Causal Arguments
A causal argument is an argument which attempts
to support a causal claim. A causal claim says or
implies that one thing caused or causes another.
Causal arguments are inductive arguments in which
the conclusion is a claim that one thing causes
another.
For example:
(i) Clogged arteries cause heart attacks
(ii) A rough surface produces friction
(iii) Exercise during heat causes sweating
Causal inferences are often an attempt to explain or
predict an outcome.
Cogent arguments in support of causal claims are
difficult to come by, and we should take great
care when dealing with causal premises. There
are lots of ways to express a cause in English
without using the word ‘cause’ and here are just
a few ways from pages 286-7.
C produced E
C brought about E
C created E
C influenced E
E was determined by
E was the result of C
E was induced by C
E was an effect of C
C was responsible for E
C led to E
C affected E
As a result of A, E occurred
C
Distinguishing between arguments and explanations
Explanations aim to convey information or knowledge and thus fall under the
general heading of informational claims. But explanations are a bit different
from most informational discourse. It is sometime difficult to distinguish
between the two for the following reasons:
1. Same indicator words: because, since, therefore.
2. Same Structure:
Argument:
1.Premise
2. Premise
3. Premise
Therefore
4. Conclusion
Explanation:
1. Factor (1)
2. Factor (2)
3. Factor (3)
Therefore,
4. Event X came to be
Different Purposes
Explanations are usually designed to show how or why the phenomenon in
question exists, happened, or is true. In an explanation, the various factors
generally explain how it was that some particular event X came to be.
The purpose of the explanation is not to establish the truth of X but merely
to give an account of how it came to be. If a person regards the truth of a
claim as unproblematic and he or she is merely interested in explaining why
it is the case (as opposed to demonstrating that it is the case) then the
person is explaining.
Arguments: In an argument someone is putting forward reasons trying to
justify a claim as true.
Consider:
Q BECAUSE P
•Is the author interested in establishing the truth of Q and is P
offered as evidence for it? Then we have an argument.
•Is the truth of Q unproblematic and at least as well established as
the truth of P? And are we interested in explaining why Q is the
case? Then we have an explanation.
Imagine that we are a team of doctors working for the Centers for Disease
Control. We have received several reports from doctors around the country
who have patients with mesothelial cancer, a rare form of cancer that
attacks the lining of the lung, heart sack, and some tissues on the inside of
the abdomen. Further, several of these patients have a history of work with
asbestos. So we formulate the following argument:
Working with asbestos is correlated with mesothelial cancer.
Therefore,
It is likely that asbestos causes mesothelial cancer.
As it stands this is not a strong argument. There are a number of possible
criticisms of such arguments that infer a causal connection on the basis of a
correlation. NOTE: Govier points out (p. 286) that it is in fact quite difficult
to construct cogent arguments to support causal claims.
Working with asbestos is correlated with mesothelial cancer.
Therefore,
It is likely that asbestos causes mesothelial cancer.
1. The correlation may be coincidental. The two characteristics might be
accidentally correlated rather than genuinely connected.
2. The items might be correlated because they are both effects of same
underlying cause, that is, the apparent relation is spurious.
3. The causal relation might be genuine but insignificant. Asbestos might be a
causal factor, but not the major causal factor.
4. The causal factor might be in the wrong direction. To say that A is correlated
with B implies that B is also correlated with A. So correlation does not tell us
the direction of causation.
5. The causal relation might be complex.
Correlation vs. Causation
Correlation is a symmetrical relationship, which causation is
asymmetrical. Here are the three ways we might classify
correlation relationships.
(i) Positive correlation: if a higher proportion of Qs than non-Qs are H, then there is a
positive correlation between being Q and being H.
(ii) Negative correlation: if a smaller proportion of Qs than non-Qs are H, then there
is a negative correlation between being Q and being H.
(iii) No correlation: if about the same proportion of Qs as non-Qs are H, then there is
no correlation between being Q and being H.
A significant correlation is one that is reliable. (288)
When Q is positively correlated with H, then one of the following
has to be true, but it doesn’t have to be a causal relationship.
1.
2.
3.
4.
Q is a cause of H.
H is a cause of Q.
The positive correlation of Q and H is a coincidence.
Some other factor, X, is a cause of both Q and H.
It should be clear now, why we cannot conclude that correlation
implies causation given these four possibilities.
It is fallacious to argue from a positive correlation directly to a
causal relationship. See page 289.
Associations and Links
To say that two things: A and B are linked is to claim that more
than just a correlation between A and B exists.
Linking suggests that there is a causal relationship between A
and B.
Linked seems to have become a code word for unknown causal
relationship. Be skeptical and investigate the data and
reasoning involved with such claims.
When we observe two events A and B, how do we find out if they are
causally related? One possibility is that A is the cause of B. But there are
many other alternatives to consider.
Case #1 - A and B are not causally related
The fact that A is followed by B does not make A the cause of B. Even
when there seems to be a correlation between A and B, it is possible that
they are not causally connected. Perhaps the correlation is accidental.
It is important to consider a control situation where A is absent, and see if
B would still occur.
Case #2 - A is the cause of B
For a particular event A to be the cause of B, it is necessary that A happens earlier than
B.
If a type of event A is positively correlated with B, this is one relevant piece of evidence
that A is the cause of B. But we need to rule out the other possibilities which are
discussed here.
Case #3 - B is the cause of A
Sometimes correlation goes both ways. The fact that A causes B can explain the
correlation, but maybe the reality is that B is the cause of A. For example, people who
are depressed tend to have low self-esteem. Perhaps the former is the cause of the
latter, but it is also possible that low self-esteem causes depression by making a person
socially withdrawn and lacking in motivation. We need further observations to
determine which possibility it is.
Case #4 - A and B form a causal loop
In many cases two causal factors can reinforce each other by forming a causal loop. In
the example above, it is more plausible to think that depression affects self-esteem, and
a lower self-esteem can cause further depression.
Of course, causal loops happen only between types of events. If a particular event A is
the cause of a particular event B, then A must happen earlier than B and so B cannot be
the cause of A.
Case #5 - A is a minor cause of B
An effect can have more than one cause, and some may be more important than others.
Case #6 - A and B have a common cause
Young children with larger noses tend to be more intelligent, but it is not because
the nose size somehow accelerates cognitive development. Rather young children
with larger noses are children who are older, and older children are more
intelligent than younger ones because their brains have developed further. So A
and B are correlated not because A is the cause of B, but because there is an
underlying common cause.
Case #7 - B is a side effect of A
These are cases where the effect might be wrongly attributed to A when in fact it is
due to some side effect of A.
It has been shown that medicine can have a placebo effect. The subjective belief
that one is being treated can bring about relief from an illness even if the medical
treatment being given is not really effective against the illness. For example, a
patient might report that his pain has decreased as a result to taking a pill, even
though the pill is a sugar pill with no effect on pain.
Assessing Causal Reasoning
It is helpful to make a distinction between two very general uses of the term
cause. We need to discuss these kinds of causes separately:
1. Causation in Specific Events: Mill’s Methods
Sometimes when we say x causes y, x and y refer to specific events. A
temperature below 32 degrees Fahrenheit causes the water to freeze,
just as the ice on the wings could cause the plane to crash
2. Causation in Populations
At other times when we say x causes y, we mean that the increase of x in a
population leads to an increase in y in that population. This does not
mean that every x leads to a y, but that as one increases so will the other.
The claim "smoking causes cancer" is such a claim. Every person who
smokes does not get cancer, but in a population, as the incidence of
smoking increases so does the incidence of cancer.
Mill’s Methods
A causal argument is an argument
which attempts to support a causal
claim. A causal claim says or implies
that one thing caused or causes
another. Mill compiled five methods for
identifying causal connections between
events. These methods function
implicitly in many of the inductive
inferences that we make in everyday
life.
Shortly after a flight from Tokyo landed in
Copenhagen, 144 passengers were hospitalized.
Another fifty-one were treated though not
hospitalized. All of the affected passengers
exhibited symptoms of gastrointestinal
disorder. Doctors immediately suspected food
poisoning as the cause of the illnesses. All of the
passengers who later became ill had eaten the
meal prepared by a cook. During investigation,
it was learned that this cook had an infected
sore on his finger. Officials concluded that
bacteria from this infection had been the cause
of the illnesses suffered by the passengers.
Mill’s Methods
The Method of Agreement: X is the common thread
•The Method of Agreement involves looking at
antecedent circumstances – events or conditions
that occurred earlier.
•The basic idea of this method is that if a
circumstance is a cause – a causally sufficient
condition in this context – of some type of events, it
will be present whenever that type of events occurs.
•That is, the Method of Agreement says that in
order to identify a cause, we should look for
agreement in the antecedent circumstances.
•If just one common antecedent circumstance can
be identified, then it is likely to be the cause – or a
part of the cause.
• Finding a common antecedent circumstance is not sufficient to
justify a causal claim, however, for there will be many such
circumstances that are causally irrelevant.
– In Case 1, all the passengers who became ill boarded the
plane in Tokyo, but we have no reason to believe that this
common antecedent circumstance causes the sickness.
• Good causal reasoning is guided by general background
knowledge about the types of events and conditions that could
be the cause.
– Why can doctors in Case 1 and we exclude the common
antecedent circumstance of boarding the plane in Tokyo?
– Because the doctors and we have background knowledge
that food poisoning, not boarding a plane in a particular city,
can cause gastrointestinal illness.
The strength of such reasoning depends largely on two questions: In this
case, how likely is it that X is the only relevant common factor preceding Y,
and how likely is it that Y could have resulted from two independent causes?
Questions:
(1) Is X the only relevant common factor preceding the occurrences of Y?
Only if it is can the argument be considered reliable. So: consider whether
there might be other possible factors common to the occurrences of the
effect.
(2) Did the occurrences of Y result from independent causes? The argument
is reliable only if this possibility has been eliminated. So: consider whether
the simultaneous occurrences of the effects may have been coincidental
effects of two different causes.
In the above gastrointestinal illness case, the doctor
specified the omelets, among other ingredients of a
meal, as the cause for the sickness in focusing on the
following married couple. A husband and a wife were
on the same flight and were served identical meals.
The wife was hungry but allergic to eggs, so she ate
all of the meal but the omelet. The husband was also
hungry but not allergic to eggs, so he ate all. The
husband became ill, but the wife did not. The doctor,
having suspected the food poisoning, identified the
omelet as the cause of the illness.
A focus on relevant differences: X is the difference
Key Question: Is the suspected cause the only relevant factor that distinguishes the
situation in which Y is present from situations in which it is not? Only if it is, is the
reliability of the argument beyond question.
We need to be reasonably sure that X is the only relevant difference between the
situations where Y occurs and those where it does not. So, before, accepting such an
argument, it is prudent to consider other possible relevant differences between this
situation and those in which Y did not occur.
For Example:
Consider the example of the XYY syndrome. A statistically significant proportion of the
criminal population has this genetic defect leading some to conclude that the genetic
defect is the cause of crime. But there are other differences between XY and XYY
males. The latter group is less intelligent on average, usually are bigger, and have
severe acne. It therefore seems likely that the cause of antisocial behavior is society's
response to the physical characteristics associated with this genetic anomaly.
In postmortem examinations of five
Alzheimer’s patients and five people without
the disease, it was found that all the diseased
patients had lost neurons from the nucleus
basalis (a tiny area deep in the brain), while all
the people without the disease had the normal
member of cells in this area. Scientists who
conducted this study believe that the loss of
neurons from the nucleus basalis may be
responsible for the decreased activity in the
cortex. (Salmon 2002, p. 184)
In England, records of the last 100 years show a
steady increase in per capita consumption of sugar,
from about 20 lbs/year in 1820 to over 100 lbs/year
today. Present consumption of sugar in the US is
about the same. Attendant with this increased
consumption of sucrose has been an almost parallel
rise in the prevalence of cavities. Conversely, surveys
in Europe and Japan demonstrated that cavities
were dramatically reduced during periods of
wartime restrictions of sugar. (E. Newburn, Science
217, 1982)
I've eaten Thanksgiving lunch at my parents-in-law for the past
ten years. This year I got sick. This was also the first time my
sister-in-law was there. I suppose I got sick because she was
there.
a) Indicate the causal claim (x causes y - what are the x and
y?)
b) Identify the pattern of reasoning: which of Mill’s methods
is employed?
c) State any other relevant differences (for x is the difference)
or any other relevant common threads (for x is the common
thread).
d) Offer another plausible cause for the event.
e) State whether the argument is good or not.
Sample: I've eaten Thanksgiving lunch at my parents-in-law
for the past ten years. This year I got sick. This was also the
first time my sister-in-law was there. I suppose I got sick
because she was there.
a. My sister-in-law caused me to get sick.
b. Method of difference: X is the difference
c. Perhaps the person is already sick; perhaps there was a
different food served this year.
d. The person was already sick before the lunch, and his
sickness had nothing to do with his sister-in-law or the food at
all
e. Bad argument. The person needs to explore the other
possible differences between this year's meal and those in
previous years.
On the planet of Bonneyloon, a planet far, far, far away from earth, there are
two kinds of people: Those who are green and those who are purple. The
Greens of Bonneyloon for many centuries were the ruling class; the Greens
owned most of the land and had most of the money. A first grade teacher in
Bonneyloon noticed that all the students who consistently failed exams were
Purples. He concluded that Purples are intellectually inferior to Greens and
that's why they failed more exams.
a) Indicate the causal claim (x causes y - what are the x and y?)
b) Identify the pattern of reasoning (x is the difference; x is the common
thread)
c) State any other relevant differences (for x is the difference) or any other
relevant common threads (for x is the common thread).
d) Offer another plausible cause for the event.
e) State whether the argument is good or not.