Are we there yet? (more narrative data analysis)

Completing a PhD as a part time student involves more than a little self motivation and management of expectations. You become very aware of what motivates you, and what is most likely to slow you down. Following my last post, I have completed (insert massive relief here) all of the transcription of the audio data from my study. Amazingly, I have also written, edited and had accepted the first article in an international journal using some of the data, on a subject which is not the 'central' question of the thesis. I should be really pleased with myself. Perhaps the fact everyone in my house is recovering from chest infections, then flu, then another set of chest infections is taking the edge off things. The article is a big confidence boost, though.

Perhaps it's a good thing I can bask in the glow of the article and post transcription relief: I am facing up  with the last stages of my analysis-interpretation. This has involved going back to 'the plan' established last summer, which I've followed so far. In summary, this has involved:

• Coding all of the narrative data into one of my two main categories: 'self talk' and 'interactional context'.
• Coding within each of these categories for each participant.
• Creating two different 'maps' (previously discussed) - one relating all the themes of the 'self talk' (what I call 'how the story hangs together') and the other identifying 'patterns' of connections between codes in each category. 
• Creating cartoon images to complement this whole process, including a cartoon 'telling' of how I see each participants overall identity narrative. 

Of course, this list doesn't give you all the detail you need to clearly understand this whole process...the point is that I have already begun an awful lot of 'analysis', and have involved participants in that. I have produced some nice images, and had some wonderful conversations...except I have not 'answered' the questions I set out to answer. Yet. Are we not there yet?

Perhaps I am just at another of those points where it is possible to flag, to give up, to feel tired of it all. I understand from friends and colleagues that this is common enough. The last two days have seen me 'going back in' to the data and it has certainly felt the opposite of glamorous. I think I've just come from a very intense phase of creating and talking about the data at quite an abstract level - patterns, connections, reflections. I am now creating a set of memos of all of my data artifacts - transcripts, maps, cartoons, session photographs. This is legwork - legwork that will help me compare and link, annotate and begin to theorise, but the experience of going through the transcripts and summarising them felt...like starting again.

I take encouragement from my understanding of the process. Thankfully, I have been keeping a research journal and writing a draft analysis chapter for the thesis. In fact, I had forgotten I'd written some of that, so it was good to read these when I sat down; before the depression set in. In short, the process I am following is heavily influenced by Paul Ricoeur's approach to hermeneutics - the interpretation of texts. I won't go into details, other than to say it is a process that involves moving from explanation to understanding and back. To get to 'understanding' you need to explain, and explain better. Understanding starts with a structural understanding, of sorts, and then moves through the process of interpretation (reflecting, comparing, immersing and so on). Of course, I'm going to write a lengthy section of my thesis saying a lot more than that, but suffice to say that I'm back with the explanation. Can you hear the sound of me stamping my feet?

I guess I forget the detail at my peril. Like many people, I like the big picture, but those insights into creative transformations between action and talk will come from building up layers of insight - and those need gathering from each of those transcripts, cartoons, maps and session photographs I have in front of me. What I am learning is that I have to ignore the quiet voice that says 'there's nothing amazing here' - because it is from the very 'ordinary' accounts of participants that I will begin to identify some amazing patterns. Eventually.