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117<br />

Chapter 3 Research Framework<br />

hunches to explain the data. The final stage <strong>of</strong> Morse and Field’s (1996) analysis<br />

framework involves recontextualising the data, which involves developing an<br />

emerging theory that is applicable to other settings and other populations.<br />

These cognitive processes typically take place regardless <strong>of</strong> the approach to analysis.<br />

Morse and Field (1996) explained that these cognitive processes thus need a<br />

structure around them or an approach to guide the researcher. The most frequently<br />

used approaches include thematic analysis and content analysis. Thematic analysis<br />

involves the search for and identification <strong>of</strong> common threads/themes that extend<br />

throughout the data (Leininger, 1985). The first task is to read and re-read the data in<br />

their entirety, and then reflect on the data as a whole. Themes, which are an outcome<br />

<strong>of</strong> this coding and categorisation process, then appear as significant concepts linking<br />

substantial portions <strong>of</strong> the data together. Content analysis is an alternative approach<br />

and involves analysis by topic, whereby each data set is segmented into topics and<br />

then categories (Babbie, 2001). These categories are typically broad descriptions <strong>of</strong><br />

the data. Once the categories have ample data the researcher may then subcategorise.<br />

The researcher may also look for relationships between categories. Thus a coding<br />

hierarchy develops.<br />

Other approaches to qualitative data analysis put forward by other experts also<br />

suggest that the analysis is about reducing the data into more manageable quantities<br />

and seeing what’s there (Miles and Huberman, 1994). This mirrors the approaches<br />

put forward by Morse and Field (1996) and is about reducing the data down to<br />

themes or categories. Similarly, Miles and Huberman (1994) suggest that qualitative<br />

data analysis should involve three main steps: data reduction, data display, and<br />

conclusion drawing and verification.<br />

Data reduction involves assigning codes and coding the data. Codes are tags or labels<br />

for assigning units <strong>of</strong> meaning to the transcribed data. Codes are usually attached to<br />

chunks <strong>of</strong> data rather than individual sentences. These codes may later be<br />

categorised in order to organise the data and to make retrieval easier (Saldana, 2009).<br />

Miles and Huberman (1994) suggest that the coding process can be made easier by<br />

the creation <strong>of</strong> a “start list” or a list <strong>of</strong> codes identified prior to the fieldwork. This<br />

start list may be compiled from a literature review or from hypotheses. The codes in

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