Analysing the data: transcription, coding and trying to put the body back in

Data analysis for me began while still in the ‘field’, as I began to transcribe those go-alongs I had undertaken, and type up observations. For any researcher

interested in embodied practice, transcribing is a disheartening process. Typing up my recordings I had a distinct feeling that the lived understandings generated at

the cinema were disappearing with every keystroke. While this may seem like a reason to have adopted a video dimension to my research, visual data does not solve this problem. Indeed, Jacobs et al. (2008:175), who videoed their research on Red Road Estate; and Dant (2004: 56) who videoed working practices at a garage, bemoan a similar deadening when presenting moving image data in a research journal and transcribing it respectively. This is also not a sensation that is unique to those working on embodied practice, and the politics of transcription has been discussed in a range of disciplines (cf. Bird, 2005; Tilley, 2003; Bucholtz, 2000).

My experience of transcribing offered a significant problem: its disembodying nature meant I was unable to produce transcripts that supported my philosophical influences and the intentions of my project. As such, I developed a form of

transcribing that included notes from the memories conjured up as I typed,

embodied memories brought to the fore by listening to my tapes and hearing more than just talk. Sometimes this was as simple as noting that Joan had brought her own sugar to the cafe because of her on-going stomach problems. At other times, it was a memory of something I felt, or something subtle that one of the women I was with did. For example, the way that Ann fiddled with her wedding ring every time her speech drifted off, or the dramatic gesticulating of Joyce that was a fundamental part of her communicating but which was lost in a straight transcript of talk.

Although my added stage directions do not, of course, solve the problem of

disembodied transcriptions, I found that during the analysis process they gave me pointers and sparked memories that helped me realise that certain spoken themes also shared particular bodily acts and embodied sensations. The process of

adding these stage directions in my transcriptions almost happened without me thinking as, while I listened and typed, the memories flooded forward. In this way I found transcribing a fundamental part of analysing my data, acting as it did like the prompts engaged in research (see also Bird, 2005). This meant that, in line with recommendations from Maxwell (2005: 96) and Crang (2005b: 222), I began my data analysis before engaging in any formal coding.

Armed with these annotated transcriptions and notes from my observations on the go-alongs, including those of bodily sensations felt during the film, I began the process of data analysis proper. As opposed to quantitative research in which the codes are set before the research is carried out, in qualitative analysis the

researcher’s task is to look through it, grouping together points repetition and singling out exceptional elements to generate codes (Cope, 2005: 225; Crang, 2005b: 224). In my case, this was achieved through a laborious process of reading and re-reading the transcripts and field notes, highlighting areas of convergence and discordance between them. So much data is generated by qualitative

research that it is well known to be unwieldy and hard to work with systematically (Brewer, 2000). For me, managing hundreds of pages of data involved a lot of photocopying, cutting and pasting, and even more post-it notes, as I attempted to convert the mess of research into something coherent while also maintaining its ambiguity (Law, 2004; Parr, 2001). This (literal) mess is of course now avoidable through the use of a digital tool such as NVivo, but having undertaken training in this process I decided against it because I wasn’t able to get an over-arching sense of the data. This is not a criticism of the software — it is just that, for me, the materiality of the data is key to its analysis.

The codes produced through this process are not, of course, an end in

themselves. What begin as ‘descriptive codes’ are then used to explore more abstract or ‘analytic’ codes (Cope, 2005: 224). Qualitative data analysis, then, is an on-going and iterative process (Hammersley and Atkinson, 2007; Maxwell, 2005). It was after iteration four of analysing the go-along data that I realised my interviews could contribute quite a lot to the analysis and interpretation process.

This stemmed from an engagement between them and my observation during analysis, and the developing theme of cinematic habitus that is discussed in Chapter Six. I was interested in how the two forms of data related, and the

different themes arising from both. I did not include the interview data in the same analysis as that of the go-alongs, instead I submitted it to the same process and compared the developing codes and themes to offer a point of comparison. I did this partly because I wanted to explore the ways in which being at the cinema together might encourage different forms of talk and knowledge (ie. did it bring forth pre-reflexive, or taken for granted knowledges?), but also because I wanted to see the continuities between the two and make note of those points referenced in both.

Although much of practice is not just ‘unsayable’ but unspoken, speech - and conversation - is nevertheless an important part of practice. As such, rather than discount interview data, I draw on it frequently across the next three chapters as I present my analysis. Although I supplement it with observations, I do not discount participants’ (our) capacity to be cognisant of, and capable of reflecting on, much of practice (Rose et al., 2010). However, there is also - as Bourdieu notes - much of practice that goes without saying and rarely makes it into our explanations of what we do. As such, despite drawing on this data in the following chapters it is

important to note that I would not have come to understand it in such a way had I not conducted go-alongs. Doing so enabled me to also observe the practice in the moment and access those pre-reflexive knowledges that constitute habitus, to think through the ways in which they relate to more reflexive biographical information.

In sum, for me, because of the different knowledges it encourages, the go-along affected not just the data collection but also the process of analysis. In this way, and as I have suggested, I found it a very productive method with which to work and think through my key questions. However, I also found that there was a key element of the method as practised that proved fundamental to its effectiveness in my research but which has not, thus far, been drawn out in the literature:

disruption of embodied knowledge, or in Bourdieu’s terms, practical logic.