Turns and twists. After last year’s big revelation about the variable constitution of data (hint: they are not just numbers), I continued my conversion from applied natural scientist (engineer) to social scientist. One of my struggles was revolving around the question of what type of data to collect for my PhD – to make the research rigorous and relevant as well as keep my whole enterprise to practicable proportions. As I have now learnt, the PhD journey is not a linear thing. Two steps forward and one step sideways – more like a fox trot dancing or suchlike.
Although we like to pretend that our research is a well-planned trip following a clear path with an accurate map, it is nearly always the case that we see sense in hindsight. When we step out of the jungle we start seeing the wood and its trees (read as: we can sift the story from the data). This is particularly true for social science relying on interviews, observations and document analysis (rather than a classical dataset of figures).
Analysis plays a role in this. However seeking out the data and deciding what data to generate in the first place is of course a crucial part of any research endeavour (PhD or otherwise). Depending on your research question, a decision will have to be made about the appropriate methods you can use (but also about ontology and epistemology – philosophical platforms). Since in my research I am trying to find out more about women activists for cycleways, their hopes and hurdles, a purely qualitatively method was appropriate. My research is not trying to be generalizable or replicable per se. It’s much more about telling a good story, in a credible way. My research is asking specific questions about a specific situation. A situation that is of human making, that is firmly sitting in its own space and time. A situation also that is seen, lived and described through my eyes (as researcher and as activist too) – I am involved, I am part of the story. (A constellation that natural sciences often still shuns to address bound by its positivist stance.)
My main concern was this: just how would you gather up seven years of campaigning in an orderly way? On the whole, I am using auto/ethnography as the main method (borrowed from anthropology, and adopted by sociology). Nestled within that there are different types of data strands (see end of article). To avoid the typical pitfalls of qualitative-data scientists (ie being too self-indulgent, carrying out so-what? research) I have devised some safeguards into my data framework.
First of all, on a bigger scale I am deliberately putting myself into new situations: I am comparing Newcastle to Bremen. This comparison to a new city is invaluable for mentally staying alert by crystallising out the differences (ie not becoming self-indulgent).As part of my PhD, I had the chance to live in Bremen for considerable amounts of time (months and months at end) to experience (and absorb as best as can) the situation there. Immersion… as the ethnographer calls it. Whilst in Bremen, I sought conversation with local activists. And not only activists, I also spoke to politicians and practitioners too (always armed with my trusty dictaphone and waving the informed consent form).Coming back to Newcastle, I was full of impressions, new ideas and angles. A transfer takes place. I described my data-collection pathway in this flowchart here. I am nearing the end of it now. And I am glad.
But what about capturing the story line? What about my journey, finding the turning points, epiphanies even, and becoming sufficiently reflexive (self-critical) … to notice my own changes and developments? After all, this is what auto/ethnography is all about.
In many ways, the story strands will emerge from the data analysis. This is mostly about re-reading (and re-watching) the material collated. I am noting with interest, again, that this is not a linear journey. There are circular elements. Starting from the position of a research question already limits your arena, arguably to a manageable acreage. Now having the arena I can roam relatively freely in its confines. I am collating my data (see below) which will shape the outcome at the end point of analysis, yet I am also changing in the very moment interacting with people, documents, reading books and papers, and being in Bremen, rather than in Newcastle. I am really looking forward to the 31 December 2017, when data collection officially ends and analysis officially starts. It is then, that I can then put these two scales together: changes that I am already aware of (f.e. from value-free engineer to world-viewing sociologist), and changes that I will only be able to spot once re-engaging with the data.
So what sort of data will I have collected by 31 December 2017?
18 hours of videos
To work through several years of campaigning (2010-2016) I committed myself to assembling a retrospective video diary. I carried out a mid-term review a couple of months back, see here. The diary was collated in 2017 and should show not only show my involvement in the years 2010-2016, but also my development in 2017.
Also throughout 2017 I am writing a reflexive field diary. It started as a weekly diary. From 1 October (to the end of the year) the frequency will be pushed up to a daily entry to capture the last stretch towards the finishing line (of the data collection).
Over 1,000 entries
In addition I have an event diary dating back to 2015 (when I started my PhD). In there are listed events such as presentations to conferences, meeting fellow activists or attending webinars. The event diary helps me to see my level of engagement with the PhD subject.
At the end of the data collection I will have completed my schedule of interviews (taped and with consent) held in Newcastle as well as Bremen.
About 200 posts
My weekly blopgposts will also help to chart my journey in time.
Throughout 2018 I will put the strands together. I give myself a year to analyse and write it up. It feels as I have all the puzzle pieces soon, I will then have to assemble them into a coherent picture. Wish me luck.