And, for some reason, if the experts – people like Dawkins, and Blackmore, and a couple of others – say it’s game over, then we believe them.  Give Don Beck credit – he knew better.

But there are problems when stringing more complex thoughts together.  Namely, replicability problems, especially when all humans are considered to have the same neural hardware.  We have convenient distinctions for how humans know.  Most of these are involved with our educational system, granting degrees, and culture – all things outside an individual’s independent assessment.  Others teach you – you don’t get to make decisions on truth yourself.  Life experience, and the assimilation and synthesis of that experience into usable knowledge is only grudgingly accepted.

Enter Conway’s Law

 One of the largest breakthrough thoughts on how humans construct knowledge came from a software pioneers – Melvin Conway.  Conway is the inventor of many different types of software innovations, but his law is the thing relevant here.  That is:

“organizations which design systems … are constrained to produce designs which are copies of the communication structures of these organizations.”

What Conway stated was that design of a system (he was thinking about software) would map to the social system that created it.  This idea has been empirically validated for software in a number of studies. But what is a design except an observable realization of knowledge?  That led me to the notion of what I named the Intermediate Corollary.

Social Structure <=> Knowledge Structure <=> Design Structure

This fundamental principle opens up the door to a larger understanding of how we produce knowledge.  And, as we’ll see, when combined with two things – Don Beck’s set of social structures, along with a deeper understanding of how people communicate, and importantly connect inside those knowledge structures – the synergy creates a new field that directly addresses the holes in memetics.  We can now understand how knowledge itself is structured, in a transcultural fashion.

Let’s fill out the first category – Social Structure – first.  Beck’s and Graves’ work on a generalized theory of human development, called Spiral Dynamics, outlined a set of eight social structures, relating to societal evolution, that are what we call a canonical set.  A canonical set in this context is a set of social structures, each unique, with increasing complexity.  Each of these individual social structures corresponds to what Beck originally called a value set.  These value sets would cover the social dynamics inside a given social structure.  For example, in an Authoritarian value set, the primary values in the value set would promote power and control.  Status inside the pyramid would be the foremost driver of behaviors, and what the individuals in the stack would believe would directly be controlled by the individual above them in the pyramid.  Legalistic hierarchies would, for example, be an evolution of an Authoritarian power structure, where rules would apply to individuals across the social system.  The rules would vary dependent on rank or level, but the overall effect would be to remove the arbitrary nature of judgment of the individual that was above another in the hierarchical stack.  Beck’s social structures are given by the diagram below.



One interesting point that needs to be made is to understand that for a given social structure, at a certain stage of evolution, lower value set social structures can be incorporated in a larger structure.  A Tribe can have Survival bands affiliated inside it.  An Authority-driven empire can be made up of tribes.  And so on.

From Conway’s Law comes Knowledge Structures – “As we relate, so we think.”

Once we have a generic set of social structures, and understand the value sets inherent in creating these, we can map these to known knowledge structures humans historically have used.  These are characterized by the dominant relational modes in each social structure, that sets the stage for the type of knowledge each must have mastery of to execute social function.  As with the above social structures, as knowledge structures build, they incorporate lower level structures into higher level structures.

These are:

  • Survival Band -> fragmented knowledge pieces, both temporally and spatially ephemeral.
  • Tribal Order -> long-term origination myths that create shared identity.
  • Authoritarian/Exploitative Empire -> knowledge fragments, whose truth is established by the authority of the person above another in the pyramid.
  • Hierarchical Authority Structure/Legalistic Hierarchy -> rules and algorithms, coupled with the ability to feed information into rules and obtained transformed values.
  • Strategic Enterprise/Performance-Goal-Based Organizations -> heuristics, incorporating lower-level knowledge structures, that rely on the independent decision-making ability of individuals (agency) to create coordination to reach goals.
  • Communitarian/Social Network/People Driven Systems -> multiple, combined heuristics from different data sources, blended to recognize appropriate differences, along with maintaining larger system coherence.
  • Systemic Flow/Process Oriented Second Tier Systems -> the first of what are known as ‘Second Tier’ systems, consisting of a larger leap of self-awareness, knowledge structures at this level and above consist of pruned heuristics, sculpted for balance of larger combined goals, with an awareness of individual bias in desired outcomes.
  • Holistic Organism/Global Holistic Social Structures ->larger complex systems of combined heuristics, integrated with the surrounding ecosystem, giving rise to emergent, complex, and likely fractal knowledge systems.


The Role of Empathy in Social Structures, Leading to Synergy in Knowledge Structures

The role of evolving empathy is poorly understood in the dynamics of societal evolution, and as a consequence, its effects on complexity of knowledge.  In fact, the very existence, outside this blog and a handful of other like-minded souls, seems to be ignored or discounted entirely.

Why this is so is likely due to the fact that the organizations we have tasked with creating greater understanding – our modern academic systems – are organized largely around low-empathy, authority-driven hierarchies.  In an authority-driven hierarchy, it really doesn’t matter much who you are, or what you contribute.  What matters is what you are, or rather your position in the hierarchical stack. You will be treated as your function demands you be treated, with little accommodation on how you might feel about that treatment.  And these systems, by their very nature, create highly fragmented, disconnected understandings of most phenomena.  The emphasis is typically on smaller and smaller fragmented units – be it units of matter, or subdivisions of ethnic classes.

Connection to your emotions, or your thoughts themselves is irrelevant.  The dark insight that comes from this is that academics studying empathy are about the same as colorblind people studying color. They just can’t see what the big deal is – especially the connecting, synergizing nature of this deeply sentient phenomenon.

There are signs that the neuroscience is slowly waking up to this fact.  In Prof. Matt Lieberman’s book, Social,(Lieberman is a professor of social neuroscience at UCLA) he says “In essence, our brains are built to think about the social world and our place in it.” This means that empathy, or more exactly, the level of development of empathy as the primary connecting function of our brains, actually creates the social structures, which are realizations of patterns of different level of human connection.  As well as how we think about everything else.  Our social relations, structured by our empathetic development, lay down the core memetic patterns in our brains, which then happen to get used for how we think about everything else.

As we move up the social structures, necessarily we also have to move up the empathy scale.  Frans de Waal, the famous primate behavioralist, has split empathy up into levels, bottom to top, that map onto the three primary areas of the brain – the basal ganglia/automatic function part, the limbic/emotional part, and the prefrontal cortex/thinking and detailed processing part.  Using simple language, that means empathy contains physiological, emotional, and cognitive functions.  And similar (or rather, self-similar) to social structures, as well as knowledge structures, these empathetic functions incorporate lower level functions into higher level ones.

These empathetic functions also, to the degree they are developed, also calibrate time scales and spatial scales inside the brain. Automatic, physiological responses of empathy, like direct mirroring, are instantaneous. Emotional empathy and connecting to others’ joys and sorrows takes a little longer, and finally developed cognitive empathy allows more complex processing of consequences, as well as dramatically increased time and spatial scales.

These map into knowledge structures, with little overlap.  Most importantly, when it comes to structural memetics, empathy is the primary factor in how fragmented, as well as coherent and synergistic, the knowledge produced by a given social structure is.  The greater the empathy any given set of individuals possess, the more opportunity and dynamic to mix the individual knowledge of two people attempting to come to an agreement.

Practicing empathy is also dictated by a given social structure. If you’re the boss in an Authoritarian system, reading someone’s face as a data stream doesn’t mean much unless you’re trying to figure out if they’re going to kill you, and they damn well better do what you tell them anyway.  But for a Communitarian, you’re likely attempting to achieve group harmony amongst a diverse range of individuals.  You’d better pay attention to all those different facial gestures.  So just as personal empathetic development matters, so also does the social structure that a pair of individuals are plopped into.  You can take two highly evolved individuals and place them in a low empathy social structure, and while they’ll likely do better than people who haven’t climbed the ladder, the odds are that they may never even meet each other — because that’s just the way the social system works!

These two empathetic factors – personal development, as well as social structure — bleed over into the knowledge structures, making them more and more data- and independent circumstance-dependent as one moves up the ladder.  At the Survival level, your data structures are where the watering hole is, or who brought donuts to the office.  Mirroring behaviors of your co-workers as they drool might be all you need to know you want some of that sugary goodness.  But higher level knowledge structures require more practice of empathy, and its twin, self-empathy.  How can you choose paths in a given design heuristic if you don’t believe that an individual has a right to choose?

All this leads to a master diagram, which knits together the basic principles of structural memetics.  Here it is below:

Empathy Neural Fcn SD Slide

and then the final step, mapping the Value Set levels to Knowledge Structures, is below.Knowledge Structures Mapping.jpg


 Social structures and personal development of empathy essentially create the brain that is receptive to more complex knowledge structures. This allows us to move our understanding of memes solely out of the world of Kermit the Frog longing for a cold one, and into an understanding of how communities of people can transmit complex knowledge from one person to another relatively quickly.  There is no cultural hook required.  Donald Trump and Kim Jung Oon merely have to be participating in a duplicate version of the same social structure to “grok” the other’s understandings.  Because just like genes, memes can lock in complex sequences.

 This leads us to the beginnings of a new field – structural memetics.  And while there is much room for development, the beginnings are here.  Because as we relate, so we think. And that means, with a combination of insights from Conway’s Law, social neuroscience, and Spiral Dynamics, we can directly lift the structural memetic patterns of knowledge from the social structures and networks sitting in front of us.  No microscope required.

3 thoughts on “What is Structural Memetics? And Why Does it Matter?

  1. Memes were introduced as a term by Dawkins in his book ‘the extended phenotype’—after his earlier one ‘the selfish gene’. It seems as though Dawkins actually never read the 2nd book he wrote or else forgot about what he wrote. There are actually 5 different formulations of the meme concept—the culturgen of E O Wilson and C J Lumsden in their 70’s book (using well known formalism of mathematical physics–Lumsden did the math which is well known in statistical physics)—their later revision in 2000’s retracted some of their claims—they had the math correct but not the interpretation.

    A version in words was about same time–‘dual inheritance theory’. Feldstein and Caffali–Svorza of Stanford had their own version around 1981. (very messy math –using population genetics formalism–its better to stick with statistical physics).

    There is a much more current version though it doesn’t use term ‘meme’–its also mathematical but while based on population genetics, doesn’t create the mathematical mess found in Feldman’s and CFS’s book. (if you take a look at old 60’s books by Ilya Prigogine on nonequilbrium thermodynamics , kinetic theory, and statistical mechanics—all the same field–you will see 100s of pages of equations complete with Feynman diagrams — modern stuff does that all in like 4 pages. Principia Mathematica took 600 pages to prove that 1+1=2. while rigorous, there are easier proofs. )

    ‘Meme’ became a contentious term because it didnt have a rigorous definition (m ruse and many others discuss this).

    I had never heard of conway until this blog–he seems to have come to the same conclusions as people in other fields–i view ‘the law of requisite variety’ as a related oncept. There is another conway–famous for his ‘game of life’ and CA as well as other things. (eg his ‘free wil’ theorem in physics concluded that ‘if experimenters have free will, then so do elementary particles’. )

    many people criticize wikipedias, but some academics who i consider to be among the ‘top’ –they have earned their privliedges—swear by it. its the first place they go for a topic they dont know , while recognizing its deficiences –people do not get paid to contribute to that. however it generally will have links to sources so you can get more information. (i have never contributed to wikiP but my mother did). some of the technical articles are actually lecture notes by professors so they tend to be very advanced similar to the free MIT math courses.

    there is a sort of field that studies ‘knowledge’ and its relation to ‘information’ (i once went to a conference on ‘information and meaning’. I have also been told by 2 professors that while they have published mathematical papers on knowledge and information using techniques from shannon’s information theory and bayesian maximum entropy, i couldn’t study that—it wasn’t their main feild, just a side project, and not what they get paid for. most academics when i was in college and doing research told me i had to ‘do something useful’. i was advised alos to not waste time reading stuff by Feynman or Ilya Prigogine–both noble prize winners in physics–or similarily Kadanoff and Wilson on renormalization group—thats where you get ‘knowledge from information’. They said that stuff was too trivial and irrelevant. They had the Dirac or Bricmont view—shut up and calculate (except they also discouraged learning any advanced ways to calculate—sort of like saying although there are planes, if you want to go from UK to USA you build a ship and sail there so you know what you are doing. Also never use a calculator–use a slide rule. ).

    Its all about empathy. I wonder how much empathy was felt by the people doing these homicides around here. ‘i feel your pain’. Empathy is a term like meme–no accepted definition. ‘god bless and pass the tithing plate’. or prasie the lord and pass the ammunition. look up and admire the tower of babel.


  2. Now we are getting somewhere !

    That was the whole concept in a blog post with very few $5 words. I thought concise and coherent. A good basis for your NSF grant and a platform to go forward.

    How do you feel and what does your son think?


    On Fri, Apr 5, 2019 at 10:37 PM It’s About Empathy – Connection Ties Us Together wrote:

    > Chuck Pezeshki posted: ” Below Kanab Creek, Grand Canyon, 2003 A quick > editorial note — lately, I’ve been referring to my work as ‘structural > memetics’ — with the intent of expanding a concept of knowledge generation > with memes along the same line as genetics — laying out g” >


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