v3.02
Material used solely for educational purposes in ESLE 301,
Theory and Methods of Research, at the University of
Connecticut.
chapter 14
Theories, Maps, and Models
from: The Science Game by Neil Agnew, 1969
A theory, or a map, or a model is an abstraction, and
abstractions involve representing the part of the world under
examination by a model of similar but simpler structure.
The important point is that theories are simpler than the data
they are designed to represent. Theories are built (1) by squeezing
some parts of experience together-all blacks, or all smokers, or all
Southern Democrats-and (2) by ignoring or omitting some
information, such as the differences that exist between
blacks, or between different smokers, or between different
Southern Democrats.
WHY BOTHER WITH THEORIES? No Other Choice
We propose that the most important reason for bothering with
theories is that we have no alternative. We would have an
alternative if we were like some wondrous computer that
(1) saw, heard, and felt everything, (2) had a massive and
unlimited memory file so we could store each bit of information
separately and permanently, and (3) could draw at will from our
memory file each bit of information and experience for examination.
Obviously, we are not like this. We listen, look, and feel selectively.
We also forget, condense, and distort the information we do
have. We tie bits of information together in our heads that
are not necessarily tied together in the world around us. We
are, in fact, information screening, condensing, and relating machines.
The end results of this process are theories or mental maps of
what goes together and what leads to what. If it were
otherwise, we would go crazy from the great avalanche of
detailed hits of information and experience to which we are
exposed both from the outside and from the inside.
You will recall that when the psychiatrist is faced with too
much information or too many alternative suspects he develops
biases or theories about what to look at and about what leads
to what. Some psychiatrists focus on biochemical information
and some on early training. The important point is that by
focusing on certain types of information, by developing biases,
and through forgetting, we reduce the avalanche of information
and experience to manageable size.
Like the psychiatrist, the scientist and the citizen
increasingly face information and opinion overload. Like the
psychiatrist, we too must develop simplified pictures,
stories, models, or theories of what goes together and what
leads to what. Through experience, training, and bias we
group together certain people, objects, or events, at the same
time ignoring many differences. We may group all blacks
together. Even if we do it on the basis of color, we must
ignore the fact that many non-blacks are as dark as many
blacks. We may go beyond simple classification and, on the
basis of selective experience, bias, or training, conclude that
blacks and low intelligence or laziness go together without
considering the question of how many exceptions there are to
this theory or picture. Others may say that low intelligence
and laziness are strongly tied to early environment, ignoring
the role which inheritance may play. We develop theories
about women, men, communists, Democrats, Jews, WASPS,
and Irishmen, the rich, the foreign, teachers, electrons, liquor,
and LSD. To the extent that we omit critical information, the
results of our oversight or error come home to roost, causing
us varying degrees of trouble. To the extent we can screen
out information contrary to our theory or bias, we continue
blithely on our way.
So we propose that the first reason for bothering with
theories and maps, those simplified pictures or stories of our world,
is that with the information-processing equipment and ability that is built
into us, we have no other choice.
Simplify Decision Making
Another reason for bothering with theories, maps, hypotheses,
or hunches is that they simplify our decision making. This
point is closely tied to the fact that we have no choice but
to develop and act on theory because of the nature of the
beast (who distorts, omits, rejects, and selectively receives
and combines information) and the nature of the world around us
(with the fantastic amount of information bombarding us each second).
All of us base many of our day-to-day decisions on hunches,
points of view, biases, or theories that we have developed
over the course of time. Some of us have the ability to formulate
a point of view very quickly, particularly if we have little information
about the issue. It is much easier to develop a theory if you are
relatively ignorant about the area in question. As one national leader
replied to a reporter, "I would have a ready solution if I didn't know
so much about it."
In any case, there is no doubt that theories do simplify
decision making by providing us with decision guidelines.
These guidelines are generally in the nature of a reduction
in the amount and kind of information we consider, and
also in the number of possible alternative decisions we might
formulate. In other words, the thousand and one potential
decisions we might make on any question are reduced to one,
two, or three merely because we have a theory
which channels our thinking along certain lines and not
others.
Theories Are Fascinating
A third reason for bothering with theories is that, for many
people, theories are exciting to develop and discuss,
regardless of whether the theory concerns why Cathy and Bill
split up or why the stock market took an unpredicted and
painful downward trend just after we made our purchases.
Most of us, when faced with an unexpected event, have a
strong desire to explain what caused the event or how it
occurred. It's like a puzzle; we worry away at it until
we've got some explanation that satisfies us. It's
particularly gratifying if our theory is some dramatic or
startling recombination and others can be swayed to accept
our new interpretation.
Predicting the Future
A fourth reason for bothering with theories is our need to
predict the future. We need to predict what will lead to
what even when we lack necessary information. The.
predictions may range from attempting to decide which of
three job offers likely gives you the best chance of
promotion and development, to predicting the future effects
of continued smoking or of air
pollution.
Scientist and non-scientist all daily act on predictions. We
use the weatherman's predictions to help us decide what to
wear and whether to leave earlier because of predicted snow
or sleet. We predict that the car will start, or if this prediction,
much to our dismay, is disconfirmed, we predict that the
public transportation system will be operating, that the driver is sober,
that the brakes are sound. We predict that the water supply is pure,
the cook is clean, the judge is honest. We predict that in
our absence our roommates will not die, and our apartment won't be
burgled. Thus we're constantly operating on the basis of a variety
of predictions of varying probability, often without recognizing it.
Rewards from the Scientific Community
Finally, theories are important for scientists because the
academic and scientific communities offer a variety of
rewards to people who build acceptable theories and who test
them. The eminent men and those to whom the accolades of
science are awarded are usually the theory builders.
In summary, we have theories, or simplified pictures of
various parts of the world, because we have no choice.
Second, we use them as decision making guides through a storm
of information, opinion, and experience impinging
on us from all directions. Third, for many, constructing
stories about the past, present, and future is exciting.
Fourth, theories about what is likely to happen assist us to
move into the future with some confidence. Finally, the
academic and scientific communities reward theory builders
and testers.
In the final section of this chapter we will develop some
yardsticks which can be used to help us evaluate the adequacy
of a theory. Before doing that, however, we will briefly
examine one way science can be viewed-as a love
affair.
BUILDING MODELS
Theory building becomes a game of building models, or
pictures of the world. Some models are based on how we see
the world through our own eyes, other models are based on how
we see the world through an ordinary microscope. There are
models based on how we see the world through an electron
microscope, and models based on how we see the world through
a telescope, or how we see the world through the eyes of a
protestant biochemist, or how the world looks through the
eyes of a Catholic gynecologist. Once a researcher or a
theorist has stabilized a picture or a model, it usually
requires a great deal of time, data, argument, and turmoil before
he changes its super-structure. In other words, if the data coming in
through his own research, or the research of others, does not
fit his picture or model, he is more likely to question
the adequacy of the data, or the competence of the researcher
than he is to question the adequacy of his model or picture.
A Love Affair
Since any experiment is open to criticism, the theorist
always has a way out in rejecting unwelcome data. The
rejection of a theory once accepted is like the rejection of
a girl friend once loved-it takes more than a bit of negative
evidence. In fact, the rest of the community can shake their
collective heads in amazement at your blindness , your utter
failure to recognize the glaring array of differences between
your picture of the world, or the girl, and the data. You will
perhaps find it easier to understand some of the excitement
and despair in the world of science if you view research as a
love affair between the investigator and his project. During the
initial courting stage he is open to certain kinds of information.
But as he invests more time, energy, and money in the
courtship, he becomes almost hostile to any information
threatening the relationship. Perhaps as the data comes in,
he has private moments of uneasiness which he shares with no
one-as he analyzes the data he may have moments of agony-but
it takes more than one or two lovers' quarrels to break up a
love affair, which is just us well. If it were otherwise
there would he almost no marriages, just as there would he
very few, if any, worthwhile results from research. Fly-by-night
relationships in almost any field yield little that is memorable or
of lasting interest.
We suspect there are those who would disagree violently with
this love ;affair model of research. They will say that the
researcher must be completely dedicated to objectivity, that
he/she is only interested in the truth. Perhaps there are researchers
like that. We haven't met enough to fill a phone booth. We have,
however, met many researchers who can be brutally objective
about someone else's research project, or about someone else's girl,
but not about their own.
But you are no doubt wondering what happens after a while-
does the love affair model shift to the marriage model? Yes,
we believe so. After working with a project for a long time
we gain some objectivity and can accept some of the limitations
and restrictions of our model. Many of us will still keep our
serious family quarrels to ourselves. The very serious and
established researcher can afford to joke in public about the
possible limitations of his model, and speak philosophically
about the relativity of truth in science. But if you are wise
and humane you'll no more join him in making fun of his model
than you would join him in his very personal game of making
pseudo-fun of himself, his wife or his dog. As you know, making
fun of something you love or cherish is one thing, having someone
else do it is quite another.
THEORY EVALUATION
We proposed earlier that we bother with theories for a
variety of reasons: (1) We have no choice in that we are
theory-manufacturing or information-condensing organisms; (2)
theories make decision making simpler; (3) theories are
fascinating; (4) theories help us make predictions about the
future, and; (5) theory production and testing are rewarded
by the academic and scientific establishments.
Therefore, while there seems to be a variety of reasons for
bothering with theories, how are we to decide on the adequacy
of one theory as opposed to another? Generally speaking a
theory is useful to the extent it provides us with acceptable
information in a shorthand or economical way, that
assists us in making decisions and approaching our goals,
or at least appears to help us avoid frequent high cost
errors.
More specifically, if we are comparing one theory with
another we can use the following guidelines: (1) Which theory
is the simplest to learn and use? (2) Which theory is more
readily open to test? (3) Which theory provides us with sufficiently
relevant and precise information at each step in our decision
making in dealing with the question at hand? (4) Which theory
provides us with the most unique and original information or allows us
to predict the most new facts or solutions? (5) Which theory
best fits with other accepted facts on theories? (6) Which theory is
internally consistent, that is, doesn't contradict itself?
Simplicity
We like simple theories because they are easy to remember and
to apply. Scotsmen are stingy, Englishmen are cold, blacks
are lazy, Jews are pushy, Wasps are self-righteous, spare the
rod and spoil the child, GM products are better than Ford
products. While these theories or condensations are simple,
they are obviously very imprecise; nevertheless, some are
widely held. So, right or wrong, the simplicity yardstick is one of
the most important. This is particularly so when, even though
the theory is wrong, we personally don't suffer from its application.
If, on then other hand, the application of an imprecise theory
obviously does lead to our discomfort, we become interested
in examining its relevance or its precision. Thus parents
come to psychologists saying, ''even though I've whaled the
daylights out of him, he still misbehaves. In fact, he seems
to be getting worse." Such people are then ready for a more
precise and more complex theory. Such theories might state,
"On some occasions some children respond better to reward
than to punishment," and for a more detailed background of
this theory we might even be prepared to invest in and study
a book on child rearing. Or, if the problem at hand is buying
a new car, we may, through bitter experience, be forced to
subscribe to the theory that only in certain years are some
GM models better than Ford models, and acquaint ourselves
with the theories or condensations of such publications as
Consumer Reports. Notice, then that increased precision is usually
purchased at the price of increased complexity in our theories.
The general rule is: The more accurate we want to be, then
usually the more complex the theory, and the more information
we have to include in reaching our conclusion.
You can usually spot a simple theory by its emphasis on one
or two bits of information: behavior depends essentially on
race, or behavior depends essentially on early training, or
behavior depends essentially on biochemical factors, or
behavior depends essentially on punishment, or behavior
depends essentially on the institution that you are working
for.
While any one of these one-cylinder theories may have some
validity, the more precision we want in our solution, the
more likely we will need to combine these one-cylinder
theories into multi-cylinder theories; behavior depends on
intelligence, and on early training, and on genetics, and on
biochemistry, and on work institutions.
So we face the problem of reaching a balance between
simplicity and precision. If we want to predict the
developing behavior of a child, we may have to combine the
series of one-cylinder theories. If, however, we merely want
to predict the behavior of a particular bus driver (e.g.,
when he will come to our stop), we will usually be adequately
accurate by consulting the bus schedule published by the institution
that employs him. In most cases it would be irrelevant to
worry about his intelligence, his early training, his genetics, and his
biochemistry.
Therefore it is not a question of simplicity versus complexity, it is a
question of whether a theory or condensation includes enough
information to meet our needs or help us make a decision.
If we want to understand or predict complex human behavior,
then theories, of necessity, must be fairly complex because (a)
people differ, (b) they learn, (c) their behavior changes
from one situation to another, and (c) they change with age.
Therefore any time you encounter a theory about human behavior
which is based on the assumption of stability, you will realize that
such a theory leaves out a great deal of information. Examples
include theories about introverts and extroverts, depressives and
nondepressives, laziness and activity, responsibility and irresponsibility, etc.
The reason why these theories have some appeal is: (1) they are
simple, and (2) there are a few people who fit them. But they
leave out most people. Most people are sometimes extroverted
and sometimes introverted, sometimes
lazy and sometimes active, sometimes responsible and
sometimes irresponsible, sometimes security-seeking and
sometimes risk-taking. Therefore the next time you hear a
speaker describe a theory about human behavior that divides
people into a few simple classifications you can bet that
he is leaving out a great deal more than he is including, and
that the major appeal of his theory is its simplicity.
Testability
While simplicity and personal appeal are two very important
yardsticks in theory evaluation, the yardstick of
testability is one which is presumably the most important for
science. Think for example how you would go about
testing the theory that southerners are less intelligent than
northerners. It would be a relatively simple matter if we
wanted to test the theory that that northerners are taller
than southerners. We would obtain a nonelastic ruler and
measure a large random sample of northerners and a large
random sample of southerners. But intelligence tests are
elastic rulers-the scores depend on (a) how the tests are
administered and by whom, and (b) whether the people being
tested and compared have been exposed to similar educational
opportunities. Perhaps eventually some researchers will
develop an acceptable test of intelligence that is as nonelastic
as a tape measure, or at least not as elastic as the tests we now
have, but, until better tests are available, the theory is
relatively immune to test.
Similarly if we wanted to test whether GM products are hotter
than Ford products, we need a series of nonelastic yardsticks
of what we mean by better and then we need to measure (test)
a large number of different cars manufactured by the two
companies. The reasons that make some theories difficult to
test or evaluate include the following: (1) lack of
nonelastic yardsticks; (2) inability to agree on which of the
available yardsticks to use; (3) inability to measure a large
representative sample of the population we are theorizing
about; and (4) citizens and scientists who refuse to change
their minds even in the face of new information. With some
theories it is difficult to agree how they should be tested,
and with others we are not prepared to invest the resources
necessary to test them.
Novelty
Theories which lead to surprising or novel information are
highly valued. Thus theory A raises few eyebrows, stating,
"Students will get higher marks if they do one hour's study a
day for ten days rather than if they do ten hours a day for
one day." Eyebrows shoot high, however, if the theory states,
"Students will get higher marks if they are exposed to a tape
recording of lecture notes for one hour a night while they
sleep, for ten nights, than by spending one hour a day for
ten days studying the same material." Of course, theories
that lead to novel or surprising information are not
necessarily readily accepted. Unless such theories lead to an
overwhelming amount of evidence, or permit a large number of
researchers to test them readily and obtain the same results,
these new findings may languish for many years in obscure
journals until more and more evidence accumulates, or until
the biases and attitudes of a sufficiently large number of
the population change so that the new information becomes
acceptable.
Goodness of Fit with Other Facts and Theories
As we noted at the outset, a few new facts do not change a
well-established or lead to the acceptance of a new theory.
This is not so merely because some scientists are biased, but
rather because we all use familiar theories to evaluate new
information_to help us in our decision making. If we gave
every new bit of information or theory careful consideration,
we would be overloaded with work in ten seconds. For example,
drug companies put hundreds of new drugs on the market each
year, and only a few can be adequately evaluated merely
because of the time and effort required. Furthermore,
thousands of research studies are published each year, but
only relatively few are repeated (replicated) by other
investigators. Most investigators are busy preparing to
publish their own research.
There is no simple solution to this problem other than using
our own personally accepted theories, or small modifications
of them, as guide-lines in helping us decide what we will
read and examine carefully.
Internal Consistency
Another way of classifying or evaluating theories is to
assess their internal consistency. This is perhaps one of the
minimum conditions a theory must fulfill if it is to bo
seriously considered. A theory which contradicts itself on
any specific question proves embarrassing at times, even
though, taken separately, each part is acceptable. Consider
the following examples: (1) He who hesitates is lost and
fools rush in where wise men fear to tread; (2) "Colonel
Catheart was conceited because he was a full colonel with a
combat command at the age of only thirty-six; and Colonel
Catheart was dejected because although he was already thirty-
six he was still only a full colonel."
There are contradictions in the above examples and with such
contradictions the theory provides no overall guidelines to
aid us in predicting or in making decisions. According to
theory (1) we should both buy and not buy the speculative
stock, and according to theory (2) we really can't predict
whether Colonel Catheart is happy or dejected. Until we have
more information about the conditions surrounding lost
opportunity because of hesitation, we can't use theory (1)
effectively.
Scientific or philosophical theories, as a rule, do not have
such gross or obvious inconsistencies; however, often
inconsistencies exist and are fair game for long arguments.
Understanding and Prediction
You will no doubt have heard that the purpose of theories is
to help us both understand certain parts of our world and
make predictions leading to new information and new
solutions. Understanding is a difficult term to define.
Perhaps one of the most common meanings of the term
`'understanding'' is that we develop, sometimes with the help
of others, a more satisfying picture of some part of the
world. For example, we may ask "What's University like?" The
reply may be, "University is like high school except that no
one cares if you come to class, and in most classes you don't
get any comments on the work you hand in." Or you may ask,
"Why is Harry so cranky?" And you may get a reply, "He had a
fight with his girl friend." Typically you will respond, "Oh
I understand." You understand because you can now combine
some bits of information that you already have in a new way-
you now feel you have a better picture to go on. Our point is
that understanding may give you a more acceptable picture
about a part of the world, but, nevertheless. that picture
may be quite erroneous. Unfortunately, you can walk away
feeling you understand from a wide variety of different
replies to the same question. It is proposed then that the
term understanding implies a personally-acceptable picture of
what goes together or what leads to what, but need not imply
an accurate picture. The accuracy is subsequently, if ever,
determined by more direct personal experience or by more
accurate additional data from another source.
The term "prediction" on the other hand, if stated in
testable form is a more scientifically useful concept. Theories
that enable us to understand are personally useful, while
theories that enable us to predict are both personally and
scientifically useful.
This does not mean that the term "understand" cannot be
redefined to include tests of the adequacy of the
information; it is merely that the term, as commonly used,
does not usually imply such tests whereas the term "predict"
more frequently does. Therefore, we propose that theories
that predict new information should be ranked more highly
than those which lead to understanding, as defined above.
We have stressed the importance of the testability of a
theory. Testing a theory can be done in several ways. A
theoretician may make a specific prediction growing out of
his theory and may state his theory in a testable form which
we then subsequently test and support or refute; or be can do
an experiment growing out of his theory, and we can attempt
to repeat his experiment. Replication in science is probably
the foundation of testability, but, as noted earlier, we
prefer the concepts of exportability or perishability of data
to that of replicability.
Summarizing, we are more and more inclined to view theories
as decision-making aids, perhaps not as whimsical as the toss
of a coin, nor as crude as a race tout's tip, but decision
aids, nonetheless. In the face of ignorance, but forced to
act, we build theories-these simplified and crudely drawn
maps of the past, present, and future-that give us some
semblance of confidence as we race or stagger through life's
great maze of alternatives: Are theories true or false? No
one knows, since most theories are designed to cover mammoth
areas or massive populations, and yet we can usually explore
in detail only a tiny corner or a few instances. Thus whether
a theory is true or false is anybody's guess, whereas
everybody knows that a decision aid is worthy if it helps you
make even one decision that is not immediately followed by a
disaster.
End of story