CAPÍTULO VII. RECOMENDACIONES
Gráfica 6. Identificación de funciones de universidades públicas
All core and background interviews, and recordings from autoethnography and observations, were transcribed by myself, which also involved direct translation from Bulgarian to English. While translation inevitably shapes the research material to be analysed, being alert to the biases inherent in the process has hopefully minimised the effects of this step on the end result. As I translated all transcripts myself, I was able to ensure consistency in the decisions which are made as part of the translation process.
The transcribed and translated research texts were coded using NVivo qualitative data analysis software. The coding frame was continuously refined, starting from the themes emerging in the course of data collection, which were gradually brought into dialogue with the original research questions. In the spirit of grounded theory, coding emerged from themes in the transcripts themselves, rather than from preconceived theoretical concepts (Gardner and Abraham 2007). Only then were data coded in these terms related back to the theoretical framework. The final coding frame included 36 codes (see Figure 4-3).
Figure 4-3. Coding frame used in software-enabled analysis. Source: NVivo.
I moved repeatedly between coding and analysis, in a process of refining both the way the research questions were phrased and the way the coding framework was organised.
During this stage, abstracting from my findings involved significant changes to the conceptual framework of the study. An earlier research focus on embodied wayfinding did not make it into the final thesis, despite some interesting empirical data on the topic.
Instead, knowing time became incorporated as one aspect of the process of making travel time, and thus transport infrastructure, valuable (Chapter 5). The discussion of comfort and stress of Chapter 7 was originally intended to include also data on boredom as a different aspect of commuter well-being, but the amount of collected data on boredom was much more limited. This was partly a reflection of studying the metro commute with a group of participants for whom it was still relatively novel and eventful, and thus unwelcoming to conversations about boredom. For Chapter 8, which presents findings on
Number of coding references Number of items coded
Nodes\ \ Change milestones 751 84
Nodes\ \ Other people's behaviour 664 83
Nodes\ \ Navigating timespace\ Routes and navigation 584 84
Nodes\ \ Navigating timespace\ Organising time 570 82
change and sameness in commuting habits, further paper-based analysis had to be carried out. First, timelines for the changes occurring in each of the 20 core participants’
commuters were constructed. The timelines were used to develop inductively a typology of change grounded in empirical data. This typology, in the form of a matrix, was then related back to the data, with empirical material categorised according to the different parts of the matrix. At the final stage of data analysis, pseudonyms were assigned to all participants’ contributions, ensuring no individual can be identified in the final text.
Concluding reflections
My own position shaped innumerable aspects of how the methods for this study were chosen and implemented. While collecting data, I often moved back and forth across the insider/outsider boundary (Turner and Norwood 2013). I am from Bulgaria, but not from Sofia. I am a native speaker, yet particular turns of phrase give me away as a long-term migrant. In what was possibly the biggest source of confusion, I am doing a doctorate, yet my questions are often naïve and focused on the most trivial of topics – mundane commuting practices. The drawbacks with my positionality had to do with my limited knowledge of local transport politics, place references, and colloquialisms. All of these took a long time to get to grips with. For the most part, however, these ambiguities in my position seemed beneficial in making participants comfortable, and in establishing them as the knowledgeable party in every conversation we had.
One of my key concerns was the big demand on participants’ time which ride-alongs made.
I was aware that commuters were missing out on various relaxing and productive activities when I accompanied them. And yet, some of them found benefits in the experience of the ride-along for themselves:
“It is so nice to have an opportunity to talk about my routine. I feel like I have been given a platform! [laughs] It’s not the kind of things that people will generally have the patience to ask you about. But you ask me about all these details, and actually I’m surprised how interesting it is.” (Lilly 2014-01-18 PM)
“It was a pleasant conversation in the morning. It made me think about interesting things. They are interesting things, but they are everyday things, and if you don’t stop and think about them, they just pass you by.” (Nell 2014-08-5 PM)
Receiving such comments was gratifying and reassuring for me as a researcher.
This chapter presented the thinking behind the research design, the specific methods used for data collection and analysis, and the limitations which resulted from the methodological choices made. Despite these limitations, I believe the multi-method, in-depth engagement with each participant, sustained over an extended period of time, has generated empirical richness of a different kind than that provided by large or
representative samples, advanced quantitative analysis, or other tools available to transport and mobilities researchers. In the next chapters, I present the data generated by this approach, and consider how they might illuminate the usefulness of the 2012 expansion of the Sofia metro network.