Analytical procedures

I now turn finally to the specific analytical procedures. I noted Corbin and Strauss’ (2008) conceptualisation of the data analysis procedure as both artistic and scientific, agreeing with these scholars that the process with which I ordered and brought meaning to the data required a balance between imagination and ‘scientific’ rigour. In this sense, while I sought to acknowledge space for creativity and ‘story-telling’, that is not to say that I embraced analytical anarchy: structure and grounding were crucial.

I drew therefore on Corbin and Strauss’ (2008: 66) account of the coding process: asking questions about the data, making comparisons across data sets, and gradually beginning to note patterns and themes within and across the data (Miles et al, 2014). I began by taking a manual approach to coding as that corresponded with my own personal preference for immersing myself in the data. As such, my first foray into

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the complete data set involved pre-coding (Dörnyei, 2007: 250) – reading through all my field notes and transcripts and noting preliminary thoughts, reflections, and comments, and highlighting points that appeared initially pertinent in transcripts. From there, I moved on to the next stage of coding, reading each text multiple times whilst listening to the audio recording in the case of interview data, and highlighting features I regarded as salient. Following Harvey’s (2014) detailed explication of her analytical approach, I worked throughout in Microsoft Word, putting the original text on one side, and, in a separate but aligned document, a blank document in which I took notes – or ‘analytic memos’ (Fielding, 2002: 163) – alongside each highlighted segment: these notes summarised my insights into that particular utterance, any contextual detail I thought relevant (for instance any field notes I had taken or distinct memories I had of a notable mood, a gesture, or a change in atmosphere in that particular moment), and my reasons for viewing this utterance as salient. I hoped in this way to be able to take into account (at least some) extra- linguistic nuances and to thus avoid ‘flattening out’ (Jones et al, 2017: 64) the articulations of the participants. Figure 5 below is a screenshot of this working document:

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This initial stage of analysis took place over a period of several weeks. I then began to draw out categories, or descriptive groups. Certain categories were quickly evident – for instance, the frequency with which issues such as cost were mentioned led me to believe that it would be salient to my analysis. Others took rather longer to become clear.

I should note that, as shown in Appendix G, my transcriptions included both line numbers and turn numbers, but that during coding I tended to use turn numbers, as shown in Figure 5 above: this forced me to return to the whole turn and therefore take into account the immediate co-text. In doing so, I attempted to resolve my discomfort with the idea of coding for ‘content’. I reject the assumption typical in much content analytical research that the participants’ language gives direct access to the content of their experience (Sullivan, 2012: 38), and I refute the idea that meaning is stable and consistent, directly represented through words which can thus be codified and quantified (Hardy et al, 2004: 20). Further, I assert that the ‘themes’ I constructed through this analysis did not simply ‘emerge’ from the data, but were instead actively produced and constructed by the researcher. For this reason, my intention throughout the analytical process was to maintain as much contextual data as possible, endeavouring as I coded to avoid isolating utterances both from their immediate ‘text internal’ contexts (Wodak, 2001), and also from the broader situational contexts in which they occurred.

On this account, my approach could be likened to a thematic discourse analysis (Taylor and Ussher, 2001; Singer and Hunter, 1999) which seeks to take into account the semantic content, the ‘ideas, assumptions, and conceptualisations’ (Armstrong et al, 2011: 352) underpinning or informing this content, and the fundamentally situated and co-constructed nature of the accounts. This approach highlights the role of language as constitutive of meaning (Braun and Clarke, 2006) and foregrounds the dialogic nature of the research interview. It also facilitates an approach which looks to the texts (in the widest sense of the term) not as isolated units, but instead as interconnected and interrelated (Phillips and Hardy, 2002). In this sense, it enabled

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me to uphold the importance of ‘intertextuality’, or the notion that ‘a text […] cannot exist as a hermetic or self-sufficient whole’ (Still and Worton, 1990: 1), that all texts are both synchronically and diachronically related to other texts (Wodak, 2008). Taking this approach then emphasised the importance of constant comparison within and across different sets of data as it is through this comparative endeavour that I could recognise moments of reproduction, repetition, and dissonance.

Before beginning this next, comparative stage, however, I decided to complement my Microsoft Word-based analysis with a more technological approach, and therefore inputted all my data into NVivo. I initially saw this software package as an ‘electronic filing cabinet’ (Fielding, 2002: 170) rather than a distinct analytical tool. However, this NVivo analysis was in fact rather revealing, as I found myself on occasion reading something rather different in the data from my initial Microsoft analysis. While this may have been down to my familiarity with the data and the passage of time between readings, I do also feel that viewing my data in two distinct semiotic modes in fact enabled a more varied and complex reading. Figure 6 below shows the NVivo document during the coding process:

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Having made initial notes in both data banks, I was able to begin the process of comparison across texts and to begin to draw out themes, or conceptual groups. By way of example, comments on cost soon came to be positioned in the broader theme of access (as explored in Chapter 5). Again I worked first in Microsoft Word, pulling together categories across data sets, before articulating these forward to the NVivo documents. As the latter allowed for clearer colour coding, I was then able to compare more clearly across my data, to see points at which certain utterances were coded multiple times, and to examine the ways in which these codes ‘spoke to’ one another. At this point, I began to work predominantly in NVivo, reconstructing my existing codes to take into account the themes I was formulating: in NVivo terms, renaming and reformulating nodes, and constructing ‘parent nodes’ under which to group key themes.

From here, I put together a code book in which I noted the code name, such as

access and exclusions; a description – in which I noted things that may be included

in this theme; examples from the data; and any notes, questions, or comments I thought relevant to this theme, as shown below. I found this particularly useful for bringing my data to tutorials in order to discuss themes with supervisors who did not have the same level of familiarity with the data. It also forced me to solidify my thoughts on each theme.

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I returned multiple times to my codebook over the next few months, revisiting each theme until they solidified into the four key chapters in this thesis – legitimacy, access, performance, and affect.

Conclusion

To conclude, this section has outlined the key philosophical presuppositions informing the research project, and has considered the ways in which these onto- epistemological principles influence the research focus, the methods, the ethical considerations, and the analytical approach. I have emphasised my commitment to an iterative approach to research, justifying this stance with reference firstly to pragmatic decisions in terms of policy shifts and complexities accessing the field, both of which have necessitated a somewhat ‘messy’ research chronology; and secondly to my theoretical commitments to a more data-driven approach which seeks to avoid the totalising imposition of a fixed theoretical framework. Following Harvey (2014: 152) in employing Sullivan’s (2012) useful terms here, I have given an outline of the ‘bureaucratic’ features of the analytical process, noting the procedures I followed in preparing and analysing the data, and have also explored the ‘charismatic’ features of this process, commenting on the beliefs and philosophical commitments I have brought to the analytical procedure. The following chapters, 4-7, will introduce the data, and my own interpretations and analysis of these ‘texts’.

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Chapter 4: Legitimacy and (self-) legitimation: knowing the speed