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Fw: Affective measures in the social sciences produce more ideologic agitprop... by Mike Alexander 16 September 2002 21:42 UTC |
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John Landon writes:
I was referring more generally to Very Large Scale historical 'evolution',
and there we have to take everything into account from high to low. And the
complexity is too vast for any simple model.
Very complex phenomenon can sometimes be described adequately using very
simple models. For example, consider the growth of micro-organisms.
This is an enormous complex process involving hundreds of individual
physiological processes, which interact with dozens of environment
variables. Yet under certain conditions the growth rate can be described
reasonably well by the Monod equation:
dX / dt = X * vS/(S+K) where X is the microbial mass, S is the
concentration of the substrate (food) and v & K are constants.
The certain condition is when growth is limited by the availability of food
as opposed to limitations of air or water, or the accumulation of toxins.
Fernand Braudel notes that at certain times in history, e.g. early 16th
century, (also early 14th) real wages fell to a level where the amount of grain
they would purchase barely matched the caloric needs of a person. In other
words, lower wages would be incompatible with life. And indeed wages
did not fall, rather, population did, and wages rose. So human populations
can become substrate-limited just as microbial populations.
But there are more interesting responses of microbial populations to
environmental consequences of their own behavior. In my Ph.D. research on
alcohol production from xylose (a wood-derived sugar), I noted cyclical behavior
of the yeasts under certain conditions. I would do experiments in which I
initially produced a stably-growing population of yeasts in a continuous
fermentor. A continuous fermentor has a feed and a discharge which
maintains a constant volume. At steady-state the culture is limited by the
rate at which substrate is fed into the fermentor--thus growth rate can be
manipulated as an independent variable. This initial population would be
exclusively performing respirative metabolism (they consumed sugar, growing new
biomass, and releasing carbon dioxide and water as waste products like we
do). I would then suddenly shift them to conditions of partial oxygen
deprivation in which they no longer had sufficient oxygen to metabolize all the
sugar available. This would kill higher animals like humans, of
course. But yeast are facultative, that is, they can do both
respiration and fermentation. So after a lag of a few hours the yeasts
would metabolize via fermentation (producing alcohol) that sugar they could
not metabolize via respiration (using oxygen). The result would be
accumulation of alcohol until a new steady-state was reached, in which biomass
was produced using a combination of fermentative and respirative that was
controlled by the availability of oxygen.
In some experiments, those in which I started with a large population of
yeasts and tried to make high concentrations of alcohol, I found that a steady
state alcohol concentration was not achieved. Instead the concentration of
ethanol (and every thing else) oscillated between high levels and low
levels. The high levels were higher than (and the low levels were lower
than) the steady-state levels I had obtained in other experiments with
smaller populations. What was happening was accumulation of alcohol (which
is toxic) was adversely impacting the growth and fermentation capabilities of
the yeasts. This is a commonly observed phenomenon, but even if it
happened, one would still expect steady state conditions to be reached.
The nature of these steady states would depend on both the alcohol concentration
and the oxygen supply.
But instead I observed cyclical behavior. After playing around with
the data a bit I noticed that one could model the effect of alcohol on growth
and fermentation if you used the alcohol concentration of the past
rather than the present in the model. There was a "memory effect".
Alcohol exerted a deleterious effect on microbial life, which took time to
manifest. During this time the concentration would continue to
accumulate. At some point the past alcohol levels finally exerted an
effect strong enough to stop increasing present alcohol levels, but by this time
the level was much higher than the problem level. So now alcohol
production began to fall in response to the still-rising concentrations of the
past. By the time the alcohol production level stopped falling, the level
had reached a present level way below the problem level, and so up the
concentration would go. The lag time required to model this behavior was
the "generation time" of the population.
I hypothesize that late Medieval and Early Modern human populations did
something similar. But instead of waste products, the driver here was
lagged response of fertility to food supply. I start with a time when food
supply is growing at a faster rate than population. People coming of age
at such times will, on average, find it easier to establish a household and to
have a family. They should experience greater lifetime fertility.
Because of this increased fertility the population a generation down the road is
going to contain more people of breeding age than the current population.
Unless the food supply grows at a faster rate, this larger population is going
to fast a less satisfactory relation between food supply and mouths to
feed. They will find it harder to establish a household and start of
family. They will experiment reduced fertility.
Thus we might expect to see oscillating fertility and relative food
supply. When fertility is low relative food supply is high and their
should be fewer famines and food prices should on average trend downward. When
fertility is high, relative food supply is low and their should be more famines
and food prices should trend upwards. The oscillations should show a time
constant of (human) generational length, which peaks and toughs spaced two
generations apart (50-60 years). This cycle in prices is called the
Kondratiev cycle. Evidence for this model would be a cyclical behavior
of famine frequency, with frequency highest at the point of the fertility
cycle at which food supply relative to population is the least favorable and
prices should average the highest (i.e. the Kondratiev peak). A
statistically significant pattern does appear in these variables as I describe
in my Kondratiev book. Other evidence is also presented.
This is an example of how a natural science approach (that is not
physics-based) can be applied to human behavior. Some of the long term
trends you mention follow naturally from this sort of a mechanism--given certain
constraints imposed by geography. I can get into these later, if people
are interested.
Mike Alexander, author of
Stock Cycles: Why stocks won't beat money markets over the next 20 years and The Kondratiev Cycle: A generational interpretation http://www.net-link.net/~malexan/STOCK_CYCLES.htm
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