Oportunidades para las empresas españolas

The process of data analysis can be described as “the search for patterns in data and for ideas that help explain why those patterns are there in the first place” (Bernard, 2011, p.338). As noted above, data were generated in this research through a number of methods (e.g. surveys, individual interviews and group interviews). Once the raw data from these methods had been collated (in the form of survey responses or interview transcripts), the data were read, re-read and coded to draw out key ideas and issues32_{. A code is often a}

short phrase or word that symbolises a piece of the data (Saldaña, 2013). Charmaz (2006, p.45) states that coding “generates the bones of your analysis” and therefore forms an essential part of the analysis process. This process of coding was done manually using traditional writing materials33_{, since it is argued that it can give you more ownership of the}

work and control over the analysis (Saldaña, 2013). The following table (Table 6) includes an extract of conversation with a LACYP participant and is intended to provide an illustration of the coding and categorisation that was done as part of the analytic process.

32 _{The participatory tasks used e.g. timelines and life-maps were not included in the analysis, since they were}

not used with all participants and their purpose was to encourage LACYP voice during the interviews, as opposed to facilitating the creation of visual data.

Table 6: An extract of an interview transcript showing the codes employed in the analysis of data

Analysis was ongoing throughout the research process to help inform later phases of data collection and analytic memos were noted as I went along. Analytic memos are “sites of conversation with ourselves about our data” (Clarke, 2005, p.202). As a result, some codes

CW: Are you able to tell me a bit about your school experience?

Nathan: Well I had a bit (laughs), it was a rumble and a tumble basically. Because I got held back a year, ‘cos I moved around a lot. And then when I, ‘cos I was living in Sharpton and then when I moved back to live here in Yarbury, they felt like, if I went back into year 11 then it would disrupt my learning, and my GCSE’s, and that. So, they kept me behind a year, so I went back into year 10. I dunno it was alright to start with, and then I dunno, it kind of went (upside down gesture with his thumb).

CW: What do you mean by that?

Nathan: Like, I turned really like defiant and stuff ‘cos of like, all the stuff that was happening. I couldn’t really be bothered to follow any orders and stuff. I’d get the bus in and go out for a fag, stuff like that.

CW: Why do you think that you started to become defiant?

Nathan: Umm I dunno, it was like, probably because I wasn’t getting into trouble that much. So like yeah, I would get into trouble at school, but then I wouldn’t have any like, I dunno, I wouldn’t have any major consequences for it and stuff like that. And then I just kinda got fed up and bored, so yeah. Placement moves School moves Turbulence/disruption to education. Behaviour (negative) Disengagement from school/education (Form of control/ communication?) Lack of boundaries Attitude towards school/disengagement/ lack of priority?

were condensed into one and new codes were developed, as commonalities or distinctions among data became more transparent. The codes were then manually grouped into subthemes according to the reoccurrence of particular issues, patterns or concepts (Gomm, 2004; Saldana, 2013). The core themes (centred around context, relationships, value, and wellbeing) in which the subthemes were sorted were not decided on prior to the coding of data and this can therefore be considered a thematic analysis approach (Braun and Clarke, 2006). This process of thematic analysis took the form of Braun and Clarke’s (2006) six phase approach:

1. Familiarizing yourself with your data: Transcribing the data, reading and re-reading the data, noting initial ideas.

2. Generating initial codes: Coding interesting features across the data. 3. Searching for themes: Collating codes into potential themes.

4. Reviewing themes: Checking if the themes work in relation to the coded extracts. Produce a thematic ‘map’ [table] of analysis.

5. Defining and naming themes: Refining the specifics of each theme, generating clear definitions and names for each theme.

6. Producing the report: Selecting extract examples and producing the report.

(Braun and Clarke, 2006, p.87)

With this particular type of analysis, themes are not predetermined but rather ‘induced’ from the data (Ezzy, 2002). Theme names and descriptions were generated with the intent of capturing the essence of the themes in the most concise way possible. Table 7, below, is an example of how the codes transpired into themes.

Table 7: An example of how themes emerged through the analysis of data

Theme Sub-themes Codes

Wellbeing and Behaviour

Wellbeing as a barrier

Emotional, Social and Behavioural Difficulties (ESBD)

Lack of confidence; lack of self-esteem; anxiety; fear Pre-care experiences (trauma; abuse; neglect; attachment) Improvements

associated with wellbeing

Social interaction; team work; relationships Health-associated benefits (fitness; active lifestyle) Emotional/mental health (resilience; confidence; self-

esteem)

Impact of behaviour/attitude

Positive attitude towards school (aspirations, achievements, engagement; motivation) Negative attitude; disengagement from school (truancy,

exclusion, isolation)

Negative coping strategies (drugs; alcohol; self-harm)

It is important to acknowledge here that the social ecological model (see Chapter 3) did not directly inform the analysis, rather it was used as a lens through which to make sense of the themes that were generated. Harry et al., (2005, p.7) argue that it “would be naïve to think that pre-conceived beliefs and perspectives will not be brought to bear on the data”, and therefore it is impossible to remove all traces of the researcher (Clarke, 2007). With this consideration, I present a reflexive account in the next section.