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Russel-Research-Method-in-Anthropology

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Qualitative Data Analysis I: Text Analysis 503<br />

each of the substantive themes <strong>in</strong> their model is succ<strong>in</strong>ctly def<strong>in</strong>ed by a quote<br />

from a respondent.<br />

When the steps of the grounded-theory approach are followed, models or<br />

theories are produced that are, <strong>in</strong>deed, grounded <strong>in</strong> the text. These models,<br />

however, are not the f<strong>in</strong>al product of the grounded-theory approach. In their<br />

orig<strong>in</strong>al formulation, Glaser and Strauss (1967) emphasized that the build<strong>in</strong>g<br />

of grounded-theory models is a step <strong>in</strong> the research process. The next, of<br />

course, is to confirm the validity of a model by test<strong>in</strong>g it on an <strong>in</strong>dependent<br />

sample of data. Kearney et al. checked the validity of their model by present<strong>in</strong>g<br />

it to knowledgeable respondents (pregnant drug users), to members of the<br />

project staff, and to health and social service professionals who were familiar<br />

with the population.<br />

Us<strong>in</strong>g Exemplar Quotes<br />

Besides display<strong>in</strong>g models, one of the most important methods <strong>in</strong><br />

grounded-theory text analysis is the presentation of direct quotes from respondents—quotes<br />

that lead the reader to understand quickly what it took you<br />

months or years to figure out. You choose segments of text—verbatim quotes<br />

from respondents—as exemplars of concepts and theories or as exemplars of<br />

exceptions to your theories (those superimportant negative cases).<br />

This technique looks easy, but it’s not. You have to choose the exemplars<br />

very carefully because your choices constitute your analysis, as far as the<br />

reader is concerned, and you have to avoid what Lofland (1971) called the two<br />

great s<strong>in</strong>s of qualitative analysis <strong>in</strong> order to use the exemplar quote technique<br />

effectively.<br />

The first s<strong>in</strong>, excessive analysis, <strong>in</strong>volves the all-too-familiar practice of jargony<br />

writ<strong>in</strong>g and the avoidance of pla<strong>in</strong> English to say pla<strong>in</strong> th<strong>in</strong>gs. If you<br />

analyze a batch of data and conclude that someth<strong>in</strong>g simple is go<strong>in</strong>g on, don’t<br />

be afraid to say so. There is absolutely noth<strong>in</strong>g of scientific value to be ga<strong>in</strong>ed<br />

from mak<strong>in</strong>g straightforward th<strong>in</strong>gs complicated.<br />

Compare these two sentences: (1) ‘‘The more generations that people from<br />

various ethnic groups are <strong>in</strong> the United States, the less likely they are to speak<br />

anyth<strong>in</strong>g but English.’’ (2) ‘‘Over an expand<strong>in</strong>g number of generations, people<br />

of ethnic heritage <strong>in</strong> the United States become, probabilistically, less likely to<br />

adhere to their traditional l<strong>in</strong>guistic symbol systems.’’ The best word to<br />

describe the second sentence is yucky.<br />

The second s<strong>in</strong> consists of avoid<strong>in</strong>g do<strong>in</strong>g any analysis on your own—be<strong>in</strong>g<br />

so gun-shy of theory and jargon that you simply fill up your papers and books<br />

with lengthy quotes from people and offer no analysis at all. Data do not speak<br />

for themselves. You have to develop your ideas (your analysis) about what’s

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