From: Jurriaan Bendien <jurriaanbendien@online.nl>

Date: Sun Dec 26 2010 - 11:33:16 EST

Date: Sun Dec 26 2010 - 11:33:16 EST

Just a thought I had, again. In the mathematical explanation of equilibrium

systems, the base data are random events. If they are truly random events,

they cannot be explained or predicted - because they are random. The very

meaning of chaos is unpredictability and uncertainty. What the analyst then

does, is that he groups the apparently random events according to

qualitative categories in clusters, and he discovers certain patterns which

suggest an order anyhow - perhaps a hidden order obscured by the surface

appearance of randomness. This is his "theoretical act". The patterns can be

fitted to an equation, and, Bob's your uncle, you have an explanation of

events - which seemed random, but really aren't; the fact, that the events

conform to an equation with predictive power provides proofs, or at least

grounds, for believing they are determinate after all, and not merely a

random fluke.

The question however is whether such an approach is really apposite in the

case of Marx's theory. After all, human activity according to Marx is mainly

not random. In the first instance, the reason is that the activity is

purposive, but secondly also, the activity is constrained by definite

parameters which cannot easily be escaped from; the human species is

compelled to do certain things to survive and prosper. There are, therefore

definite means-ends logics in human behaviour, even if several of such

logics operate at the same time and may contradict each other. If that

wasn't

the case, one might as well throw out all ideas of a rational politics and

close down the law courts.

The first problem is really that in order to understand seemingly random and

arbitrary events as non-arbitrary, non-random events, we require

categorizations which define constants and variables. But what is it, that

entitles the analyst to adopt those categorizations, if there is prima facie

nothing in the random distributions that would suggest any particular

categorization as preferable to any other? The analyst argues, that if

certain categorizations are adopted, then events are predictable. In

principle of course one could succeed in predicting something without

knowing why the prediction succeeds. But where does he get his

categorizations from? In the last analysis, the "model" assumes the

hypothesis of some causal relationships, a causal theory which tells us

where to look for patterns and explanations. What makes the

choice of assumptions non-arbitrary?

Problem number two is that in the procedure, we might well be assuming what

we seek to explain. We set out with theoretical assumptions to find

empirical

corroboration, but in reality we may not explain very much but just

describe something. The fact that one variable can predict another

variable does not necessarily say anything yet about the possible

causal relationship between them.

Problem number three is, if the result of the analytical procedure is to

supposed to demonstrate that random events are in truth not random events,

why should we assume to start off with, that they are random events? Why

should we try to demonstrate the likelihood that a result is, or is not, due

to chance, when we know very well that it is determinate?

Problem number four is that a theory, if it is at all adequate, if it has

any

depth, must explain the choice of its own assumptions. That is what

models typically do not do, or only superficially. The model is an

isomorphism or "likeness" (analogy) which is offered precisely in

advance of a comprehensive theory. It signals, that we do not

really know how to theorize phenomena yet.

The whole edifice of equilibrium theory is based on the simple idea

that, other things being equal, supply and demand will tend to adjust

to each other. But is this all that we can say about the capitalist economy?

Marx certainly thought not, and penned three fat volumes to provide

a causal explanation of its workings.

There is a direct connection between the use of models and

ideological fabrications. That is, the model permits us to fathom

an empirical relationship without any more comprehensive knowledge

of the relevant phenomena - this is a convenient ploy to abstract

away from any knowledge or assumption that would be highly

uncongenial to the modeller. It is not just that the model is often

mooted in advance of comprehensive theory, but that the model is

substituted for a comprehensive theory. Thus, the proliferation of

models is a neat way to obscure the interconnection of the

phenomena modelled as a whole, which a comprehensive theory

would reveal.

Jurriaan

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Received on Sun Dec 26 11:34:53 2010

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