The detailed process I undertook for organising my interview data ready for analysis is set out in the table below. Essentially, I used audio recordings in the analysis of half (n=11) of my interviews (no textual document) used written transcripts for the other half (n=12).
I transcribed half of my interviews (mixing up the order in which they were conducted) and left half as audio recordings and then analysed these in these two different formats. I transcribed 12 of the interviews myself using Dragon Voice Recognition Software (VRS) to avoid typing. There are precedents for this approach (Brooks, 2010; MacLean et al., 2004; Matheson, 2007; Perrier and Kirkby, 2013). I provide a detailed description of the exact steps for this stage of processing my interview recordings into data, including the free software that I used to anonymise my audio recordings, in Appendix 6.
I undertook the analysis of each set of interviews - x12 using transcripts only, x11 using audio recordings only - separately and in the course of analysis I also noted down (in a separate file created for this purpose) any observations I made or thoughts I had about the specific format of the data. A summary of the practical and analytic advantages and disadvantages of each method are outlined in the table below.
Table 2: Summary of the advantages and disadvantages of analysis using transcriptions compared with using audio
Transcriptions Audio recording
Easy to import Easy to import
× Significantly more data preparation time Significantly less data preparation time Quicker to pick up how to do it in NVivo × Slower to pick up how to do it in NVivo Quicker to scan back and forth across the text
to find sections
× Slower to find the exact section (more difficult to locate the start & end)
× Lose the affective dimension data and contextual information
× Retain the affective dimension data and contextual information in voice
Easy to export or cut & paste quotes Easy to export quotes (audio form)
× BUT need to have technology to share it and can’t use them in a paper doctoral thesis! So ended up transcribing quotes.
Transcribing audio recordings into written documents made the information available more manageable, but it was at the cost of rendering the interview less alive; freezing it, literally pinning it down onto a page ready for dissection. How else to manage the rich complexity of individual people with all their decisions over 50 or 70 years of adult life and their narratives about their decisions over their lifetimes? In this process of rendering, of making more manageable all that is encountered in these interviews, there was an inevitable letting go of the visceral intensity of live interaction. In order to draw any conclusions from research – not tp become self-undermining, as Hammersley describes it - we need to make it manageable. Transcripts rendered my experience in my interviews more manageable: I felt less implicated in them once they were text on a page; I gained distance from them, I carried them around, I read them in whatever order I wished, I poked at them and scribbled on them and I
extracted from them what I saw as relevant, what I needed and then I filed them away.
I found that I could do exactly the same carrying, re-ordering, poking, scribbling, extraction, filing and rendering with the audio recordings, though the technology involved in scribbling notes and thoughts adjacent to sections of audio recordings made the process less portable
and more dependent on information technologies that took time for me to learn. Paper documents still had the advantage of being more portable - data analysis on a paper document can be done anytime, anyplace, anywhere. Having audio recordings as the medium for data analysis had other advantages though: hearing my interviewees speak wasn’t as detached as reading their words; I felt myself drawn back into their world, noticed unspoken emotions, recalled histories revealed in accents and was more aware of my own presence in the interview. I also had a keener awareness of what could what didn't, get followed up; how partial these analytical findings might be.
On reflection the audio recordings revealed more of the fragility of communication between myself and the interviewee; I was reminded of the dance that had taken place between us: I was trying to both listen and guide the conversation. They were chewing over the questions, trying to articulate explanations of what had happened to them in life and sometimes struggling to provide coherent rationales for their decisions or choices, when they were often the result of specific and circumstantial webs of interactions.
What I also identified through this process was a greater presence within audio recordings of the emotion within the stories and the story-telling process. Thomson et al (Thomson et al., 2012) have argued that this can be present in text if you take the time to look for it, if you read it slowly and carefully - even text written by past researchers re-read by new
researchers some 10 years later. They reanalysed the observation notes of interactions between a young mother and her baby (originally part of a psychoanalytic infant observation study). They used texts written by the original researchers and made their own analyses, paying attention to the 'feel' of the episode in their own readings. They then compared these with the analytic narratives of the original researchers. In doing so, they revealed 'the textual mechanisms through which affect is housed in material' and drew out 'the unspoken' present in the text, stored in the text (citing Ogden, 1999) further (Thomson et al., 2012: citing Lorenzer) that 'scenic material can be encoded within and communicated by texts’ (p317).
I concluded audio recordings could be used more in analysis, not only on an equal footing with transcriptions, but as one that retains more of the ‘affective dimensions of meaning making’- affective dimensions being 'immediate, embodied sensations' (p320) - that Thomson et al are keen for researchers pay attention to in their analysis. The process revealed to me something of what Savage describes as ‘the messiness and indeterminacy of
the research process itself’ (Savage, 2010: x), and that research is, itself, socially constructed and the rules and conventions of its processes are also open to dissection.