Types and levels of analysis. Concepts and conceptual themes
TYPES AND LEVELS OF ANALYSIS First, identifying and using conceptual themes in analysis are considered. The addi- tional level of analysis we will explore is the more ambitious level of analysis that is theory building.
Concepts and conceptual themes An emerging concept can be an idea or a model which, in turn, might represent the beginnings of an emergent perspective or theory. Alternatively, an already established concept might be a signifier of a perspective or theoretical position and epistemo- logical standpoint. Documents can be interrogated and re-visited for already established concepts that they variously draw upon. Concepts that might be expected, yet are omitted or neglected, might be noted. This can produce findings. Similarly, established concepts might emerge out of your interview data or there may be a specific search for such key concepts. This mode of analysis is most suited to unstruc- tured or loosely/semi-structured interviews where respondents were not led towards predetermined responses. Additionally, new concepts might present themselves and these are the sorts of findings that might have import for theory building or theo- retical development, especially if theorizing on your subject is less than adequate. When analysing qualitative data, a concept may be thought of as an underlying idea that is not necessarily referred to directly by respondents, whereas a theme is an idea that can be seen running through several responses (Harding, 2013: 6). Conceptual themes are therefore themes that represent underlying ideas or principles emerging from your data. Conceptual themes are findings in their own right because they are commonalities. As already illustrated, coding frames can be used to analyse a conceptual theme. Conceptual themes may help to explain relationships between different elements of your data. Though the characteristics of conceptual themes vary substantially, Harding (2013) nevertheless presents five characteristics of con- ceptual themes, each of which are summarized in Box 12. 5.
In my own research, respondents discussed their experiences, opinions, percep- tions and feelings. In some instances, detailed illustrative examples were provided. The analysis was approached as a creative activity, co-produced by myself (already immersed in the topic via an initial review of documentation and steeped in a femi- nist-influenced victimological epistemology – see critical reflection below) and my respondents. As the principal investigator and the interviewer, I was immediately aware of the nature of the data being collected and the analysis began to take shape whilst I was still in the field. The point at which I was doing analysis rather than doing data collection was when I had reached saturation point. It was clear that new concepts and themes were no longer being discovered. It was nearing time to exit the field. Interviews were transcribed verbatim and I used an analytic-inductive process, including data reduction – or the technique of identifying themes – to organize the data. The concepts that were emerging included existing concepts (though these
were not predetermined) that were also evident in the initial documentary review, as well as newly emergent conceptual themes. These are illustrated in Box 12. 6. My analysis had to find a way of illuminating the key narratives, yet reproducing these in a way that nevertheless allowed for outlying nuances to be retained. By drawing on concepts and conceptual themes, there was added value in terms of findings and the promise of another level of analysis began to present itself. Underlying assump- tions, prejudices, stereotypes, values and principles were emerging from the interview data that sometimes resonated with ideas and sentiments evident in the documentary resources I had already explored but sometimes did not. Some of the concepts and conceptual themes had strong affinities with my own epistemological position and there were commonalities emerging between the disconnects. By approaching the analysis in this way, I began to connect different elements of the data together.
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