Donna Hughes Homepage
The construction of
Donna M. Hughes
Women's Studies International
Forum, Vol. 18,
No. 4, pp. 396-406, 1995.
hate the very name
statistics, but I find them full of beauty and interest. Whenever
they are not brutalized,
but delicately handled by the higher methods, and are warily
interpreted, their power of
dealing with complicated phenomena is extraordinary. They are the
only tools by which an
opening can be cut through the formidable thicket of difficulties
that bars the path of
those who pursue the Science of man." Francis Galton,
The scientific method is a tool for the construction
and justification of
dominance and exploitation in the world. It also enables the creation
information and explanations of the natural and social world.
Recognizing these dual
functions is crucial to understanding how the scientific method is
used to provide
increasingly broad and in-depth understandings of the world and to
explain and create
stratifications within the world.
Although sexist, racist, heterosexist and classist biases in
and representation have been uncovered by scholars studying gender,
race, class and sexual
identity, the scientific method remains the citadel of scientific
authority. Science, as
an institution, remains secure in its power and authority as long as
the scientific method
is without culpability in politics. The need for a feminist critique
of the scientific
method is stated by Evelynn Hammonds (1990, p. 181),
Feminist critics have articulated a sophisticated argument about
the inscription of
gender in the language and norms of scientific practice, but they
have been less
successful in demonstrating, at least to the satisfaction of
practicing scientists, how
the scientific method, especially in the "exact"
sciences, is itself inscribed
by gender. Above all, we have yet to demonstrate how the scientific
method can provide
successful representations of the physical world while at the same
time inscribing social
structures of domination and control in its institutional,
conceptual, and methodological
The politics of domination are integrated into the scientific
method and used as a
social and political agent for those in power. Specifically, the
invention of statistics,
while being a major methodological advance in the descriptive
sciences was, and is, used
to create and support political dynamics of domination and
methods were invented over the last 100 years to support politically
The focus of this paper is on how these methods are used in a process
knowledge in a way that legitimizes paradigms of domination.
Statistical Methods and the Politics of
Positivist views of science argue that an objective scientific
method is powerful
enough to eliminate social and political subjectivity. Feminists
argue there is no
objectivity disassociated from the social and economic politics of
the inventors or users
of specific scientific methods. Even methods of mathematical analysis
are intertwined with
politics. Statistical analysis is an intrinsic part of the scientific
method and used by
every discipline in the natural and social sciences. The journal
Science listed the
development of the chi-square statistical test as one of twenty
breakthroughs of the 20th century (Barnard, 1992, p. 1).
Statistics is defined as: "a scientific discipline concerned
with the collection,
analysis and interpretation of data obtained from observation or
(Plackett and Barnard, 1990, p. 4), "the mathematics of
1943, p. 9), "the language of science"(Atkinson and
Fienberg, 1985, p. vii),
"the branch of scientific method which deals with the data
obtained by counting or
measuring the properties of populations of natural phenomena"
(Kendall, 1948, p. 2),
"an indispensable tool in all branches of human endeavor from
scientific research and
complex decision making to regulation of our daily lives" (Rao,
1983, p. 35), and
"a practical discipline for understanding the indeterministic
world that we live in
and for solving the real problems in society from agriculture,
through meteorology to
zoology from A to Z!" (Barnett, 1983, p. 7)
There is some recognition among statisticians, mathematicians and
statistics is a socially constructed method. They ask: Is it an
or a "social product"? (Bibby, 1983, p. 239) Are
"discovered" or "invented"? (Tankard, 1984, p.
138) There is a tension
between statistics as an "exact science," defined as
culture-free, [and] technique oriented" and statistics as a
product" which is "produced as the outcome of human
responses to a wide variety
of conflict-laden situations" (Bibby, 1983, p. 239). Although
some statisticians and
a few scientists are aware of the limitations of the methods and urge
caution in their
use, the social construction of statistics is often obscured or
forgotten by emphasizing
[T]here remains an insidious force within [statistics] which
towards technique. The tendency is enhanced by the fact that
'statistics as social
product' remains an amorphous and ill-formulated concept: this is
seen as a weakness in a
world where precision is a sign of strength (Bibby, 1983, p. 244).
It is impossible to separate the process of invention, discovery
and science. Efforts
to distinguish between discovery and invention or between fact and
theory are efforts to
disassociate science from its subjective context. The artificial
distinction enhances the
illusion of objectivity in science, but once the social, political or
economic history is
reconnected the subjectivity becomes apparent.
The statistical methods developed by scientists cannot be
separated from the social,
political and economic forces that motivate the research. The early
statistics were motivated to invent mathematical tools to measure and
human race. They were not interested in statistics itself as a
scientific method; they
were looking for a way to describe and prove their political ideology
of human superiority
and inferiority. The tests that comprise the foundation of
statistical analysis were
invented to provide authoritative support for the paradigms of
domination and exploitation
created by social, political and economic forces. That does not make
incorrect, or nullify knowledge that has been gained by the use of
but it does raise questions about the objectivity of the methods. It
places the invention
of the scientific method deeply within a social, political and
Many of the early inventors of the early statistical methods had
interests similar to
other nineteenth century scientists who were greatly interested in
categorizing racial and ethnic differences, especially as they
revealed perceived mental
abilities. In their pursuit of race science they invented tools and
methods to measure the
variables of interest. For example, to measure physical differences,
shape and size, among races, ethnic groups and sexes the scientists
cephalometers, craniometers, craniophores, craniostats and parietal
1990, p. 43). They also invented experimental techniques and methods
of data analysis.
These statistical inventions created new scientific methods which
enabled the scientists
to construct knowledge in new ways, all of which reinforced their
social, political and
For centuries the principles of probability have been investigated
statistics used by science and nation states to compile information,
but what today is
called statistical analysis had its beginnings in the work of Sir
Francis Galton, wealthy
cousin of Charles Darwin. Galtons goal was the mathematization
of the laws of
heredity. Influenced by Charles Darwins Origin of
Species, he drew upon the
mathematics of probability to search for the relationship among
physical traits and mental
ability between parents and their children that would lead to the
discovery of natural
laws of inheritance (Cowan, 1972a; Cowan, 1972b; Kevles, 1985).
Abraham de Moivres
normal curve became a basic tool in Galtons investigation of
physical and mental
anthropological measurements and invention of statistical methods for
(Tankard, 1984, pp. 23, 48). By studying the mathematical
relationship among physical and
mental traits Galton invented a measurement of
"co-relation." Today this measure
of "co-relation" between two variables is called the
Galton also invented a measurement of "reversion" to
describe the mathematical
stability of physical traits in a population when measured
intergenerationally. Today that
statistical method is known as regression analysis.
With his invention of these techniques Galton transformed the
concept of heredity as it
was known. Prior to his work the investigation of inheritance focused
on finding the
mechanism or "force" of heredity, with the invention of
regression, heredity became a relationship between generations that
could be studied by
measuring physical and mental traits (Cowan, 1972a).
Galton, today, known as the founder of biostatistics, biometrics
and behavior genetics,
made the previously descriptive science of biology accessible to
mathematical analysis. In
the hierarchical world of science, this transformed biology into a
Measurement has long been considered a hallmark of science
properly practiced, and once
a new discipline has developed a mathematical discourse, it has
almost immediately laid
claim, at least in the language of its most enthusiastic disciples,
to the significant
status science! (Woolf, 1961, p. 3)
Galton is also known as the founder of eugenics the science
of improving the
human race through encouraging reproduction of the most capable and
reproduction of the least capable. He planned that the mathematical
heredity, once discovered, would form the basis for a political moral
society which would lead to the improvement of the human race.
Eugenics was the single
motivator for Galtons work. Karl Pearson (Tankard, 1984, p.
biographer, and protégé wrote,
We can see that his researches in heredity, in anthropometry, in
statistics were no independent studies, they were all auxiliary to
his main object
the improvement of the race of man.
Galton (Cowan, 1972b, p. 511) wrote about the power of men to mold
the future of the
human race by the selection of progenitors on the basis of
The power of man over animal life, in producing whatever form he
pleases, is enormously
great. It would seem as though the physical structure of future
generations was almost as
plastic as clay, under the control of the breeders will. It
is my desire to
show....that mental abilities are equally under control.
Galton thought that traits such as character, disposition, energy,
physical power were quantitative and determined solely by heredity.
"natural qualities" or "talents" comprised the
social worth of a
person. Galton ranked the categories of people in the British social
structure. They were,
starting at the bottom, the "criminals, semi-criminals, loafers,
others," followed by the "very poor persons who subsist on
casual earnings, many
of whom are inevitably poor from shiftlessness, idleness or
drink," next were
"those supported by intermittent earnings they are a
hard-working people, but
have a very bad character for improvidence and shiftlessness,"
then came the
"mediocre class" of ordinary respectable workers. After
these classes came those
of higher worth, the "better paid artisans and foremen,"
followed by the
"lower middle class of shopkeepers, clerks and subordinate
professional men, who as a
rule are hard-working, energetic and sober," the last and
highest class were the
entrepreneurs and the professionals who had "the brains of our
(MacKenzie, 1981, p. 16). Galton never questioned the class hierarchy
society. He just invented statistical methods in his attempt to prove
the biological basis
for its existence.
In his book, Hereditary Genius, Galton (Tankard, 1984, p.
47) describes an early
IQ scale for the "classification of men according to their
natural gifts," and
speculated on how it could be used to measure the mental capacity of
different races. He
concluded that Negroes were two grades below whites in intellectual
abilities. Galton also
concluded that female traits were defects with no adequate adaptive
Galtons work, both eugenic and statistical, attracted
followers. Karl Pearson
(Cowan, 1972b, p. 525) later wrote of the influence of Galtons
work on their life
For some of us Galtons new calculus ......enabled us to
reach real knowledge...
in many branches of inquiry where opinion only had hitherto held
sway. It relieved us from
the old superstition that where causal relationships could not be
traced, there exact or
mathematical inquiry was impossible. We saw the field of
scientific, or quantitative,
study carried into organic phenomena and embracing all the things
of the mind. It was for
us the dawn of a new day.
Karl Pearson, as Galtons protégé, finished the work Galton
correlation and used his findings to prove that heredity had greater
control over physical
and mental traits than did the environment. In a study meant to
resolve the nature-nurture
debate he measured physical characteristics such as eye color, hair
color, and head length
on school children who were brothers and sisters, and had the
teachers evaluate the
children on mental characteristics, such as introspection,
conscientiousness and general intelligence. Pearson found similar
correlations among the
siblings in both the physical and mental characteristics. From these
findings he concluded
that since physical traits were not affected by the environment, and
the correlations for
the mental traits were the same as the physical traits, the mental
traits were equally
influenced by heredity. This meant that the influence of the
environment must be small as
compared to heredity (Tankard, 1984, p. 78).
Pearson is known in the history of statistics as the inventor of
product-moment expression of the coefficient of correlation and a
large part of the theory
of multiple correlation and regression. He is best known as the
inventor of the chi-square
statistical test for comparing the fit of observed data to the normal
curve or normal
distribution expected in a population sample. The chi-square test has
been described as
"a powerful new weapon in the hands of one who sought to do
battle with the myths of
a dogmatic world" (Peters, 1987, p. 105). Pearson wanted to make
sciences as mathematical as the science of physics. In his book
The Grammar of Science
he states that the essence of science is its method, and no areas of
human experience are
inaccessible to study by this method (Barnard, 1992, p. 4).
Pearsons motivation, like Galtons, was the
investigation of heredity and
evolution as based on eugenic principles for the biological
improvement of the human race.
Pearson is attributed with taking Galtons ideas and turning
them into a new science
(MacKenzie, 1981, p. 88). Commenting on Pearsons mathematical
papers, his son Egon
Sharpe Pearson (Tankard, 1984, p. 69) said,
The main purpose of all this work was the development and
application of statistical
methods for the study of problems of heredity and evolution; it
would certainly be wrong
to think of the Pearson of this period as concerned with the
development of statistical
theory for its own sake.
Pearson was an ardent supporter of eugenics and a socialist
reformer. Although he was
opposed to a society stratified by wealth, he was not an egalitarian.
He thought education
and culture determined the value of a person in society. In his view
the group that should
have the highest standing and power in society was the professional
middle class. He was
quite concerned that the "lower" classes of people not
become too powerful.
Pearson thought that natural selection had to be replaced by
artificial selection to
ensure that the 'unfit' did not out breed the 'fit' in a socialist
1981, p. 84)
Pearsons politics and scientific studies lead him to write
papers opposing Jewish
immigration into Britain (Tankard, 1983, p. 62). According to
Fredrick Henry Osborn, an
American eugencist (Tankard, 1983, p. 62), "Pearson shares the
possible the dreadful misuse of the word eugenics in Hitlers
The quantitative methods invented by Galton and Pearson added the
power and authority
of numbers to their science and ideology. Galtons work,
followed by Pearsons,
made heredity accessible to mathematical scientific study.
Galton developed a definition for heredity which was limited and
meaningful, a definition which could be researched. In so doing
Galton managed to bring
order where there had been chaos; he managed, in short, to simplify
a situation which
previously had been hopelessly complex (Cowan, 1972a, p. 403).
Eugenics motivated the invention of statistical techniques and the
emerged. The newly defined science of heredity enabled scientists to
investigate the conceptual dualism of nature and nurture. For Galton,
and the other
eugenicists, all was nature. The politics of domination and
exploitation of the time were
inscribed into the methods and the science.
Eugenic doctrine was antiurban at a time when fear of the cities
was becoming rampant.
It was racist at a time when the conflicts between the races were
apparent, in the United States and in the British Empire, at home
and abroad. Most
significantly, eugenic doctrine congratulated Anglo-Saxons on the
superiority of their
civilization at a time when they were beginning to feel insecure
about their role in the
world. (Cowan, 1977, p. 201)
Galton and Pearsons goal to transform the study of
heredity and evolution
was successful. Their statistical techniques, correlation, regression
and the Chi-square
test, introduced quantitative methods to the descriptive sciences
which enabled scientists
to construct knowledge in a way that had never been done before. In
the next phase of
invention of statistical methods, the new techniques furthered the
social construction of
knowledge, and added the social construction of objectivity.
William Gosset contributed to statistical methods by inventing the
t-test. He worked as
a brewer for the Guinness Brewery his entire life, although he kept
in close contact with
the other inventors of statistical methods by correspondence and he
spent one year
studying in the Galton Laboratory at The University of London with
Karl Pearson. Guinness
Brewery would allow Gosset to publish his work only if he used a
pseudonym and if none of
the brewerys data appeared in the papers. Therefore, all of
were published under the pseudonym of "Student"
explaining why for years
this statistical test was known as the Student t-test.
Gossets work represents a shift in the invention of
statistics. Up until then the
work in statistics focused on studying relationships among variables
by methods of
correlation. Gosset introduced the problems of experimental control
and the significance
of differences. His statistical methods were invented in response to
the needs of the
brewery. He needed to know the accuracy and reliability of results
derived from small
sample sizes. The t-test enabled him to determine if differences
ascribed to experimental
results could reliably be due to experimental treatment, not chance.
Gosset published his
invention of the t-test in 1908, but the other biometricians of the
time were more
interested in studying traits in large human populations, so the
t-test went unused for
Ronald A. Fisher extended the concept of a test of significance.
greatly influenced the areas of statistical methods, experimental
design and genetics. He
is the inventor of the statistical method the analysis of variance.
Like Galton and
Pearson before him, eugenics was central to Fishers career.
Natural and artificial
selection featured strongly in his work on theoretical genetics and
experimentation. This scientific focus is consistent with his social
support for eugenics.
He favored use of scientific selection to mold the population of the
(MacKenzie, 1981, p. 190) said,
Biometrics can effect a slow but sure improvement in the mental
and physical status of
the population; it can ensure a constant supply to meet the growing
demand for men of high
Fishers new methods quantified Gossets statistical
differences. A question
that arose in determining the reliability and repeatability of
experimental results was to
what degree could the findings be relied upon. Fisher invented a
statistical test that
determined significance levels for experimental results. He (Cochran,
1976, p. 13)
explained it this way:
[T]he evidence would have reached a point which may be called
the verge of
significance; for it is convenient to draw the line at about the
level at which we can say
Either there is something in the treatment or a coincidence
has occurred such as
does not occur more than once in twenty trials. This level,
which we call the 5
percent point, would be indicated, though very roughly, by the
greatest chance deviation
observed in twenty successive trials. Personally, [I] prefer to set
a low standard of
significance at the 5 percent point, and ignore entirely all
results which fail to reach
Fishers arbitrary decision to set the point of significance
at the five percent
level still holds today in drawing conclusions from experimental
results. Gosset and
Fisher invented ways to quantify the significance of experimental
results and findings of
"differences." These tests are essential to the scientific
method. When data is
analyzed by statistical methods, the reporting of significance levels
The establishment of a way to determine differences between
variables and the
quantification of the significance of the differences marked the
addition of a
quantitative determination of objectivity to experimental results.
>From now on, variables
could be quantified, tested for significant differences and declared
to be objective
findings of the scientific method by adding the authority of level of
variables are compared and found to be significantly
different, the results
acquire the authority of fact, truth, or objective
Fisher introduced another experimental design concept the
null hypothesis. The
null hypothesis is the assumption in statistical methods that there
is no significant
difference between two variables (or experimental treatments,
whatever is being measured).
If statistically significant differences can be found between the
variables, then the null
hypothesis can be rejected. If significant differences are not found,
the null hypothesis
cannot be rejected. In research laboratory practice this is a
negative result, a failed
experiment. Findings of significant differences are the positive or
successful results in
research. Experiments are designed to look for differences. R. A.
Fisher (Tankard, 1984,
p. 127) said, "Every experiment may be said to exist only in
order to give the facts
a chance of disproving the null hypothesis."
Scientific methods of experimental design and statistical methods
and determine "differences." Determinations of differences
and their explanation
are considered to be progress, to have advanced scientific knowledge.
No such procedure is
used for measuring and confirming sameness. Sameness is not much of a
question in science.
Experimental findings of sameness (no significant differences) are
The above described statistical methods make up a central part of
method. The men who invented them were either influenced or motivated
ideology. Their goal was the explanation of social, political and
among people by differences in heredity. They envisioned a future
society where artificial
selection of people to reproduce would replace natural selection.
With the use of the new statistical techniques the construction of
biological sciences, such as heredity and evolution, shifted from
descriptive analysis to
mathematical analysis. The use of these apparently more sophisticated
techniques enabled the men to transform the study, reporting and
analysis of the sciences.
They used the new techniques to construct scientific knowledge to
conform to their
political ideology of eugenics. By cloaking their ideas with
"objective" analysis that qualified their ideas as the
leading science of the
times, they were able to explain, justify and enact the social,
political and economic
oppressions and exploitations of the time.
These statistical techniques became part of the basic scientific
method in designing
experiments and analyzing results. The statistical methods of
determining and quantifying
differences became a standard methodological technique in science.
Statistics, Knowledge and
A fundamental principle in the implementation of domination and
exploitation is the
construction of the dominant group as the norm and the subordinate
group as the
"Other." For science to serve the powerful, its methods
must play a supporting
role. Statistical methods were invented as a way of knowing by men
motivated by eugenic
politics. It continues to serve as a tool for analysis and validation
results, from which the findings can be declared to be
analysis serves in the verification and establishment of
differences," by "objectively" determining whether
populations (or samples
of populations) are the same or different. Any people politically,
economically outside the dominant group are identified and studied by
psychological and social sciences. Scientific investigation has great
groups who are socially and politically defined as "Other,"
such as women,
lesbians, gay men, African-Americans, Latinos, the old, the poor, the
"difference" between groups has been established as fact by
the authority of
"objective" "neutral" science, the powerful can
act, all the while
believing in and justifying their actions because of the proof
supplied by scientific
methods. While enabling investigation in every field of study
statistical analysis has
also aided in the social construction of dominance by giving
scientific authority to the
construction of reified categories which lead to the objectification
I have constructed a five step process for the scientific
construction of the
"Other:" 1) Naming, 2) Quantification, 3) Statistical
analysis, 4) Reification,
and 5) Objectification. This five step description is not a linear
process; it is circular
and interactive, with each step legitimating and reinforcing the
previous and following
All scientific investigation is conceptualized from a social,
political and economic
context. What is worthy of measure and analysis is that which has
social or aesthetic value to the dominant group the people
with economic, social
and political power. What is measured is often important to the
maintenance of the present
structure and balance of power. In the scientific method the first
step is to name and
define the variables to be studied and analyzed. Naming and defining
of variables is an
essential element in the construction of knowledge and consequential
exploitation. Once something is named it is made visible and real.
Concepts can be
constructed around it which are then used to explain experience and
In addition, the variables measured and the attributes assessed by
the variables depend
on what can be measured. A brief look at the history of the
scientific study of
women reveals that when skull size could be measured, the science of
constructed theories of intelligence (Gould, 1981). When sex hormones
could be measured,
the science of endocrinology constructed theories of femininity and
and Wijngarrd, 1991). When brain laterialization could be measured,
the science of
neurobiology constructed theories of verbal and visuospatial ability
(Bleier, 1987). Not
surprising, considering mens domination and womens
subjugation, women were
always found "objectively" to be inferior to men. Variables
are not assessed
without social history and meaning attached to them. The reason the
variables come to the
attention of scientists is by the social, political or economic value
or meaning attached
to them. Often times variables are measured because new techniques
have been invented to
measure them .
Helping to strengthen the naming is the use of metaphor and
analogies. Metaphors and
analogies are used to construct scientific theories which link
systems of oppression. For
example, in the 1800s women were demonstrated to lack intelligence
because they were more
like the "lower" races, while "Other" races were
proven to be inferior
because they were like women. The metaphors "functioned as the
that without them the science did not exist " (Stepan, 1990, p.
30). The theories,
constructed from the analogies, were then tested by assessing
variables that could be
measured like skull size.
In constructing knowledge, variables can always be found to
measure. New variables are
"discovered" and named as new techniques are invented which
enable them to be
measured. This is a process by which new information and
understandings of the world are
made. In and of itself, this is not a problem, but when social,
political and economic
forces influence the naming and construction of variables, the result
is the scientific
construction of ideas which support the perspective and power of the
Once variables have been named the next step is quantitative
Quantification creates the scientific illusion that subjectivity and
politics have been
transcended. Numbers, in and of themselves, proclaim objectivity. The
power and authority
of the scientific method established by statistical analysis is based
on the idea that
numbers are the ultimate expression of objectivity. Numbers are used
to construct meanings
to present views and support theories. When the perceived objectivity
of numbers is added
to ideas, the value and power of the ideas are enhanced.
As the social and political value of quantification increases,
what can be expressed in
numbers also takes on a greater meaning. Once something is expressed
in numbers it quickly
lends itself to further mathematical analysis, the more complicated,
the more prestigious.
If concepts and theories can be expressed in numbers, the ideas
themselves take on greater
objectivity and authority. This esteemed value is socially
constructed. Thomas Kuhn
(Woolf, 1961, p. 31) states:
Both as an ex-physicist and as an historian of physical science,
I feel sure that, for
at least a century and a half, quantitative methods have indeed
been central to the
development of the fields I study. On the other hand, I feel
equally convinced that our
most prevalent notions about the function of measurement and about
the source of its
special efficacy are derived largely from myth.
In addition, the serial nature of numbers easily allows the
ranking of measurements and
the creation of hierarchical relationships. Differences can be
quickly determined and
evaluated by statistical methods. As stated in one statistics text
(Phillips, 1982, p.
133), "Virtually any kind of difference can be tested for
The only requirement is that the data be expressed numerically."
Quantification is seen as an important step in the scientific
observations. As variables are quantified they take on greater
authority and lend
themselves to further mathematical evaluation.
3. Statistical Analysis Difference and
The creation of "difference" is essential for the social
construction of the
"Other." The scientific method makes that difference appear
to be just the
facts. The inventor or user of these methods appears to be powerless
to influence or
control the outcome. The distancing of the observer and the observed
creates the illusion
of objectivity, from which the "facts" emerge from the
proper implementation of
the scientific method. As stated in one statistics text (Mather,
1948, p. 12),
"Statistical analysis must aim at making the data tell their own
story in such a way
that their true value and degree of trustworthiness may be accurately
Statistical analysis and the scientific method take on the
appearance of being detached
from any social, political or economic forces. The data or numbers
are perceived as
telling the story, not the researcher or theorist. Also, increasingly
within statistical analysis give the impression of being more
finders." Most techniques of data analysis enable a
decontextualized practice of
Exploratory data analysis is dangerously empiricist it
risks encouraging the
notion that knowledge somehow 'arises out of the data,' it
downplays prior knowledge and
the role of theory (Bibby, 1983, p. 279).
In data analysis following the implementation of every statistical
method is the test
of significance. In experimental research this is the determiner of
success or failure of
an experiment, and whether knowledge has been added to the field. The
elevation of this
test to this status has been referred to as "the canonization of
significance." The test of significance is the adjudicator for
the value of
experimental findings, of whether a significant truth has been
discovered. "The only
purpose of the experiment seems to be to test significance, and
thereby the problem is
considered solved." (Hamaker, 1982, p. 665)
Statistical analysis becomes a powerful tool in constructing the
premise for domination and exploitation of an oppressed group is that
"Other" is not the same as the dominant group.
exploitation would be impossible to sustain if "difference"
was not created and
maintained. Difference is equally important for statistical analysis.
Variation of individuals in a measurable characteristic is a
basic condition for
statistical analysis and theory. If uniformity prevailed there
would be no need for
statistical methods. (Cox, 1992, p. xxvii)
Statistical analysis serves as a process through which measures of
variables can be
transformed into objective facts and knowledge. The findings of
differences" validates constructed ideas about
populations. If "differences" are proven by scientific
scientific proof exists that the "other" is not the
same as the norm.
These findings hold great political power in constructing theories to
"differences," and the eventual inferences that are drawn.
Oppressor classes can
feel secure in their social, political and economic domination, and
internalize their oppression as the "fact" that they really
4. Reification Interpretation and Ranking
Reification is the transformation of abstract concepts into
concrete entities. It is
the next step in constructing the "Other" from
scientifically collected and
analyzed data. In this step variables that are measured are
constructed into entities and
given meaning. Whatever difference has been found and analyzed to be
"significant" is interpreted to further knowledge, verify
or disprove theories
and validate and reinforce social, political and economic structures.
The process of
science produces information and meanings, which are used to
make decisions and
formulate further study.
Stephan Jay Gould (1981, p. 24) has described the process of
reification in the
scientific construction of "intelligence." The
"wonderfully complex and
multifaceted set of human capabilities" were reified into the
entity known as
"intelligence," which was then further reified into a
single number known as the
intelligence quotient or IQ score. The reified entity was then
measured and analyzed among
men and women, and whites and "Other" races, with the
results confirming that the dominant group was more
The reified differences and meanings further the construction of
Differences are assigned value, which legitimizes and promotes
exploitation. Identities based on these differences are created.
stratifications are argued. The "Other" is made.
Robyn Rowland (1988, p. 2) has described the social construction
identity by the reification of difference.
I argue that men have created an identity for women, based in
biology, which is
intended to reinforce difference and to tie women to a
natural position in
such a way as to make woman the negative or other.
Through patriarchy men
direct and try to impose this self on woman for the purpose of
controlling her and
maintaining woman as a serving class for men.
After naming, quantifying and analyzing the variables, they are
ranked. Complex and
abstract qualities are reified into single entities to be ranked in a
hierarchy of social,
political and economic value. Sex, skin color, age, sexual identity,
culture, and economic
class once reified into meaningful social and political entities by
the powerful, become
determinants of power and privilege or powerlessness and
is not just an illusion to the reified: it is also their
reality" (MacKinnon, 1982,
In the reification step the differences measured in a variable are
according to the theory being tested. Differences in variables such
as skull size and sex
hormones are reified into determinants of abilities and behaviors on
political and economic domination can be justified.
In objectification, the last step of the scientific construction
"Other," the full social, political and economic
implications of the integration
of the politics of dominance and the scientific method are revealed.
the process of turning a subjective entity into an object. The
quality of objectivity so
highly valued in scientific methodology is shown to be closely
related, if not the same
thing, as the process of turning an entity into a thing, an object
quality of the "Other."
Objectivity is seen as crucial to the process of science.
Objectivity is what is
supposed to prevent social and political subjectivity from skewing
scientific results. One
part of the construction of objectivity thought to be needed for the
proper conduct of
science is the distancing of the object of study from the scientist.
have noted that the objectification of a person or group is the
starting point for
violence against the person or group (Barry, 1979, p. 253). It has
been further noted that
the distance created by objectivity is "perhaps roughly the same
for pains infliction." (Baldwin, 1992, p. 50)
Connecting the objectivity of the scientific method with
objectification, or identifying them as the same thing, forms the
final link in the
integration of the politics of domination with the scientific method.
MacKinnon (1982, p.
Objectivity is the methodological stance of which
objectification is the social
process. It unites act with word, construction with expression,
enforcement, myth with reality.
Another way in which the politics of domination through science
ensures the continuing
stratification of power is the institutional discrimination against the
"Others." The exclusion or invisibility of women,
"Other" races, the
poor, the disabled, and gays and lesbians from participation in
science ensures that their
status as objects is maintained.
This interactive five step process of the scientific construction
"Other" reveals the integration in form and function of the
domination with the scientific method. "Statistics is a part of
the technology of
power in a modern state" (Kapadia, 1983, p. 170). Statistical
analysis, as part of
the scientific method, serves the powerful by constructing knowledge
and meaning; it is a
way of knowing and controlling the world.
More and more scholars of gender, race and sexual identity are
analyzing how these
identity classifications are used to construct social reality.
Biological determinism has
long been shown to be sexism, racism and heterosexism at work under
the guise of science.
The objectivity of science has long been suspect or rejected. The
outcomes of scientific
study on "other" groups are frequently observed to be
reinforcement for politics
of domination. The continuing social stratifications by gender, race,
identity has led Sandra Harding to ask, "Is it possible that
medical, and technological research in societies stratified by race,
class and gender
actually increases social stratification?" (1991, p. 36;
emphasis) If the scientific method is deeply implicated in
constructing differences then
more research on differences leads to more reification of differences
objectification of the "Other."
The use of the statistical analysis in the scientific construction
goes beyond research in the natural sciences; it also includes all of
the social sciences.
The predominant research method in the social sciences is the use of
to study people and society (Tankard, 1994, p. 1). For example, in
analyzing her research
on the homeless, Anne Pugh (1990, p. 108), observed that
"statistics contribute to
the formation of a new ideology or stereotyping."
The continual reification of differences that occurs in the
natural and social sciences
insures that the paradigms of domination and exploitation will never
change. The only
changes may be the variables. The resurgence of the womens
movement in the last 25
years has generated much scientific research on gender and gender
differences, but have
the findings brought about more than incremental progress for women?
I am reminded of the
words of Audre Lorde (1984, p. 112) "[T[he masters tools
will never dismantle
the masters house. They may allows us temporarily to beat him
at his own game, but
they will never enable us to bring about genuine change." This
thought raises a
question about the value of continuing to measure and analyze
between dominant and subordinate groups, no matter the good
intentions of the researcher.
At least it indicates the need for further thought on the use of the
scientific method as
a tool for social, political or economic change. As MacKinnon (1983,
p. 639) states
"the equality of women to men will not be scientifically
provable until it is no
longer necessary to do so."
The scientific method is as deeply implicated in the social
construction of paradigms
of domination and exploitation as any other institution in society.
The invention of
statistics was politically motivated and statistical methods are part
of a process that
scientifically constructs the identity of the "Other"
an essential step
in justifying domination and exploitation. The integration of these
politics of domination
into the scientific method means, not only, that the scientific
method is not objective,
but that the scientific method itself is an agent for those with
social, political and
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