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HOW DOES CONTENT ANALYSIS WORK 481<br />

There are several computer packages that can help<br />

the coder here (e.g. ETHNOGRAPH, N-Vivo),<br />

though they require the original transcript to be<br />

entered onto the computer. One such, Code-A-<br />

Text, is particularly useful for analysing dialogues<br />

both quantitatively and qualitatively (the system<br />

also accepts sound and video input).<br />

Having performed the first round of coding, the<br />

researcher is able to detect patterns, themes and<br />

begin to make generalizations (e.g. by counting<br />

the frequencies of codes). The researcher can also<br />

group codes into more general clusters, each with<br />

acode,i.e.beginthemovetowardsfactoringthe<br />

data.<br />

Miles and Huberman (1994) suggest that it is<br />

possible to keep as many as ninety codes in the<br />

working memory at any one time, though they<br />

make the point that data might be recoded on a<br />

second or third reading, as codes that were used<br />

early on might have to be refined in light of<br />

codes that are used later, either to make the codes<br />

more discriminating or to conflate codes that are<br />

unnecessarily specific. Codes, they argue, should<br />

enable the researcher to catch the complexity and<br />

comprehensiveness of the data.<br />

Perhaps the biggest problem concerns the<br />

coding and scoring of open-ended questions. Two<br />

solutions are possible here. Even though a response<br />

is open-ended, an interviewer, for example, may<br />

precode the interview schedule so that while an<br />

interviewee is responding freely, the interviewer is<br />

assigning the content of the responses, or parts of it,<br />

to predetermined coding categories. Classifications<br />

of this kind may be developed during pilot studies.<br />

Alternatively, data may be postcoded. Having<br />

recorded the interviewee’s response, for example,<br />

either by summarizing it during or after the<br />

interview itself, or verbatim by tape-recorder,<br />

the researcher may subject it to content<br />

analysis and apply it to one of the available<br />

scoring procedures – scaling, scoring, rank scoring,<br />

response counting, etc.<br />

Step 9: Conduct the data analysis<br />

Once the data have been coded and categorized,<br />

the researcher can count the frequency of each<br />

code or word in the text, and the number of<br />

words in each category. This is the process of<br />

retrieval, which may be in multiple modes, for<br />

example words, codes, nodes and categories. Some<br />

words may be in more than one category, for<br />

example where one category is an overarching<br />

category and another is a subcategory. To ensure<br />

reliability, Weber (1990: 21–4) suggests that it is<br />

advisable at first to work on small samples of text<br />

rather than the whole text, to test out the coding<br />

and categorization, and make amendments where<br />

necessary. The complete texts should be analysed,<br />

as this preserves their semantic coherence.<br />

Words and single codes on their own have<br />

limited power, and so it is important to move to<br />

associations between words and codes, i.e. to lo<strong>ok</strong><br />

at categories and relationships between categories.<br />

Establishing relationships and linkages between<br />

the domains ensures that the data, their richness<br />

and ‘context-groundedness’ are retained. Linkages<br />

can be found by identifying confirming cases, by<br />

seeking ‘underlying associations’ (LeCompte and<br />

Preissle 1993: 246) and connections between data<br />

subsets.<br />

Weber (1990: 54) suggests that it is preferable<br />

to retrieve text based on categories rather than<br />

single words, as categories tend to retrieve more<br />

than single words, drawing on synonyms and<br />

conceptually close meanings. One can make<br />

category counts as well as word counts. Indeed,<br />

one can specify at what level the counting can<br />

be conducted, for example, words, phrases, codes,<br />

categories and themes.<br />

The implication here is that the frequency of<br />

words, codes, nodes and categories provides an<br />

indication of their significance. This may or may<br />

not be true, since subsequent mentions of a word<br />

or category may be difficult in certain texts (e.g.<br />

speeches). Frequency does not equal importance,<br />

and not saying something (withholding comment)<br />

may be as important as saying something. Content<br />

analysis analyses only what is present rather than<br />

what is missing or unsaid (Anderson and Arsenault<br />

1998: 104). Further, as Weber (1990) says:<br />

pronouns may replace nouns the further on one goes<br />

through a passage; continuing raising of the issue may<br />

Chapter 23

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