Russel-Research-Method-in-Anthropology

62 Chapter 2
the dependent variable (the decision that is finally made), but the contribution
may be quite direct and causal.
Condition 2: Lack of Spuriousness
Just as weak correlations can be causal, strong correlations can turn out not
to be. When this happens, the original correlation is said to be spurious. There
is a strong correlation between the number of firefighters at a fire and the
amount of damage done: the more firefighters, the higher the insurance claim.
You could easily conclude that firefighters cause fire damage.
We know better: Both the amount of damage and the number of firefighters
is caused by the size of the blaze. We need to control for this third variable—
the size of the blaze—to understand what’s really going on.
Domenick Dellino (1984) found an inverse relation between perceived quality
of life and involvement with the tourism industry on the island of Exuma
in the Bahamas. When he controlled for the size of the community (he studied
several on the island), the original correlation disappeared. People in the more
congested areas were more likely to score low on the perceived-quality-of-life
index whether or not they were involved with tourism, while those in the
small, outlying communities were more likely to score high on the index. People
in the congested areas were also more likely to be involved in tourismrelated
activities, because that’s where the tourists go.
Emmanuel Mwango (1986) found that illiterates in Malawi were much
more likely than literates to brew beer for sale from part of their maize crop.
The covariation vanished when he controlled for wealth, which causes both
greater education (hence, literacy) and the purchase, rather than the brewing,
of maize beer.
The list of spurious relations is endless, and it is not always easy to detect
them for the frauds that they are. A higher percentage of men than women get
lung cancer, but when you control for the length of time that people have
smoked, the gender difference in lung cancer vanishes. Pretty consistently,
young people accept new technologies more readily than older people, but in
many societies, the relation between age and readiness to adopt innovations
disappears when you control for level of education. Urban migrants from
tribal groups often give up polygyny in Africa and Asia, but both migration
and abandonment of polygyny are often caused by a third factor: lack of
wealth.
Your only defense against spurious covariations is vigilance. No matter how
obvious a covariation may appear, discuss it with disinterested colleagues—
people who have no stake at all in telling you what you want to hear. Present
your initial findings in class seminars at your university or where you work.