Russel-Research-Method-in-Anthropology

492 Chapter 17
We come next to the two methods that are very widely used across the social
sciences for analyzing text: grounded theory and classical content analysis.
Grounded theory emphasizes the discovery and labeling of concepts (variables)
and the building of models based on a close reading of the text. Content
analysis emphasizes the formal description of concepts and the testing of models
and hypotheses.
Grounded Theory
The grounded-theory approach is a set of techniques for: (1) identifying
categories and concepts that emerge from text; and (2) linking the concepts
into substantive and formal theories. The approach was developed by sociologists
(Glaser and Strauss 1967; Strauss and Corbin 1990) and is widely used
to analyze ethnographic interview data.
The mechanics of grounded theory are deceptively simple: (1) Produce
transcripts of interviews and read through a small sample of text. (2) Identify
potential analytic categories—that is, potential themes—that arise. (3) As the
categories emerge, pull all the data from those categories together and compare
them. (4) Think about how categories are linked together. (5) Use the
relations among categories to build theoretical models, constantly checking
the models against the data—particularly against negative cases. (6) Present
the results of the analysis using exemplars, that is, quotes from interviews
that illuminate the theory.
The key to making all this work is called memoing. Throughout the
grounded-theory process, you keep running notes about the coding and about
potential hypotheses and new directions for the research. Grounded theory is
an iterative process by which you, the analyst, become more and more
grounded in the data. During the process, you come to understand more and
more deeply how whatever you’re studying really works.
Coding Themes
The heart of grounded theory is identifying themes in texts and coding the
texts for the presence or absence of those themes. Coding turns free-flowing
texts into a set of nominal variables (what statisticians mean, by the way, when
they use the phrase ‘‘qualitative data’’). In a set of texts about the experience
of divorce, people do or do not talk about what to do about pension funds;
they do or do not talk about how their children are taking it; they do or do not
talk about their relations with their former in-laws; and so on.
Where do you stop? There is practically no end to the number of themes