D ATA ANALYSIS

It would be misleading to assume that the analysis process began once fieldwork had ended and all data were collected. To the contrary, attempting to make sense of the data has been an ongoing process, which has been entwined with the tasks of accumulating data in the field, as well as a period of

‘sorting’ data (see below) and with writing drafts of the thesis. Because I was not seeking to demonstrate or ‘test’ an existing hypothesis, an inductive or

‘bottom-up’ approach to analysis was taken, whereby meanings were explored in an open-ended manner (Thomas, 2006), and I worked ‘upwards’ to identify emerging themes and patterns across the data.

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In line with the research aim and questions, the goal of data analysis was to identify emerging themes and patterns in participant’s narratives about: the way they identified themselves in relation to their ethnicity; the ways that they ‘do’

family; and their interactions with transnational/translocal spaces and places in the city. I will outline the ways I attempted to achieve this.

As was previously mentioned, all interviews were recorded and fully transcribed.

I decided to transcribe interviews word-for-word and to include any pauses,

‘um’s’ and also laughter. As well as this, I added to the transcripts any notes I had made (during the actual interview) about the interviewee’s behaviour, for example, if they were being humorous or appeared reluctant to discuss a particular topic. These observations were indicative of the ‘performance’

element of the narratives and can potentially be very revealing in themselves (Elliot, 2005). To avoid introducing another layer of interpretation onto the data, I have not edited the language used where the interviewee is speaking in English, but their first language is Greek, therefore not all language used in quotes later on in the thesis is ‘grammatically correct’. However I wanted to keep the quotes as close to their original form and feel they are still accessible.

The principal analysis of data loosely followed the trajectory of grounded theory.

As Herbert (2000:552) observes, the ethnographer ‘allows social order to reveal itself through extended fieldwork’, and seeks to unravel the ways in which the social world is understood and made meaningful by its members; this is not so easy to do if one enters the field with rigid categories with which data is analysed. My aim was for order to emerge from the field, rather than be imposed on the field using a set of pre-determined categories (Silverman, 1985;

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Herbert, 2000). Therefore, ideas were built from the ground up (Glaser and Straus, 1967).

Although providing a definitive account of the grounded theory approach is not straightforward, some of the basic components of the approach include:

simultaneous data collection and analysis; the generation of codes and categories from data; theoretical saturation and constant comparison between data and conceptualisations (Bryman, 2016). As I have already pointed out, data collection and analysis occurred simultaneously from the outset. When I finished fieldwork, I did spend some time ‘sorting’ my data in order to generate codes and categories. This involved multiple critical re-readings of transcripts and field notes in order to narrow-down the focus and identify meaningful patterns and themes across the data (Corbin, 2008). I used the computer software package NVivo to organise data; once I had re-familiarised myself with the interview data through transcribing and re-reading, I coded the material according to the topics and themes that were discussed (e.g. migration of the first-generation, parent-child relationships, transnational social spaces, male dominance). Some of these initial themes were then divided into sub-themes, for example, migration of the first-generation was then sub-coded into reasons for moving, settling in to the UK, return to Cyprus and so on. This process, known as ‘open coding’, enabled emerging themes and relationships to be investigated and helped to un-pick the data.

One of the components of grounded theory, theoretical saturation, infers that a point is reached whereby new data are no longer illuminating the concepts or categories that the researcher is seeking to investigate. Because this was a smaller scale, in-depth study that was constrained by time, and the experiences

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of each family were so vast, while trends and patterns clearly emerged from the data, I cannot say that theoretical saturation was fully reached. However the trends and patterns that did emerge were certainly clear enough to make some generalisations.

I kept a research diary detailing my reflections and experiences throughout the fieldwork, particularly during participant observation, and this was used to corroborate and add depth to the findings (Hoggart et al, 2002). Observations helped to shape some of the questions in future interviews, as I sought to gain clarity or contradict things I had witnessed. I also selected observations to use in the write-up that either supported claims that were made in interviews or contradicted what had been said. The process of writing-up and drafting and re-drafting chapters also contributed to the ‘sense making’ (Schiellerup, 2008) of the data and, following the grounded theory framework, constant comparisons were made between data and conceptualisations. It is important to acknowledge that grounded theory provided a rough model of analysis in this thesis and the framework was not employed wholly. In reality, the analysis involved a lot of jumping between concepts and ideas, interviews and participant observation while attempting to apply codes and categories to the data. Thus, the analysis of data was not achieved while seated in front of the computer coding data, rather it was an on-going process which continued throughout the fieldwork.