When I studied
engineering in the Northwestern
Polytechnic University from 1978 to
1982, I was attracted to social studies due
to my strong wishes to participate in
China¡¯s social reforms. Because of my
strong social participation intention and
engineering background, I hoped all good
social researches to be scientific with
results actionable. At that moment, to me a
college student who loves mathematics, it
seems to model social systems mathematically
provides a lot more challenges and fun than
to model engineering systems. Politically, I
still trusted China¡¯s political systems
and respected its leaders. However, I was
puzzled by the many horrible decisions
China¡¯s great leaders had made in the
past. Through a lot of reading, I came to
conclude that rigorous and scientific social
studies were what China needed the most at
then. I believed that we should be able to
construct scientific social theories similar
to that for physics, and to manage social
activities as to run engineering projects. Therefore, in
1981, I decided to give up my engineering
career and started my journey to explore methods of studying social systems.
As guided by the
thinking mentioned above, in 1983, I
switched to sociology and entered Beijing
University as a graduate student. At then, the Beijing University
sociology department favored empirical
research methods that my classmates and I
got a lot of assignments to learn from
practicing questionnaire survey as well as data
analysis. We even got to conduct large-scale
surveys for
the State Council¡¯s Economic Reform
Committee, and to propose public policy
ideas to top leaders. However, results produced from these
surveys were not satisfactory, as they never
led to any good solutions but only to some
useful hints. I was a little disappointed by
these results, and thought they were caused
by my lack of advanced empirical research
skills, for which I needed to spend time to
learn.
In 1986, I
entered a Ph.D. program at Stanford
University where I took many statistics
and computing courses besides sociological
ones. With the data I collected from China,
I tried some of the advanced data analysis
tools I learned. But, it came out to me
these advanced tools were still not enough
to solve my problems that I started casting
doubts on the prevailing empirical research
practice. One day in Stanford Bookstore, I
came cross a book Making It Count by
professor Stanley
Lieberson and immediately got attracted
to it. In its introduction, professor
Lieberson wrote:
¡°There were many
failures before human successfully learned
to fly. After watching birds flap their
wings, bold and adventurous individuals
built huge wing like structures, leaped off
cliffs, flapped their wings vigorously, and
broke their necks. There are principles of
flight to be learned from watching the birds
all right, but the wrong analog had been
drawn.¡±
Then, he went on to
argue that ¡°in similar fashion, our
empirical approach to social behavior is
based on an analog¡±, like building wing-like structures to fly. I did not agree with
him on many of his arguments made in the
book. But the above analog he made became
something I never forget.
With some doubts on the
empirical social research practice, I still
moved on to learn more of empirical social
research, but my focus was on statistical
techniques and computing tools for data
analysis since I thought they will always be
useful anyway. I took many advanced
statistics courses and earned a M.S. of
statistical computing from Stanford. In
practice, in the Spring of 1989, I participated in the Beijing
pro-democracy movement and got elected to be
the founding president of the Independent
Federation of Chinese Students and Scholars
in USA after returned from China.
Partially due to this special experience, I
selected democratization as my main research
topic and conducted a few empirical
researches on it. The result of this work
led me to produce a book Patterns
and Results of the Third Democratization
Wave. However, my research and my
practice were separated from each other
then. My
research did not produce any meaningful
guidance to my practice that cast a lot more
serious doubt on my believing in empirical
social research than ever. I felt this might
be resulted from my restrained to sociology
and to quantitative analysis. In other
words,
interdisciplinary approach and quantitative
mixed with qualitative methods may cure my
problem. Here, I mean my way of collecting
data was restrained to the quantitative way
and sociological way. In general, I did not
agree with the way most scholars viewed the
qualitative data. In terms of data, I think
that qualitative and quantitative are the
same, and both can be processed by
computers.
Started in 1993, I
jumped into health economics first, then to
the studies
of social networks and globalization,
then to the fields of entrepreneurship
and international business, in order to be
interdisciplinary. All these studies,
especially the study of entrepreneurial
process, were fascinating to me. However,
more work led to more doubts for me,
especially when I had difficulty in dealing
with the subjectivity issue. The
entrepreneurial process was especially
stimulating to me. At the beginning,
entrepreneurs often do some market research
formally or informally. Then, they act on
what came out from this research. But the
results out from this process are often
different from what suggested by the early
research. However, this does not prove the
research is wrong, but only to show the
power of entrepreneurs¡¯ will and
participation. This led me to some thoughts
similar to George
Soros¡¯s reflexivity. Also, the more
work I did and the more I got to see the huge
difference between natural science and
social science, as I always looked for actionable
knowledge out from research. Definitely,
additional human thinking is always needed
together with what research suggested to
enable a good social action.
From 2000 to 2005, I
got a few opportunities to teach research
methods to Ph.D. candidates and to conduct
empirical research on democratization and
consumer behavior. This time, I encountered
another problem about equivalent
models. In analyzing social science data,
there are always tens or even hundreds of
model that can fit a same set of data very
well. How to deal with these issues became a
focus of mine work for a while, and led me
to focus on research process rather than
research results. I feel we may not be able
to obtain the so-called correct model for
any data, but still need to obtain a best
available or just a final model for our
predictive work. Therefore, to a
methodologist, what is important is not
about how to reach a final model for a
research, but the process leading to final
models. During this period, I encountered
the work done by a few computer scientists
including professor
Judea Pearl who used powerful AI tools
to assist deriving causal relationships out
from statistical evidence, and I even spent
more than 4 months as a consulting scientist
in IBM research to work on this set of
methods. Through a careful examination of
their work, I concluded that full automation
of social studying is impossible that led me
back to my idea of ResearchMaps.
From this line of work,
I became more and more familiar with the
newest IT development that can offer huge
assistance to social research. But its power
has not been fully recognized yet by the
empirical social research community. When
the newest IT development brings out
unlimited opportunities, it also brings out
great challenges like that of information
overflow. Now, I see many of our social
research problems such as that of equivalent models are
amplified by the newest IT technologies.
However, I started to believe that the
newest IT may be the only cure to our
problems or at least will create a path for
us. The newest IT Technogical developments
can make many unimaginable possible. One of
these lines of thinking led to some work as
summarized in a
2005 presentation of mine.
Excited by the IT
revolution, I decided to focus my work on
developing IT tools and IT solutions to
social research for a while. As mentioned earlier, I do
not think all the research can be automated
by computing tools or AI systems. But, IT
systems are the most powerful tools to break
down all the barriers in social research,
such as the qualitative vs. quantitative and
the single discipline approach vs.
interdisciplinary approach. With all the
newest IT tools in your hand, the world
is flat. With some IT tools, we may be
able to manage reflexivity issue as well. As
for the researches scientific and capable to
generate actionable knowledge, the ones I am
interested, I think interdisciplinary
approach is necessary, but is difficult
to implement under current research
establishment. We need the IT tools to flat
our academic research world. Here, one of
the problems is that scholars use difference
terminologies to describe the same
techniques. To cure this problem, RM4Es
is what needed, as I believe. Now, I am
developing RM4Es and its related IT tools.
To deal with the issues of reflexivity and equivalent models, I believe that ResearchMaps is truly the solution proposed and it started to get recognized now. As reflected by the unavoidable reflexivity and the existence of equivalent models, the ¡°correct model¡± of a data may not exist at all. The final model reached by a researcher actually depends on our assumptions and on our preferences together with some of our research working habits. I think it is okay for us to stop at our final model and use it for predictions. However, we do need to know how this ¡°final model¡± is different from the other possible ones so that a research map should be constructed and used to document the paths leading to our model and hopefully other possible paths leading to other possible final models. With this research map, we may guide our future directions and current actions of research. To provide ResearchMaps for others, I am working hard now to further develop the ResearchMap framework and its related IT tools.
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- June 2006
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After 2006, I obtained good opportunities to apply my RM framework to real life problems such as that of Indymac Bank, to project evaluation of international aid, and also opportunities to develop software systems of implementing my RM4Es & ResearchMap frameworks.
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Recommended readings:
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RM Publications
RM Programs
RM Platforms
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