Russel-Research-Method-in-Anthropology

544 Chapter 18
There are two problems with componential analysis. First of all, it seems a
bit shallow to say that a Corvette is an expensive, impractical, American car
and nothing more, or that a Mercedes is an expensive, practical, foreign car
and nothing more. You can get so caught up in finding the minimal analytic
combination of features in this type of analysis that you forget you’re interested
in the meaning that people assign to different objects in a domain. On
the other hand, if you know the most parsimonious set of distinctive features
for an item in a domain, you can predict how someone will label new things
in the domain that they haven’t encountered before.
The second problem with componential analysis is the same one we run
into with all cognitive research methods: We have no idea if it reflects how
people actually think. This problem was raised early in the development of
cognitive studies by Robbins Burling (1964), who noted that, in a folk taxonomy
of trees, he could not tell the essential cognitive difference between hemlock
and spruce. ‘‘Is it gross size, type of needle, form of bark, or what?’’ If
an ethnographer could not answer this question, Burling observed, then no
componential analysis could claim to be ‘‘more than an exercise of the analyst’s
imagination’’ (p. 27).
Of course, this same critique could apply to any social research that
‘‘imputes the presence of something inside people’’ (like values and attitudes)
and must be balanced with a positive perspective on what can be done (Hymes
1964:119).
In fact, what can be done is impressive, intuitively compelling analysis of
the meanings that people attach to terms in their languages: Decision analysis
allows us to predict which of several behavioral options people will take,
under specific circumstances; taxonomic analysis lets us predict which class
of things some new thing will be assigned to; componential analysis lets us
predict what classification label will be assigned to some object. These methods
produce effective knowledge that finds application in practical fields like
health care delivery and advertising.
Analytic Induction and Boolean Tests
Analytic induction is a formal, qualitative method for building up causal
explanations of phenomena from a close examination of cases. The method
involves the following steps: (1) Define a phenomenon that requires explanation
and propose an explanation. (2) Examine a single case to see if the explanation
fits. (3) If it does, then examine another case. An explanation is
accepted until a new case falsifies it.
When you find a case that doesn’t fit, then, under the rules of analytic induc-