Russel-Research-Method-in-Anthropology

Qualitative Data Analysis I: Text Analysis 495
In his research on household healthcare in Njinikom, Cameroon, Gery Ryan
(1995) had several coders sorting the quotes-on-cards into piles. He recorded
their conversation as they discussed what they were doing and used the discussion
to help identify the themes in his data. Later, in chapter 21, I’ll introduce
you to multidimensional scaling (MDS). We use MDS to find similarities in
pile sorts, and there is no reason you can’t do that with your pile sort of your
own data.
Word lists and the KWIC technique are extensions of the philosophy
behind in vivo coding in grounded theory: If you want to understand what
people are talking about, look closely at the words they use. The method has
a very, very long history. The classic KWIC method is a concordance, which
is a list of every substantive word in a text with its associated sentence. Concordances
have been done on sacred texts from many religions and on famous
works of literature from Euripides (Allen and Italie 1954), to Beowulf (Bessinger
and Smith 1969), to Dylan Thomas (Farringdon and Farringdon 1980).
(See McKinnon [1993] and Burton [1981] on the use of concordances in modern
literary studies.)
It’s easier to build concordances today than it was before computers, and
many programs are available that will list all the unique words in a text and
count how many times each is used (see appendix F).
Ryan and Weisner (1996) asked fathers and mothers of adolescents,
‘‘Describe your children. In your own words, just tell us about them.’’ In looking
for themes in these rich texts, Ryan and Weisner did a word count. Mothers
were more likely than fathers to use words like ‘‘friends,’’ ‘‘creative,’’ and
‘‘honest’’; fathers were more likely than mothers to use words like ‘‘school,’’
‘‘student,’’ and ‘‘independent.’’ These counts became clues about the themes
that Ryan and Weisner eventually used in coding the texts.
There is another technique, called semantic network analysis, which
involves tracking the association among words or concepts in a text. This
method, though, like pile sorting, also requires multidimensional scaling, so
I’ll hold off on telling you about it until we get to chapter 21.
No matter how you actually do inductive coding—whether you start with
paper and highlighters or use a computer to paw through your texts; whether
you use in vivo codes, or use numbers, or make up little mnemonics of your
own; whether you have some big themes in mind to start or let all the themes
emerge from your reading—by the time you identify the themes and refine
them to the point where they can be applied to an entire corpus of texts, a lot
of interpretive analysis has already been done. Miles and Huberman say simply:
‘‘Coding is analysis’’ (1994:56).