Disorders of Magnitude
Catataxis is a neologism to describe the disfunction that arises when issues are scaled up. The micro view is inherently different to the macro view. This is something readily acknowledged in many disciplines – physics, economics and computer science – but rarely applied in a broader sense. Physics has yet to combine quantum mechanics and Einstein’s relativity into a single grand unifying theory – the two approaches are still distinct. Likewise, economics courses are separated into micro and macro versions of the discipline. In computer science, issues at the p/n junction level in the underlying silicon are rarely conflated with coding in Python – software and hardware are seen as distinct domains.
We can express this disjuncture between the micro and the macro in four catataxic maxims – crafted as paradoxical statements that highlight the flaws in assuming that all things are linearly scalable.
1. More of the same is different
When you scale something up its not just the size that changes. In the end, a quantitative change becomes a qualitative change. Sometimes it is expressed like this :
“Quantity has a quality all its own”
This quote is often attributed to Josef Stalin who also callously remarked, in the same vein, that
“The death of one man is a tragedy; the death of a million is a statistic”
This principle of quantitative change leading to qualitative change is one of the central tenets of the Marxist theory of Dialectical Materialism but its roots lie in Hegel’s Science of Logic and beyond that in the paradox of the heap as formulated by the ancient Greek philosopher Eubulides
The problems of increasing scale can be expressed mathematically in relationships such as the surface area to volume ratio. Both the surface and the volume of an object expand exponentially when scaled up. But where the surface increases proportionally to its square, the volume increases in proportion to its cube. That’s why animals in colder climates tend to be larger; heat is lost through the surface so a low surface area to volume ratio keeps you warmer. A polar bear is twice the size of brown bear.
2. Categorisation destroys information
The act of categorising something removes it from its context and turns it into ‘data’. In this transformation it moves up one level to a meta level and so crosses a catataxic boundary. The data is then processed and analysed to formulate conclusions which might be erroneous because important contextual information has been left behind.
Identifying something as a member of a group risks reducing its identity to just being a group member – a flaw at the heart of much of identity politics. But in a wider sense this is a problem with the whole analytical process. Typically this involves three steps :
1. Abstraction
2. Theoretical formulation
3. Re-application to practical reality
It is the first step – abstraction – that is the most dangerous because it eliminates context. So much so, that it might be wiser to actually reverse this analytical process and put practice before theory.
My favourite anecdote here concerns Montagu Norman, the Governor of the Bank of England, who in 1933 hired the first professional economist to work at that institution, a man called Henry Clay. When explaining the new role the Governor told Mr Clay:
“You are not here to tell us what to do, but to explain to us why we have done it”
3. Order requires chaos
The western esoteric tradition of Hermeticism was the wellspring of the Renaissance and the inspiration for the development of the scientific method in the 17th century. Isaac Newton was a Hermeticist and his Theory of Gravity was prompted by the key Hermetic principle:
The idea here being that the order of the heavens was reflected on earth; that the macrocosm and the microcosm are mirror images of each other. However, catataxis expounds the opposite principle:
As above, not so below
The point here being that stability on a higher level requires disorder and conflict on the level below. Take as an example the workings of a stock market. Smooth changes in prices are only achieved by disagreement between buyers and sellers. It’s only when everyone thinks the same way that you get discontinuous price movement. Markets crash when there are only sellers. The multitudinous, chaotic roiling of buy and sell transactions amongst parties with opposing views is what keeps the price movements at a higher level smooth and continuous.
Politics provides a second example, summed up in the motto “divide and rule”. If the political factions beneath the king are constantly arguing with each other they are less likely to depose the ruler. So disagreement on level one creates stability on level two.
4. Complexity requires simplicity
If you compare an amoeba to a human being you will probably conclude that the human is vastly more complex. After all, the amoeba is just a single cell whereas a human has trillions of cells. On the other hand, each one of of those human cells is specialised in some way such a liver cell, a brain cell or a skin cell. Each cell does one specific task and is dependent on the other cells doing their particular specialty in order for the organism as a whole to survive. With an amoeba the single cell is multifunctional – it does everything. But the complex human being requires its cells to be simple.
Adam Smith in his Wealth of Nations (1776) drew the same conclusion using the example of pin making. Have a look at the picture on a UK £20 pound note where this is commemorated. His insight was that the division of labour leads to greater efficiency and productivity. When individuals become more specialised, the whole becomes more efficient. So the complexity of a modern supply chain requires simplicity at its individual stages.