But the issue is interesting to me. Like Martin, I'm also a one-time
physicist (and in some general ways am still one), and it's certainly a
part of my intellectual habitus. But it never made me into a
positivist-empiricist, even in my earliest days ... I always saw the role
of culture and viewpoint, was always fascinated by relativity and quantum
physics (my first loves) as new ways of making sense rather than as closer
approximations to a Truth.
Now there are physicists and physicists. Experimentalists tend to be much
more like their social science imitators in attitudes to research and in
the kinds of quantitative data analysis they do. Theoreticians are quite
different, I think, being more likely to see their work as generating
possibilities rather than truths (though many are quite absolutist in
temperament), and use forms of mathematical reasoning which are designed to
express conceptual relationships, to paint theoretical ideas in the palette
of mathematics, rather than to simply reduce data to summary expressions,
or compare data points to theoretical predictions. I was mostly a
theoretician by habitus, and also did 'phenomenology', which in physics
means translating abstruse theory into 'testable' models for
experimentalists, and sometimes the reverse, making data-driven
generalizations fit some sort of larger explanatory scheme.
My point here is that there are ways of using mathematics very much as a
tool of mediation for interpretive projects and for creative visions; it
does not need to be tied to Old School philosophies, especially as they are
dogmatically pronounced in the more datamanic human sciences.
While I certainly agree with David Dirlam that ecology has much to offer
social theory by way of conceptual models that have some mathematical
representations (and so some operationalizable links to observation) -- see
chapter 5 of _Textual Politics_ -- once physics caught up with ecology's
interest in non-linear dynamically coupled systems (popularly called
'chaos' theory), and dug down into the substantial, and unused,
mathematical literature (a case where pure research did turn out to later
be useful) in this field, the new conceptual models of emergent
self-organizing systems were really developed. This is what theoretical
physicists are good at. There are, unfortunately, very few theoretical
ecologists (more in the last decade or so), for all the great insights
ecologists have had into their data.
Again my point is that conceptualization mediated by mathematical models is
not inherently either data-driven or data-reduction-analytical (i.e.
'quantitative' in the sense used by many people in the human sciences).
Pedro is probably still quite correct that some people are attracted to
interpretivist research and 'qualitative' methods (ALL methods are
qualitative, no?) because they either hated statistics courses or did
poorly in them. At worst, they were poor students inadequately prepared by
their prior education to work mathematically -- which may not bode well for
the quality of their research by any method -- but, at best, they may have
rebelled against quantification and formalization for its own sake in a
field where intuitively this is not what our research programs are mainly
interested in. The autobiographical narratives in Heshusius & Ballard's
_From Positivism to Interpretivism and Beyond_ tell how even some very
successful 'quants' had second thoughts and converted to the New religion.
It also tells of grad student experiences that left people really upset
that the only legitimate way their institutions would credit them as
researchers was for quant-orthodox work. Some did well in statistics, and
some did not.
I believe that physics is an atypical science. It mostly studies systems
where generic behavior predominates and unique behavior is non-existent or
irrelevant. Ecosocial systems are certainly not like that, nor are many
phenomena pertaining to their smaller-scale component subsystems (like
people). On the other hand, a good theoretical physics habitus and training
equips someone quite well to learn and critique mathematical and
quantitative methods used in other disciplines. I never took a stats course
(thank God!), and when I read the textbooks, I gagged at their
anti-intellectualism and the lack of any mathematical insight (or even
pretense of it). They are mostly 'cookbooks' that talk down to students and
talk past their intended audience. I junked them and read more
mathematically literate accounts in the theory of probability, so I could
have a clue what 'degrees of freedom' really meant and where the
F-distribution tables in the back of the book actually came from. Some of
that mathematics is rather profound and beautiful; a lot of it requires
sophisticated prior background. On the statistics side, there is often a
lot of obscure window dressing covering very simple mathematical ideas. I
get angry to think that university students and future researchers are
forced to swallow volumes of relatively meaningless jargon and formulas
with no clue as to what its intellectual foundations are. How are people
supposed to apply it intelligently and critically? No wonder so many
students hate it, and not just because it's hard to 'learn'.
I taught a course in standard quantitative data analysis and experimental
design methods at the advanced Master's level for several years. I never
found a good textbook, so I chose a cheap and practical one. Neither was
there the time available to do things right, nor were the students prepared
to deploy the mathematical tools that were really needed, nor probably did
they need all this, since they were not going to become researchers, just
educated consumers of research. (The course was later revamped to meet this
more reasonable objective.)
Far down under all this, I sense, is quite a different problem from the
battle between Old and New schools of research in the human sciences. It is
a problem about intellectual habitus (and the lack of inculcation of it) in
many places in universities -- people and courses that don't really want to
understand the underlying issues of a subject in a critical way. And it is
a problem about the cultural reasons why mathematical and quantitative
reasoning are so marginalized in the school curriculum, despite their
obviously rather pervasive role in modern society, and their broad
usefulness in many fields that are only lately discovering them. Are these
two problems deeply connected? We know, I think, why critical understanding
and inquiry are socially dangerous. Are mathematics and quantitative
reasoning so detested in our schools, our society at large, and even in our
intellectual and academic culture, because the only forms of them that are
safe enough to permit into wide social distribution are those that are
rote, dehumanized, and anti-intellectual?
JAY.
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JAY L. LEMKE
CITY UNIVERSITY OF NEW YORK
JLLBC who-is-at CUNYVM.CUNY.EDU
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