Review of Turchin
- From: "Lance" <lachenicht@xxxxxxxxxx>
- Date: 17 Feb 2006 14:23:53 -0800
11 March 2005
http://www.sas.org/tcs/weeklyIssues_2005/2005-03-11/books/index.html
"Historical Dynamics: Why States Rise and Fall"
Peter Turchin, Princeton University Press, 2003.
Reviewed by Kevin T. Kilty
At the conclusion of my talk about experimental and historical sciences
at the June 2002 meeting of the Society for Amateur Scientists, Sheldon
Greaves asked me if I had ever thought about how the study of history
itself might become an experimental science. I had not thought about
this, and my first inclination was to suggest that perhaps economics
already combined elements of history and experimentation. Peter
Turchin's "Historical Dynamics" (Princeton University Press, 2003)
presents a better answer, but one that is still not satisfactory. Yet I
recommend the book on the basis of its most engaging passages on
history and causation.
"Historical Dynamics" is an extremely ambitious book and fascinating to
read in parts. According to Turchin, the problem he intends to attack
in this book is that a science, such as history or sociology, cannot
become a mature science until it incorporates mathematical models. He
intends to show the way toward applying mathematics to history.
History and sociology both rely on verbal arguments, not mathematics,
as models. Verbal arguments can be misleading at times. They give a
person the confidence of explanation without a reliable view of model
dynamics. This is similar to the problem I identified regarding geology
in my 2002 talk. One can propose a verbal model as geologists often do,
but one cannot know the value of the model until one specifies its
consequences and tests these against experimental data.
Consider predator-prey relationships as an example of the verbal model
problem. The feedback system that results in population cycles of
predator (lynx) and prey (snowshoe hare) is explained verbally as
growth of prey in the presence of few predators, then over-exploitation
by a rapidly expanding predator population. This explanation sounds
perfectly complete and convincing. Yet, the phase lag between the two
populations (and differing time constants of response) that is needed
for cyclic behavior might be overlooked where it not for analysis of
the associated differential equations.
Turchin's organization of his book is one of iteratively stating a
problem in the study of human action (for example the growth of ethnic
identity), providing a background of facts pertaining to the issue,
presenting verbal theories, reducing the verbiage to a mathematical
model, describing some results of the mathematical model, and
occasionally applying an empirical test. The discussion of growth of
empires, or even just polities, constitute the most interesting parts
of the book. It made the book so interesting that I continued to read
even though I became bored with the "mathematical" discussions.
The mathematical models Turchin presents consist of the usual
culprits--the exponential growth equation, logistic equation, and
second order reaction-diffusion equations (sets of two or more first
order coupled differential equations) we have seen in the past. Many
people have applied these for the past seven decades to explain such
varied phenomena as feedback control circuits, electronic devices,
predator-prey relationships, autocatalytic chemical reactions, and
chaotic behavior of climate. We have seen them too often in the context
of complexity science, which has little accomplishment compared to its
fan-fare and book sales. Historical dynamics looks slightly like an
excuse to present these same analyses yet one more time.
The book contains several other flaws that seem worth mentioning.
First, there is the usual problem with historical science by way of not
enough data to compare theories to predictions. Second, the conclusions
seem tendentious rather than objective at times. For example, in the
chapter on ethnokinetics Turchin examines actual data on the growth of
religion against a series of models and finds that growth according to
a logistic model (autocatayltic model) fits well; in fact, according to
Turchin, it "does much better relative to alternatives." Yet the data
he illustrates for growth of Christianity in Egypt suggests a threshold
model and not logistic-style growth.
Turchin's empirical tests contain too much "adhoc-icity." For example,
in his analysis of the political history of Europe from 0 to 1900 C.E.
he looks at the frontier as an independent variable and empire as the
dependent variable. These he organizes as a two-way table. However, his
measure of being on a frontier is a sum of points given by being on the
boundary between antagonistic religions (each weighted 0 to 3),
differing languages, lifestyles, and intense warfare (0 to 2). It is at
once an ad hoc scale, and also skewed, since religious differences and
strife are practically one and the same. Moreover, his measure of being
an empire is simply that of comprising an area greater than 100,000
kilometers squared. It is equally ad hoc. Such are not the ordinary
fare of two-way analysis which depends on objective, clear measures.
What we need is a sense that his analysis does not depend on his ad hoc
divisions. Yet he offers nothing in the way of a table of contrasts or
"dose-response" curves.
The biggest flaw that I see is one typical of the historian-sociologist
applying mathematics to their science. The process is more like finding
models that satisfy the need to have an explanation rather than
providing the basis of an experimental test. Certainly the models
sometimes fit well, but what do the parameters in the models mean? In
the physical sciences, we do not just apply mathematical models. We
test whether or not the models make sense. Partially this is a process
of deciding whether or not the parameters in a model are realistic. In
fact, thinking about the connection between model parameters and
physical meaning is where prediction usually begins. And prediction is
a prerequisite to hypothesis testing. Turchin touts one of his models
as containing only five parameters! To a physicist five parameters
seems just on the verge of being complex enough to lose its explanatory
power. One can fit almost anything with five parameters.
People outside of hard sciences often think that a science matures
because it uses mathematics. But this misses the point of both science
and mathematics. Science matures through definitive experimentation and
the testing of hypotheses. Mathematics is necessary for this goal, but
it is not sufficient.
.
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