Connecting codes categories

Many researchers want to go beyond mere classification and explore whether or not the subject under analysis possesses a discernible structure, or whether or not linkages exist between or among particular categories. The purpose is to develop propositional statements or to relate concepts in order to discover the underlying principles - often referred to as the generation of hypotheses. Analysing focus group discussion data in this way can produce questions or hypotheses that might then be answered or tested by large-scale survey work and quantitative analysis.

None of these programs really facilitates 'theory building'. The procedure that theory-building qualitative analysis programs employ is somewhat different to those mentioned previously. Although a code is attached to a particular segment of text, the code 'characterises' the file in which it is present. Codes are therefore thought of as more like 'values' of a variable. For example, if the category or concept is 'relationship with peers' the corresponding codes could be 'competitive', 'cooperative', etc. Any given file will have one of these embedded, perhaps attached to several segments, all of which represent evidence of the


QSR NUD*IST program Source: QSR NUD*IST3 (NUD*IST is developed by QSR International Pty Ltd)


QSR NUD*IST program Source: QSR NUD*IST3 (NUD*IST is developed by QSR International Pty Ltd)

'competitiveness' in the peer relationship, for example. It could also be that among the remaining categories there is one that is concerned with work behaviour. The programs might be used to find that files characterised by competitive relationships with peers are more often than not also characterised by aggressive work behaviour. This might then form the basis of a more formal hypothesis. QSR NUD*IST3 is a program that facilitates this form of analysis (Figure 11.3). The latest versions of the product are N6 and Nvivo.

NUD*IST stands for non-numerical unstructured data indexing searching and theorising. It is a computer package designed to help users handle non-numerical and unstructured data in qualitative analysis. NUD*IST does this by supporting the processes of indexing, searching and theorising.

NUD*IST handles data such as:

text - for example, reports or minutes, transcripts of unstructured conversational interviews, evidence transcripts, literary documents, personnel records, fieldnotes, newspaper clippings and abstracts non-textual records - for example, photographs, tape recordings, films, maps, plans.

Catterall and Maclaren,4 in an article examining the use of computers in research, suggest that programs such as NUD*IST take out some of the tedium of exploring qualitative data and therefore help the researcher in this task. However, they also point out that it is important that the program chosen is appropriate to the task in hand and that it remains a tool to assist the researcher and does not become the driving force of the research. They point out that programs such as NUD*IST are sophisticated tools for the researcher, but the intellectual task of conceptualising data remains the researcher's and will reflect their competence and the quality of the data they have collected.

The same authors point out that such programs encourage the researcher to build detailed and complex coding structures that can be an advantage when exploring complex phenomena. However, they warn that the researcher can get 'bogged down' in its complexities. They warn that such procedure can decontex-tualise data and make procedure mechanistic. They suggest that there is always an advantage in returning to the original data to gain further insights.

The computer program QSR NUD*IST allows the researcher to build up a complex categorisation system to classify the data under analysis. The document system numbers each line of text for you and brings up the text as a window that allows you to explore it and read each interview thoroughly. Using the indexing system, which allows you to tag and code lines of text with an appropriate term and then store this code in an index tree, you can go through each text indexing lines and assigning line numbers to categories that are created as you go along. These categories are changeable and can be revised over time. As new insights are gained, so you are able to create new codes as the data are explored and a better feel for them is experienced. Another advantage is that it is possible to code one piece of text with several codes. Examples of different categories can often be more than one line long, which means that small sections of text can be assigned a number of different codes if they illustrate several different categories. Thus, NUD*IST allows you to multiple code sections of text and, at the same time, to store each code separately in its own category.


• Making notes in the field.

• Writing up or transcribing fieldnotes or interview proceedings.

• Editing: correcting, extending or revising fieldnotes.

• Coding: attaching a keyword or tags to segments of text to permit later retrieval.

• Storage: keeping text in an organised database.

• Search and retrieval: locating relevant segments of text and making them available for inspection.

• Data 'linking': connecting relevant data segments with each other, forming categories, clusters or networks of information.

• Memoing: writing reflective commentaries on some aspect of the data, as a basis for deeper analysis.

• Content analysis: counting frequencies, sequences of locations of words and phrases.

• Data display: placing selected or reduced data in condensed, organised format, such as a matrix or network for inspection.

• Conclusion drawing and verification: helping the analyst to interpret displayed data and to test or confirm findings.

• Theory building: developing systematic, conceptually coherent explanations of findings; testing hypotheses.

• Graphic mapping: creating diagrams that depict findings or theories.

• Preparing interim and final reports.

Once the first version of categories is completed, you can go back over all the categories, making reports of them using the indexing system in NUD*IST and revising your initial findings. You can then explore the categories created, to try to gain a better understanding of the phenomena they represent and also to work at better conceptual labels to describe them. This can be accomplished by means of the index system in NUD*IST and a separate report of each category can be produced. The reports can contain all the examples of the categories you have tagged in each transcript and, by exploring these reports, you can refine your thinking about the category and shift, add and delete coding as you feel appropriate. This may be important in places where you have coded things wrongly or where a new category has subsequently been created that better describes an example that had previously been assigned to another category. You can also move the position of the categories within the tree structure to represent what feels more appropriate. As a result, the tree may be simplified as the individual categories become more distinctive.

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