Methods of Data Analysis

3.4.1. Analysis of Qualitative Data

Qualitative research deals with words, experiences, stories and behaviours. It can produce understandings of social processes in a way that attempts to offer explanations about how and why individuals, households, communities and other human groups think and behave in the way they do (Barbour, 2008). The goal of qualitative research is not necessarily to identify how many people possess a specific opinion, but to understand why the opinion of one individual might differ to another and to produce theory on the wider implications of such variation. The present study employs a qualitative approach to both data collection and analysis due to the fundamental goal of understanding and comparing priorities for adaptation across Scottish island communities.

After undertaking the data collection methods described in Section 3.3, the empirical qualitative data was analysed to produce results and findings about adaptation in Scottish island communities. Initially, the information collected during policy mapping and documentary analysis was reviewed informally to gain

an understanding of the concepts of ‘adaptation’ and ‘community’ in the context of

the case studies. The qualitative data collected during deliberative workshops consisted of transcripts, written participant workbooks and hazard-impact- consequence posters that were colour-coded in terms of risk factor by the participants. Having collated and examined these data, the key impacts of climate change in each case study were identified. These results directly contributed to the design of focus groups that were used to gather data on issues, factors, motivations and priorities for adaptation, as well as to test the utility of scenario-based community engagement using hypothetical vulnerability mapping. This section highlights and explains the approaches undertaken to analysing qualitative data gathered during focus groups and interviews in the case studies.

3.4.2. Grounded Theory

The interpretation of empirical qualitative data was a central aspect of formal analysis within the research. This phase of analysis employed a grounded theory approach using coding as a technique to rigorously analyse the data. Originating from Glaser and Strauss, ‘grounded theory’ is “the discovery of theory from data…systematically obtained from social research” (1967, p.2). Within their work, Glaser and Strauss stressed the importance of generating new theory from qualitative data rather than focusing solely on applying existing theories to data. They argued for the advantages of letting empirical data drive the production of theory rather than attempting to fit pre-defined theories to the data. Grounded

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therefore draws on inductive arguments to support conclusions, contrasting with theories that have been based solely on assumptions made by the researcher which are rendered invisible within deductive approaches (Glaser and Strauss, 1967).

The research favours a stakeholder-led approach to exploring small island adaptation, where community perspectives and experiences form the basis of investigation. Therefore, a grounded theory approach was employed to develop theory on small island adaptation through themes that emerge inductively at the community level. However, in contrast to Glaser and Strauss, the current research also applies existing adaptation theory to the empirical data. If a grounded theory approach is paired with the application of existing theory during analysis, it could lead to more nuanced and detailed understandings of small island adaptation. A dual approach was employed to rigorously analyse the empirical data. Grounded theory analysis was conducted initially, followed by the application of existing theory and knowledge from the adaptation literature.

3.4.3. Coding

Coding can be used to analyse qualitative data when employing a grounded theory approach to research (Robson, 2016). When coding is applied to qualitative data, it can uncover patterns and themes that aid understandings of relationships, linkages, similarities and differences (Cope and Kurtz, 2016). A key feature of

coding is the iterative comparison and analytical questioning of participants’

responses leading eventually to the generation of theory from the data. Responses can be coded and compared not only across focus groups and interviews within one case, but also across focus groups and interviews between multiple case studies. With this in mind, coding can be a beneficial method of analysis within research that uses a multiple case study approach. Coding was used in the present study to identify and understand the issues and priorities for adaptation in the case studies. The use of coding enabled a cross-case comparison of community priorities for adaptation and the reasoning underpinning these priorities. As an iterative process, this led to the emergence of key themes grounded in the data that formed a major set of results within the study. This led to the development of findings on the wider implications of adaptation to the impacts of climate change in Scottish island communities.

In practice, the process of coding was undertaken systematically in order to analyse the qualitative data gathered during focus groups in a detailed and in- depth manner. NVivo software was used to organise and code the data. Focus group transcripts were imported into the software and organised according to case study. The research adopted an iterative and strategic approach to coding and the qualitative data was analysed and interpreted with the core research questions in mind. Initially, broad-brush coding was undertaken for each focus group, as well as the individual interviews from Westray. This approach involved a broad and brief exploration of each transcript, without becoming involved in finer details, which led to the identification of overarching themes. For example, transport infrastructure emerged as a broad theme across all three case studies during initial

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broad-brush coding. This preliminary phase of coding led to increased familiarisation with the data, and the overarching themes became the first codes that emerged from the datasets. A more detailed approach was employed in subsequent rounds of coding for each transcript as described below.

Qualitative data has many layers and can be examined through various analytical lenses. Descriptive or inductive coding – where in vivo codes are produced based on the terms and phrases used by participants - is a type of analytical lens that can be applied during coding to categorise the data (Cope and Kurtz, 2016). Analytical coding offers another approach to analysis, where the descriptive codes are further examined in relation to theory-based themes present in the existing literature (Cope and Kurtz, 2016). Therefore, it was important to examine the qualitative data from both inductive and analytical coding approaches in an iterative process. Inductive coding, where codes emerge from the data in a grounded theory approach, was undertaken before theory-led coding. Inductive coding did not involve the use of any preconceived questions or themes. Instead,

themes emerged from the qualitative data in participants’ own words. Emerging

themes were grouped into categories such as ‘Lives and Livelihoods’. During later

iterations of inductive coding, sub-categories emerged within each broad category. For example, the sub-codes ‘Industries and Economy’ and ‘Cultural Heritage’ emerged within the ‘Lives and Livelihoods’ code. Eventually, it was possible to form comparisons between the case studies using the codes and sub-codes that were grounded in the data.

Following several iterations of inductive coding, an analytical theory-led coding approach was employed. Theory-led coding involved the application of pre- defined themes to the data. In this study, the themes applied during theory-led coding were derived from the key debates and theories outlined in Chapter 2. Five theory-based themes were applied to the data: (1) Responding to Harm, (2) Developing Networks, (3) Defining Responsibility, (4) Upholding Societal Values and (5) Transforming Societies. Again, each code contained a range of sub-codes that were also influenced by the literature. For example, the sub-codes

‘Connections and Relationships’, ‘Communication’ and ‘Coordination’ were part of ‘Developing Networks’. Theory-led coding offered a new way of looking at the data and allowed for links to be made between existing theory and participant responses. Grounded theory analysis could then be linked to existing debate in the published literature. Overall, coding offered a means of rigorous and iterative data analysis.

3.4.4. Scenario-Based Community Engagement Using Vulnerability Mapping

Analysis of qualitative data gathered during Westray focus groups enabled a comprehensive examination of the utility of climate projections and vulnerability mapping as tools for scenario-based community engagement within the case study of Westray. This phase of analysis aimed to dissect the ways in which participants responded to a map conveying hypothetical vulnerability to sea level rise in Pierowall Bay, as well as published projections of sea level rise for this area. It was important to assess how participants responded to scenarios of vulnerability to

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sea level rise, and particularly the level to which respondents engaged with the vulnerability map and sea level projections. Participant observation can be a beneficial technique for interpreting the behaviour and actions of participants, in turn leading to improved understandings of the experiences and perspectives underpinning these actions (Robson, 2016). Participant observation was employed during this element of the Westray focus groups in order to gauge participant reactions and responses to the tools presented with little researcher involvement. It was important to initially allow respondents the freedom to discuss the material, and the implications for Pierowall Bay, in any manner they chose whilst the researcher acted as an observer. Questions and probing were then gradually introduced as part of a semi-structured approach to assessing the utility of vulnerability mapping and climate projections. Analysis of the data collected during this phase of research indicates whether respondents showed an active interest in the map and projections, and ultimately whether vulnerability mapping could be a useful tool for community engagement in adaptation planning.

This analysis involved an exploration of the Westray focus group transcripts. Specific sections of the focus group transcripts, where participants had been provided with the hypothetical vulnerability map and sea level projections, were subjected to analysis. This phase of analysis was undertaken after rigorous coding had been applied to the data as described in Section 3.4.3. At that point, the researcher had developed a high level of familiarity with the transcribed data and codes. The codes produced during previous rigorous coding were useful in providing background context for participant responses to the vulnerability map and sea level projections. Previously coded data was re-examined from a new perspective and three core questions were applied to the data:

1. How did participants initially respond to the vulnerability map and sea level projections - actively, passively or not at all?

2. How did participants attempt interact with the materials?

3. How did the materials encourage discussion among participants about future adaptation in Westray?

Subsequently, participant responses were categorised based on these core questions. It was then possible to draw out key themes across the focus groups based on how participants had engaged with the materials. For example, a common theme across all Westray focus groups was the willingness and ability of participants to actively contribute to interpretations of local vulnerability to sea level rise. Participants were keen to offer their own understandings of local vulnerability based on their knowledge of coastal land around the island. Full results of the analysis are described and interpreted in Chapter 4. Overall, the analysis of focus group transcripts, using the aforementioned key questions as a framework, enabled the utility of vulnerability mapping and climate projections as tools for scenario-based community engagement to be assessed. The analysis produced interpretations about the implications of employing such tools for engagement at the community scale within adaptation planning.

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3.5. Conclusions

The methodological considerations of the research have been discussed in detail within this chapter. The chapter has reported the methods of qualitative data collection and analyses undertaken to address the research questions and aims. A multiple case study approach allowed cross-case comparisons to be made during the analysis stage. Analytical cross-case comparisons allowed a key research question to be addressed: what are the motivations and priorities for adaptation across Scottish island communities and how do they vary? Systematic selection of the case studies was a fundamental part of the research. The study used policy mapping and documentary analysis to develop understandings of the current state of adaptation in the Scottish Islands as well as the key components of

‘community’ in each case study. Deliberative workshops identified the key climate

impacts affecting the case studies in a stakeholder-led approach. Focus groups were the chief method for investigating issues, factors, priorities and motivations for adaptation, as well as exploring the utility of vulnerability mapping for community engagement. The research favoured a grounded theory approach to the analysis of qualitative data. Theory-led data analysis was also undertaken as a means of supporting grounded theory analysis in a rigorous approach. Ultimately, the analysis of qualitative data gathered during focus groups allowed the research questions to be addressed. Chapters 4 and 5 present and discuss the results of the analyses described in this chapter. Specifically, Chapter 4 reports and examines the outcomes of climate projections and hypothetical vulnerability mapping when used as tools for scenario-based community engagement in Westray. Furthermore, Chapter 4 considers the utility of the aforementioned scenario-based tools for adaptation planning according to the results of the research. Chapter 5 presents and interprets the results of focus groups to investigate motivations and priorities, as well as issues and factors, for adaptation to key impacts of climate change in the case studies.

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Chapter 4: Assessing the Utility of Scenario-Based